On 2021-12-06 18:05:54, user FACAGIRL wrote:
What were the CT values for the PCR confirmed cases. I ask because PCR test only test for presence of virus and not infectivity - yes? I found the following CEBM/Oxford systematic review on this and the detail suggesting a lower CT value is better to use as proxy for infection - was based on cultured and PCR samples. Reinfection would be subject to the same limitations associated with PCR tests.
Thanks
On 2020-01-24 19:36:35, user Jeremy Ho wrote:
On 2020-01-27 07:01:41, user Perseus Smith wrote:
The paper points out valid concerns, but so do commentators below. However, the prediction model of such work is always contestable, as of today German researchers put the r0~3.
Would be curious to see contesting research articles.
On 2020-01-27 04:11:13, user Mavrick55 wrote:
A city the size of Wuhan would have at least 40K beds in their hospital’s combined with a population of 11M. Why was it 2 days ago we saw film of over crowded hospitals with dead in corridors. Build more beds fast adding 2 more critical care units to be finished in a week. I think the estimates given above are quite conservative actually. I believe a million or more will be infected by mid February.
On 2023-03-08 12:30:58, user Carlos Oliveira wrote:
This study has been published on Frontiers in Public Health: <br /> Routine saliva testing for SARS-CoV-2 in children: Methods for partnering with community childcare centers<br /> Frontiers in Public Health, 11, 1003158 - February 2023<br /> https://doi.org/10.3389/fpu...
On 2021-12-23 21:35:13, user Dan Ostermayer wrote:
is the negative VE for 91-150 days a typo?
On 2020-01-27 17:32:05, user Iddo Magen wrote:
Another work of mine, focusing on classification of frontotemporal dementia by microRNAs in plasma. Was just submitted to JCI.
Highlight: a handful of microRNAs can classify FTD with high precision, using machine learning techniques (Figure 3)
On 2020-08-08 06:57:06, user Dr-Beesan Maraqa wrote:
Thank you for this study. I am struggling to find studies assessed the associations between stress and demographic factors, job title, and relation to social life.
On 2025-08-13 20:05:34, user Zach Hensel wrote:
This preprint was cited in a movie that was released on streaming media platforms today called "Inside mRNA Vaccines - The Movie". The movie was produced with substantial participation by the REACT19 organization, with which at least two of the authors of this study are affiliated.
The declaration of interests section of this preprint does not include authors interest in the new movie, and the movie attributes the result to "a Yale preprint" without noting the involvement of REACT19 in recruiting for the study.
To say the least, the movie is problematic on the facts. It is being most heavily promoted by Peter McCullough, who is currently selling the "Ultimate Spike Detox" supplement for only $80.99 every 30 days.
Another movie was released on streaming video from the same production team last month ("Inside the Vaccine Trials—Lived Experiences") and also features study author Brianne Dressen. Dressen is thanked for her contributions in the credits for both movies.
On 2025-04-19 16:15:06, user Jan Stratil wrote:
I find it quite Strange that neither Point estimate Not confidence Intervall Changes in any way after including two statistically significant variables (Sex, Occupation). Can it truely be that they are Not associated at all with the decision to get the vaccine?
Typo?
On 2020-09-08 05:45:42, user Asher Zeiger wrote:
First of all, since you apparently don't know what what "peer-reviewed" means or why it is significant - Peer-reviewed is the bottom line standard for knowing if a scientific study can be taken seriously. It doesn't look at the resuklts of the study, it makes sure that the methods used to conduct the study were scientifically grounded and not flawed.
For several decades now, scientific studies have not been cited or used to guide clinical practice without being peer-reviewed.
Second, what does the study say about long-term health effects of people who get Covid, but don't die?
Before we downplay the pandemic, it's a good idea to look at it with an open mind. Maybe - just MAYBE - the epidimiologists and immunologists who keep telling us how awful it is know a tad more than the average Joe opining about it on social media....
On 2020-07-16 12:04:36, user MT Foley wrote:
Hi, The high seroprevalence results from Bergamo (57% infection rate by June 3) may present a counterfactual challenge to this model. I find it unconvincing that this busy district of northern Italy would have had little by way of previous exposure to the other four common corona viruses, or would experience much less cross-protection from such exposure to prevent infection rates climbing this high. Would welcome any clarification or thoughts, as the implications are substantial if on the back of such research public health policies or populations were to relax measures too soon.
On 2020-12-20 22:03:54, user Sam Smith wrote:
Congratulations for publishing the research.<br /> Would any of the modern anti-allergy antihistamines probably work equally well? For example bilastine tablets? Then there is Azelastine nasal spray. So one could use both oral antihistamine and nasal antihistamine at the same time.<br /> And take it with famotidine = Pepcid of course.
On 2020-04-21 23:43:04, user docmeehan wrote:
I'm not sure VA database born retrospective cohort analysis that declines to reveal drug dosing protocols contributes much to the science. Let's have those drug dosing protocols.
On 2020-12-07 04:30:15, user Murilo Perrone wrote:
Because the spreading of this information is so important, I suggest changing the license. See:
Why Sharing Academic Publications Under “No Derivatives” Licenses is Misguided
PS: Because of CC BY-ND I don't think I can comment on your maps in my youtube videos.
On 2021-06-06 13:42:01, user Maryam Pahlavan wrote:
Hej, How I canrequest for dataset?
On 2024-09-18 19:46:20, user Zach Hensel wrote:
The discussion notes: "One possible explanation for the anomalies observed in this paper is data errors."
This is the explanation. No further studies are needed.
Dropout artifacts in amplicon sequencing for the regions discussed in this paper are well known and described in numerous papers and technical reports. Novel mutation patterns in Omicron led to failures to amplify regions of the genome. This sometimes leads to assembly artifacts.
An expectation from this is that assembly artifacts will often include mutations from another common circulating lineage.
A cursory search for one of the variants described here (BA.1.1 with reversions of K417N, N440K, and G446S; 1/Dec-27/Dec/2021; USA) finds that 31% of such sequences carried L452R. This Delta-defining mutation was found in nearly 100% of non-Omicron sequences during this period. It was rarely found in Omicron sequences outside of sequencing artifacts.
I have not read further to know why USA is singled out as an anomaly or why BA.1.1 is discussed rather than BA.1; the same artifacts are observed for both.
Proposing "non-natural spread of infection" without conducting such a basic sanity check is inexplicable.
On 2024-04-28 12:21:49, user Henry wrote:
How much Berberine is required for the improvements to begin? Really interested in this study, thank you!
On 2020-08-20 17:21:13, user m knudson wrote:
This is very interesting data and I am grateful they put this together. To me the dosing data has the potential to be very informative. This data is promising but the analysis does not appear to have been adjusted based on study period. This seems very important to me as it looks likes patient outcomes improved with time. If other centers are like us, our CCP Ab levels also improved over time so I wonder if this could be why the high "titier" CCP appears to perform better, could it be that it was just given later in the study on average when other treatments may have improved.
On 2021-09-09 09:00:48, user Mc wrote:
Wouldn't these results look different if the previously infected who died were included? i.e. you can't know they wouldn't have a deadly reaction again which would drive the immunity of the "previously infected" category down considerably.
On 2021-10-11 16:09:28, user sentner wrote:
I'm surprised this article is still in a pre-print state. It's a hot topic and it's now been available for 6 weeks, which is plenty of time for peer review. Usually by now it's either rejected or accepted for wide publication in peer reviewed journals. It makes me wonder if, due to the politicization of this topic, some scientists are deciding not to review this document at all in a fair way.
On 2021-04-17 15:33:53, user Geng Wang wrote:
There are 11 cases (8+1+1+1) of B.1.351 in less than 800 samples, but the authors state "the B.1.351 strain was at an overall frequency of less than 1% in our sample". Did I miss something?
On 2021-05-25 06:21:14, user japhetk wrote:
The clinical site of this trial defines case as following and positive serology alone should be counted as a case. But instead in this manuscript, positive serology is not counted as a case.
Positive serology is greater in BCG group (7/148) compared with placebo (2/153). But in the result this is apparently not counted as a case as BCG group has only 2 cases.
Primary Outcome Measures :<br /> Positive for the respiratory <br /> questionnaire consisted of questions concerning the appearance of <br /> symptoms possibly, probably and/or definitively related to COVID-19 on <br /> visit 3. [ Time Frame: Visit 3 (90 +/- 5 days) ]
This is set on visit 3 (90 ± 5 days from the date of visit 1). The two <br /> groups of vaccination are compared for the primary endpoints which is <br /> composite. Patients who meet any of the following will be considered to <br /> meet the primary endpoint:
O Positive for the respiratory questionnaire endpoint when at least one of the following <br /> combination is met either at visit 2 and/or at visit 3:
-One situation definitively related to COVID-19<br /> -All four questions of symptoms possibly related to COVID-19<br /> -At least two questions of symptoms possibly related to COVID-19 as well as need for admission at the emergency department of any hospital and/or need for intake of <br /> antibiotics<br /> -At least four questions of symptoms probably related to COVID-19 one of which is "need foradmission at the emergency department of any hospital and/or need for <br /> intake of antibiotics"
OPositive IgG or IgM antibodies against SARS-CoV-2
On 2020-04-13 19:18:24, user Charles R. Twardy wrote:
Very similar to Benvenuto et al from 26 Feb, whom they cite as [4] and [9], but applying only to Italy. The earlier paper fit an ARIMA to worldwide Hopkins data through 10-Feb (then 43K cases) and, like this paper, found that we had just passed the peak. The previous forecast was absurdly optimistic. The current paper benefits from another month of data, and a single country.
Perhaps it does better. Eventually it's bound to converge, but it would seem the main value in the limited 4-day forecast is recognizing when the data has violated your model so you can put more weight on another one.
Benevenuto et al: https://www.ncbi.nlm.nih.go...
On 2021-09-22 14:02:47, user Carolina Faria Ferreira wrote:
I didn't understand very well... The conclusion was that the delta variant is more dangerous in the vaccinated group than in those who received placebo? Or was it the opposite? I got confuse
On 2022-09-29 15:48:37, user Gabriel Costa wrote:
Update: The work can now me cited in BMJ EBM. https://ebm.bmj.com/content...
The abstract is published but not the full paper, we're still working on ramifications of the main analysis.
On 2020-11-03 11:20:46, user Thomas de Broucker wrote:
one of my concerns is the validity of so little differences (although significant) of the SD values throughout the results knowing that the minimal pathological value admitted by neuropsychologists is -1,65 of the normal population tests results
On 2021-08-03 04:55:20, user Evidence wrote:
Sorry, but i have to correct you. The cause of death does not discard Covid-19 infection, wish can and is the primary cause of death linked to most causes in the study table. Covid infection is documented to commonly cause almost all the complications in the table and linked directly to them:
Let's just look at almost all of them, except a couple, one by one:
Cardiac arrest<br /> https://www.india.com/lifes...
cardiac failure congestive<br /> https://www.ncbi.nlm.nih.go...
Cardiorespiratory arrest<br /> https://journals.lww.com/md...<br /> https://wio.news/court-acto...
Chronic obstructive pulmonary<br /> https://www.businessinsider...
Emphysematous cholecystitis<br /> https://www.journal-of-hepa...
Hypertensive heart disease<br /> Search phrase "This shows that newly diagnosed hypertension was present in a significant portion of COVID-19 patients."<br /> https://www.frontiersin.org...
Sepsis/Septic Shock:<br /> https://www.global-sepsis-a...
So, there you are, 100% Pfizer vaccine failure in reducing mortality from Covid. Since Pfizer does not mention if either placebo or vaccine deaths were infected, we can assume they were...
On 2022-01-04 18:02:40, user Barbara A. Zambrano wrote:
What do the 21 “uncomplicated pregnancies” mean with respect to the babies, and how does this differ from the 29 who delivered healthy babies? Were the 21 babies born from uncomplicated pregnancies also healthy???
On 2021-10-18 00:04:56, user Geoffrey Graham wrote:
An encouraging study! Mobile HEPA filters may do a great deal of good.
Cigarette filters can also remove aerosols of biologically relevant sizes from an air stream. Seventy-five half-length filters in parallel will transmit enough air for a facemask wearer to breathe comfortably. Cigarette filters are very common around the world and so are other materials from which facemasks could be made. Building a 75-filter facemask from these materials is straightforward. If cigarette filters can also remove SARS-CoV-2 from an air stream (this needs to be tested), we could save a lot of lives this winter.
Here is a brief account of where things stand:<br /> See “The Saga of the Universal Anti-COVID Facemask: Where Things Stand”<br /> at:<br /> https://geoffreyjgraham.sub...
And here is a comprehensive (read “gargantuan”) account of all significant results.<br /> http://distributiveeconomic...
Clearly, the cigarette filters must be tested against actual virus. I am soliciting advice on the best way to do this. Beyond this, I welcome advice on what to do (and what not to do) next.
Geoff Graham<br /> gjgraham4health@protonmail.com
On 2021-08-09 21:08:09, user Richter David Oliver wrote:
One major flaw of this and the "Dresden"-study is the "self-reported" questionaire. Introspection is not a scientific measurement. Particularly extremely common symptoms like "tiredness" or "headache" are not suitable to diagnose any particular condition and are basically treated as reliable long-covid markers in the study. Also age -groups around 6, most likely did not fill out the questionaire themselves. A study like this would greatly benefit from data like respirometry or any quantifiable physiological or biochemical parameter that can be objectively measured. This would also allow a single/double blinded design.
On 2021-10-10 10:09:22, user kdrl nakle wrote:
Factors that drive that disparity? Obviously rag-tag American healthcare system that has little to offer to anybody outside urban areas unless they belong to elites.
On 2022-01-18 13:58:07, user William Henry Talbot Walker wrote:
Were all of the vaccinated participants studied for pre-existing cellular response or globulin levels before the vaccines were administered?
On 2020-08-14 15:40:32, user Ricky Turgeon PharmD wrote:
This article has generated some discussion on Twitter, including a thread where I provide some comments. https://twitter.com/Ricky_T...
In particular, I hope that the authors can revise and/or provide responses to address the following concerns:<br /> 1. Please provide the rationale for selecting July 31 as the date for interim analysis. Please also provide details regarding this interim analyses, including pre-specified stopping rules, who had access to the data. Although this manuscript is labeled as a "preliminary report", it would be valuable for the authors to explicitly state whether this trial is ongoing, and whether any changes to the conduct of the trial were made based on this interim analysis.
In version 1 of the article on this site, the Methods section had a sentence that stated "No concealment mechanism was implemented". This was subsequently removed in version 2 yesterday. Please clarify what is meant by this. Did the authors mean to imply that allocation concealment was not performed, or was this an erroneous statement intended to describe the unblinded nature of the study? Please also describe the process for treatment allocation and how allocation concealment was maintained.
The authors describe a change in the primary outcome in terms of timing of CRP measurements. However, I note that the clinicaltrials.gov summary of this trial previously had an entirely different outcome as the primary outcome, with CRP only described as an exploratory/tertiary outcome. The authors should describe the timing and rationale for switching the outcome from a clinical one (need for supplemental oxygen in the first 15 days post-randomization) to the inflammatory biomarker CRP.
Despite changing the timing of CRP measurements, data on this modified primary outcome of CRP was missing in a large proportion of patients at day 5, and in the majority of patients at day 8. Further details should be provided regarding the reason for missing data, how this was handled in their analyses, and how this should temper conclusions.
Finally, performing an interim analysis and disseminating their results in the midst of an open-label trial with subjective endpoints can pose challenges to maintaining impartiality. The authors should describe how they will mitigate potential allocation, performance, detection and attrition bias during the remainder of the trial.
I hope that the authors will seriously consider these comments.
Sincerely,<br /> - Ricky Turgeon
On 2020-11-21 02:14:12, user kdrl nakle wrote:
Less than 5% acquired in schools. Except that you have no idea about asymptomatic transmissions because you do not test for that. And that is 50% or more among children. So when a parent gets infected you simply ascribe that to "community acquired." And we should really believe your tracing, right?
On 2020-03-09 02:23:08, user Angel Paternina-Caicedo wrote:
Great to see more data on the COVID-19 epidemic. The following comment does not deal with study methods. Despite the study appears methodologically sound, the Supplementary Material is not complete at this point, and this is needed for a full assessment.
This comment focus on the broad interpretation on the results of this study. The results of this study does not support the conclusion that the disease has been contained in Wuhan.
The study does not show evidence of no circulation in Wuhan after containment measures.
According to the results of this study, these isolation and quarantine measures have been effective to curve down and delay the peak attack-rate. Despite this, so far, there is no evidence that the final peak attack-rate will be lower after these measures, meaning, the final tally of infected population may not differ with or without these containment measures. The epidemic is only a few months old, and COVID-19 is still circulating in Wuhan and elsewhere in the world.
Also, the economic costs of shutting down the entire city are not quantified yet. And this experience is unlikely to be able to replicate in most of the world.
The conclusion that COVID-19 is contained after these strong measures in Wuhan, based on results of this study, are misleading. Notwithstanding, the delay to achieve the peak attack rate may give some time for the development and testing of a vaccine.
On 2020-07-11 20:42:32, user Andrew Rasmussen wrote:
A far more likely explanation <br /> https://medium.com/@ageitge...<br /> The problem is that this weekly cycle is fake. It’s an artifact of how the data is collected and reported.<br /> Once a day, each medical facility reports its total number of deaths to a central authority. The overall rise in deaths reported by the UK is the sum of those numbers minus yesterday’s sum.<br /> This causes two important side effects:<br /> The sum for a single day can be (and usually is) incomplete. If any medical facility fails to report a number in time or under-reports, those deaths will be missing from the overall UK total and will eventually get lumped into a future day’s total when that facility catches up.<br /> There is a 1-day lag between each facility reporting and the UK-wide sums being reported to the public.<br /> The explanation for the weekly cycle is simple. Hospitals don’t all have full staffing on weekends, so they don’t have the bandwidth to perfectly report their numbers in time. Slow reporting causes a drop over the weekend and then a corresponding rise after the weekend. And because of the one-day lag in reporting, that shows up in the data as a drop on Sunday and Monday instead of on Saturday and Sunday.
On 2020-03-26 20:05:32, user Pedro Perez wrote:
Hemoglobinas could escape for diferent PH with cloroquina
On 2021-04-04 02:48:44, user SurgeonGate wrote:
Great Arab eye study! Arab Americans need more studies understanding their burden of disease compared to whites. Hopefully more soon!
On 2021-03-11 13:20:03, user Yan Gp wrote:
Even if it seems obvious, may I suggest to indicate in your abstract that you're talking of Soluble ACE2 ?
On 2020-07-12 18:45:47, user Mario Moisés Alvarez wrote:
Please let us know if this contribution has been useful.<br /> Very, very best from Mx!
On 2021-08-31 19:11:00, user Andy Loening wrote:
I think this is a thought provoking model. However, I think there are some major flaws with the model (as I understand from the pre-print manuscript) that severely limit the interpretation of the results.
The biggest flaw I see is:<br /> 1) "Case-investigation of potential contacts is not conducted." So the "no testing" cases have NO contact tracing, which makes this not at all a far comparison. If they included contact tracing/testing (status quo), I would believe most (or all) the difference between their "testing" and "no testing" lines would go away.
Other flaws I see<br /> 2) As a previous comment pointed out, they assume an initial rate of infections coming into the school at ~10-20-fold greater rate then actually infection rates. Similarly the 1 new case coming into the school per week may be too high.<br /> 3) They don't seem to build in any allowance for the ~36-48 hrs it would take a RT-PCR test to get a positive result back. The model doesn't seem to take any of this delay in testing results into account. This would obviously blunt the positive effects that surveillance testing would have.<br /> 4) They seem to treat their student population as a single classroom of 500 kids, and do not take into account that kids (even in the pre-covid days) are mostly segregated into their classrooms for the majority of the day.<br /> 5) There are no error bars provided for the model. Presumably the model has randomization within it, so there should be some variation in the outputs, it would be interested to see what the spread of the outputs are to gauge the significance of the findings.
I would be really interested in the results of this manuscript if it was redone with more appropriate assumptions. My guess is that there would be a much smaller difference between the surveillance and non-surveillance groups.
On 2020-04-22 09:08:23, user Pol Martin Ubando Fernandez wrote:
The economic impact of COVID-19 is longer and more intense than thought. Here's a material on socio-economic impacts of COVID-19 to the world and how to get through it: https://www.tomedes.com/bus...
On 2020-11-26 14:59:36, user Raul_Y wrote:
This paper is of ridiculously low quality. They even forgot to mention what dose of dutasteride was used.
On 2020-07-05 11:53:17, user OxImmuno Literature Initiative wrote:
On 2021-02-04 13:18:44, user Daniel Hervas Masip, MD, pHD wrote:
It is shocking to observe such a big difference between this meta-analysis and others, For example A. Hills group (https://www.researchgate.ne... "https://www.researchgate.net/publication/348610643_Meta-analysis_of_randomized_trials_of_ivermectin_to_treat_SARS-CoV-2_infection/link/6007a57ea6fdccdcb868a4b3/download)"). It also goes against Tess Lawrie meta-analysis preliminary data. The FLCCC members are not exactly a gang of gangsters; they are serious colleagues. It is starting to be very confusing.
On 2020-04-25 15:20:13, user Alex Backer wrote:
Very nice analysis. Here is a paper from 3 weeks ago that is very relevant to this: https://ssrn.com/abstract=3... (The Impact of Solar Irradiance on COVID-19). <br /> These two are relevant as well:<br /> https://ssrn.com/abstract=3... (Why African Americans are dying more)<br /> https://ssrn.com/abstract=3... (Why Latinos are dying less)
On 2020-04-24 20:01:13, user Christos Ouzounis wrote:
Nice follow up from https://osf.io/397yg/
On 2025-07-03 15:36:38, user Iraq Body Count wrote:
We commend the authors of the Gaza Mortality Survey (GMS), and in particular their Palestinian survey colleagues, for producing the first rigorous estimate of violent deaths in Gaza since 7 October 2023 which is completely independent of deaths documented and collated by Gaza’s Ministry of Health (GMoH). Also significant is that it contains the first data-driven attempt to estimate non-violent deaths, which has so far been lacking from any other source.
Also welcome is that, while the GMoH’s numbers are notably lower than those in GMS, its authors recognise that “By naming individual victims one by one, the GMoH endows each person with a measure of human dignity.”
In their concluding section titled “The Future”, the authors go on to state that “Undercounting of violent deaths by the GMoH is likely to persist.” However the level of this undercount cannot be consistently derived from a single snapshot survey, for the simple reason that the GMoH documentation is continually being backfilled, as we have discussed extensively elsewhere: https://iraqbodycount.substack.com/p/gazas-internal-list-of-the-killed .
The number the authors provide for the “comparable” period to GMS is one which the GMoH put out in early January 2025: 45,650. However in the GMoH’s list published March 2025, which the authors refer to elsewhere, this number had grown to 48,440. Latest GMoH data (15 June 2025) show that they have further increased their number of verified violent deaths for the period to 49,048 individuals.
In addition to the deaths listed by GMoH, another 4122 identified dead were known to them by 10 April 2025 but had yet to be verified for addition to their list. (See: https://iraqbodycount.substack.com/p/gazas-victim-details-and-victim-deniers ) On past evidence, most if not all of these names will eventually be included too.
In fact, had the GMS been conducted a year earlier (January 2024) the gap between its estimates and deaths listed by GMoH would have been markedly wider, as the GMoH has increased its numbers for that early period from an initial 14,121 to 26,987 (an increase of 91%). As the backfilling has progressed, the shortfalls have become appreciably smaller. A notable and predictable pattern has been that the higher the intensity of killing, the more has needed to be completed later. At any rate, these efforts by the GMoH have been constant (not to say noble and brave) and are likely to continue to reduce the difference between competently estimated and actually-recorded casualties.
So any figure given for the level of difference between a survey and the GMoH is temporary, provisional, and dependent on the date at which the GMoH data was accessed.
This exemplifies some of the difficulties in comparing a snapshot view such as is obtained by a survey with an ongoing casualty recording effort conducted on a daily basis. Any such comparison needs to be done with appropriate caveats which, if not included, might have the unintended effect of setting in stone a particular estimate of official “undercounting”, thus undermining essential casualty documentation efforts, particularly where such efforts are already being impeded by the most awful circumstances on the ground.
Hamit Dardagan and John Sloboda, Iraq Body Count, London, UK<br /> 3 July 2025
On 2020-04-14 17:31:09, user Troy D wrote:
Why arent they using Zinc?
On 2020-04-15 19:05:05, user disqus_NrkWMn1KOM wrote:
"collected data to emulate a target trial" - So, not a real study?
On 2020-04-15 22:33:38, user suradip das wrote:
Very interesting work. I have some questions -<br /> 1. Page 15 (Table 1): C-Reactive Protein is an indicator of cardiovascular disease. It is interesting that the authors chose to conduct the study in a population where 86% of all the patients had high CRP.<br /> 2. Out of the 84 patients receiving HCQ (90.5% having CRP>40mg/l and 45.2% having cardiovascular diseases) only 3 patients died (3.6%). In comparison, the group which did not receive HCQ but had similar weight proportions of high CRP and CVD saw 4.1% mortality.<br /> To summarize, there appears to be no significant difference in mortality rates when patients with CVD and COVID-19 are treated with HCQ versus a placebo.
On 2020-04-18 05:16:02, user rodger bodoia wrote:
Deeply flawed methodology. Others have noted (as did the authors) the obvious inherent bias towards those seeking antibody testing (maybe they had symptoms, maybe they knew someone who had symptoms). Also note the bias that is inherent in the method of using Facebook as the messenger with a brief period between posting on FB and the actual testing. We would need significant information on the other behaviors of people who use FB this frequently and whether they are more or less likely to have engaged in practices that would have put them at risk of acquiring the virus.<br /> Back of the envelope "smell test": 48,000 infections and only 69 deaths (as of April 17) is an infection fatality rate of 0.14%. This is inconsistent with Diamond Princess data, even if we adjust for age differences. Also compare with https://www.nejm.org/doi/fu... in which they did UNIVERSAL screening of obstetric patients from March 22 to April 4 in NYC and found 15% positivity of SARS-CoV-2. Without lots of population-weighted adjustments we can interpret this as pretty good evidence of roughly 15% prevalence in NYC (say roughly 1.2 million infections) and roughly 9,000 deaths for infection fatality rate of 0.75%
On 2020-04-18 04:00:54, user We'll See What Happens wrote:
"Participants were recruited using Facebook ads targeting a representative sample of the county by demographic and geographic characteristics"
What about past symptom characteristics? The obvious volunteers for this study would be people that had symptoms and want to know if they have it. This is not random sample at all. Reporting two sigma confidence for prevalence in the general population is completely irresponsible. This is an embarrassment for Stanford University.
On 2020-04-23 15:27:16, user mendel wrote:
The Heinsberg study doesn't exist yet, not even as pre-print. All we have is a press release that cites numbers with no context, and plenty of media echoes that forgot to mention that Heinsberg was the epicenter of the first big outbreak in Germany. The UCLA study is at the same stage. The Netherlands data supports a reasonable mortality rate, I believe? since the Netherlands have a high per capita mortality from Covid-19. And the NYC study is not a representative sample in any respect.
But go and look at "Outbreak of Covid-19 in Germany" (Lancet, preprint Match 31): of 217 high-risk contacts, only 11 were infected, all symptomatic (though some symptoms were mild). Contact tracing and containment is proven to work most of the time. (The Munich group had a mutation in the virus, which has not been seen elsewhere since.) With a rate of asymptomatic cases as high as it would need to be to support an infection fatality rate as low as 0.1%, containment should not work at all, but it does.
On 2020-04-19 08:11:58, user Shang Tsung wrote:
"and the German study came up with a 0.37% infection mortality rate ", this is not correct if you watch the original discussion in german of Prof Streeck, the leader of the study , i did , and what he said is :<br /> The current 0.37% infection mortality rate is based on INTERMEDIATE results, and is changing based on the new samples coming, with the trend that in the final result it wil be ACTUALLY LOWER than that, as they also inititally estimated
On 2020-04-22 05:16:57, user Marm Kilpatrick wrote:
This is published now in Lancet. Not sure why this isn't indicated above:<br /> https://doi.org/10.1016/S14...
On 2020-05-13 18:37:05, user Matthew Spinelli wrote:
Would recommend you present odds ratios from your conditional logistic regression instead of an unmatched t-test in table 2. Important work!
On 2023-10-22 13:47:09, user Rahma Menshawey wrote:
This research has now been peer reviewed and published here: <br /> https://bnrc.springeropen.c...
On 2021-01-18 20:12:59, user ad4 wrote:
The authors state that "only national lockdown brought the reproduction number below 1 consistently". This appears true for the first lockdown (23 Mar), but I'm not sure the same claim can be made about the second lockdown (beginning 05 November). I would strongly suspect that if Figure 1I showed data for December and January, we would see an increase in R above 1, despite tiered lockdowns at the time.
On 2022-04-18 19:58:31, user M. Akers wrote:
I am looking for some clarification on the connection between race and lower life expectancy:
It seems that for life expectancy to have dropped that significantly, a large proportion of young people would have needed to pass away in order for that drop to occur, yet we know that statistically, young people (e.g. <30 years old) did not die as a result of COVID.
Any clarification would be helpful as I am having a difficult time making the attempted connection suggesting that race is the only viable variable that explains a drop in life expectancy. With the pandemic, it seems there could be, and likely are, numerous factors contributing to your findings, yet nothing other than race is focused on.
Thank you.
On 2024-05-02 18:11:05, user Keith Robison wrote:
There is a great degree of interest in this preprint due to it being the first extended description of using the iCLR technology.
It would be very valuable to have details on how much Illumina short read data was generated from iCLR libraries and how much of that data contributed to the iCLR reads vs. what could not be used
It would also be valuable to report the read length distribution of the iCLR reads in greater detail - particularly since many interested parties cannot perform that analysis themselves on the clinical data sets
On 2021-04-05 17:44:22, user Armchair Hydrogeologist wrote:
Graph labels are swapped in Figure 1. Should be PepcidAC + Aspirin is 50% not other way around.
On 2023-05-30 13:27:21, user Nils Yang wrote:
This paper has been published in Journal of Child Psychology and Psychiatry, see http://doi.org/10.1111/jcpp...
On 2022-01-14 20:11:27, user Boback wrote:
Why are the event number exactly the same between vaccine arms in Table 1 in multiple places. Calculated point estimates and CI also the same for those. Did you have a coding error with events? I wouldn't expect so many exact event counts to overlap.
On 2021-06-10 17:55:41, user Steve Johnson wrote:
It is possible that fully vaccinated participants fared better because testing for infection was done 5 weeks or more after dose 1. Are there results for partially vaccinated participants tested 5 weeks after dose 1, but free from infection in prior tests?
On 2022-08-06 11:55:02, user Dieter Mergel wrote:
I have a question concerning the following passage:
"Previous work demonstrated that vaccination reduces severe COVID-19 and hospitalisation 46 and also the risk of Long COVID 7, 47. However, we did not observe evidence of qualitatively different symptom clustering in vaccinated vs. unvaccinated individuals, with either alpha or delta variants."
Does it mean: <br /> (a) Vaccination does not reduce the risk of Long Covid.<br /> or<br /> (b) Vaccination reduces the risk of Long Covid, but if (!) vaccinated people get Long Covid, then (!) the symptoms are similar to those of unvaccinated people.
On 2024-10-16 16:27:20, user CDSL JHSPH wrote:
I quite enjoyed this article. I found it very interesting as it proposed significant thoughts to how we can improve antibiotic treatment. I wanted to comment about some of the thoughts I had while reading this article. I first wanted to see if the results that were found in TB could be translated into other bacteria infections, such as staph. or strep. species. I also wanted to see if the results found for antibiotics in this article could be translated to other pathogenic treatments including antivirals or antifungals. Finally, in terms of future approaches could we see a systemic or ordered approach when it came to treatment duration whether bacterial, viral, or fungal in nature, or is it mostly going to be drug/ species specific?
On 2024-10-23 00:04:57, user Mohammad Shah wrote:
Hello!
Thank you for sharing this preprint. I really enjoyed reading it. Your application of techniques like MCP-Mod and FP for duration-ranging trials provides valuable insights into detecting duration-response relationships much more effectively than traditional approaches. I also appreciate how you highlight the risks of underestimating the MED in smaller sample sizes and suggest using conservative thresholds to mitigate those risks—this is such a critical point.
One thing that really stood out to me was how you clearly lay out the limitations of traditional duration-response methods, while proposing model-based techniques, like MCP-Mod, as a better alternative. Your comparison of different models and how they behave with varying sample sizes and regimen responses is especially insightful for optimizing TB treatment duration.
Like others have mentioned, it’d be fascinating to see how this approach could be applied to other chronic diseases, such as HIV or hepatitis. Is that something you’re considering or perhaps already working on? Additionally, applying these model-based techniques to real-world patient data, where comorbidities and adherence issues add more complexity, seems like a natural next step. It would be interesting to see how that plays out in practice.
I also found your discussion on model selection particularly thought-provoking. Your suggestion of using MCP-Mod alongside Fractional Polynomials under different assumptions opens up an exciting possibility for integrating multi-model approaches in early-phase trials. I wonder if combining these models, maybe in a hybrid MCP-Mod/FP approach, could improve adaptability, especially in trials with more heterogeneous patient populations—those with comorbidities or fluctuating adherence, for example.
Lastly, your use of simulations to predict treatment efficacy in the face of sample size imbalances touches on a key challenge in trial design. Have you thought about how this framework might be extended to adaptive trial designs? It seems like interim analyses could help adjust treatment durations dynamically based on early patient responses, which could make trials even more efficient.
Overall, this was a great article, very informative and forward-thinking!
On 2020-06-18 21:46:00, user Paul Gordon wrote:
Very interesting work, thanks for posting. I'm wondering if you can explain slight discrepancies in the # viral genomes sequenced. The text says 49, while there appear to be 48 red dots in the figure, and 47 'CZB' genomes matching the collection dates (March 25-28, May 6-7) in GISAID. Maybe an overlaid (non-offset) red dot? Two genomes refused by GISAID due to issues, or alternate names perhaps? Thanks for any insight you can provide.
On 2024-01-03 10:54:03, user Andres Ceballos wrote:
This paper has been publised on Frontiers. Cell. Infect. Microbiol journal:
Emergence and circulation of azole-resistant C. albicans, C. auris and C. parapsilosis bloodstream isolates carrying Y132F, K143R or T220L Erg11p substitutions in Colombia https://doi.org/10.3389/fci...<br /> Front. Cell. Infect. Microbiol., 21 March 2023<br /> Sec. Fungal Pathogenesis<br /> Volume 13 - 2023
On 2020-08-30 22:20:50, user JimboKatana wrote:
Is the virus truly decreasing in virulence or is it following the phenomenon of decreased severity that occurs with viruses in the summer?
On 2021-10-18 14:09:02, user S Wood wrote:
peer reviewed version now at
On 2021-06-13 18:06:46, user Tough Love 2019 wrote:
This study confirms what people with a modicum of common sense already know: that, with very few exceptions, only those who ignorantly and stubbornly resist getting vaccinated are ending up in the ICU with COVID-19. At this point in the United States only those who don't want to avoid becoming gravely ill or dying of COVID will in fact get sick and die from it. In effect, getting sick with COVID, once a fate at least partially beyond one's control, is now a matter of personal choice, except for those with compromised immune systems that don't respond normally to vaccines. The United States now must avoid hoarding tens of millions of vaccine doses for those who haven't wanted them during the months that they have been available. It is morally imperative to make these vaccine doses available to poor countries where lots of people want to protect themselves from COVID but are unable to because of the lack of vaccines there.
On 2021-05-12 01:30:10, user Heidi Connahs wrote:
Interesting paper! I have one comment though. I am noticing an increasing number of papers using the term post-exertional malaise (PEM) without providing any definition of what this condition represents. This is important because PEM is not a term widely known in the medical community and it has a distinct presentation. PEM is the worsening of a variety of symptoms following even minor physical or mental exertion and moreover, the severity of the impact is often delayed by hours or days and can take days, weeks or months to recover from. The reason why PEM is not widely known is because it is the cardinal symptom of the disease ME/CFS which has been significantly ignored and underfunded. PEM is unique to ME/CFS and any mention of PEM should really provide appropriate references to ME/CFS literature.
On 2020-08-04 22:41:08, user kdrl nakle wrote:
This is OK but I think the study is a bit premature in terms of time and developments in Florida.
On 2020-04-14 08:38:01, user Quyen Vu wrote:
I am not scientist or sort of , however, BCG vaccine has been already used in Vietnam in 70 or 80 years until now , now covid?-19 death rate in Vietnam today is zero (today April 14th) , yes 0? ?at current infected 265 and recovered 155 . BCG is total make sense to me .
On 2021-05-28 12:53:12, user rusbowden wrote:
Earlier, I pointed out that the study does not show that mask use fails to protect the individual, mostly looking at more meta data about mask mandates versus virus spread. It's simply not what the study is about. It is about the effectiveness of mandates. The data the researchers used for mask use comes from Washington IMHE, which urges mask use. And here I will point that the researchers seem to be outside their areas of expertise. This study also supports the idea that masks cause delays in upswings, which may mean that contracting the virus took place more while unmasked. We cannot make the leap to say that wearing a mask does not help the individual. It is irresponsible to do so.
There's a further problem with the robustness of this study, which goes beyond simple timing and groupings. It has to do with not holding other factors constant. For instance, did mask use cause people to breach social distancing guidelines, and how much enforcement was used in different states. There's a tale of 2 cities here in Massachusetts, Lowell, which was lax in enforcement and attitudes, and Cambridge, which levied fines. When you entered Cambridge, you see most people wearing masks -- especially during the day -- not so in Lowell. Surreptitious unmasking did take place at night in Cambridge, especially among men (who should be wearing masks if for no other reason then to make others feel safe around them -- another psych/social, which were not allowed discussed). But, Cambridge, a more congested city of the same population size, had less cases per population than Lowell -- which as I mentioned earlier only got off the high-risk level a couple weeks ago.
On 2021-05-25 19:41:53, user rusbowden wrote:
A further point needs to be made, before we throw away our masks -- that masks do not help the individual wearer. This research barely touches on that, thus is open to be used politically to cause virus spread. And if an individual thought that this research showed that a mask does not help the wearer, it could cause many to shed their masks when it would be dangerous.
Here in my city, we just dropped off the "high risk" or "red" category last week, which means too many spreaders were walking around town, many willy nilly. Should I still be wearing a mask, can it stop the virus from getting to me? This study does not answer that question. If masks help as many studies shown or at least indicated, then public health officials need help now in getting the message out.
Let's backtrack and attempt the assumptive leap for a moment and try to affirm that this study points to a yet-proven truth, that all the wearing of masks was futile, because of the ineffectiveness of the mask only, which even causes problems for wearers. Let's try to affirm that with a thought experiment. Imagine with me that what got invented is the dream 100% mask back in April 2020, that (1) when worn, causes no discomfort or infection in the wearer and (2) completely prevents any wearer from being able to catch the covid virus. What if any difference would this have made to the results of this study? The hypotheses this leads to have to do with how human behavior and politics help viruses spread -- even in the face of mask-wearing.
For instance, consider the work of Ngaire Woods, founding dean of the Blavatnik School of Government and professor of Global Economic Governance at the University of Oxford. In his article, "What factors have determined how well countries have done in responding to the pandemic?," Richard Smith, a fellow of the Royal College of Physicians of Edinburgh, writes that "Woods identified three factors that had a strong influence on how well countries did," and, "The single most important factor, she argued, was effective collaboration between national and subnational governments."
Could this be translated for our purposes here, to be that there was little "subversion" by the populace too, that more successful countries had fewer parties or funerals where masks were shed, events which I witnessed and attended. It only takes one bullet to hit a target, so catch the target when the mask is off or down under the nose. In other words, if you were a virus, how would you enlist "subversive grandmother soldiers," say, to unmask around their grandchildren, allowing a snaking trail of the virus to spread from household to household. How many people broke their social bubbles?
On 2021-07-13 11:53:38, user DflippinK wrote:
How many SARS Cov-2 genomes are isolated to a single strain?
On 2020-12-05 18:54:57, user Zed wrote:
Dear authors,
I'm pretty sure your preprint is now somewhere under peer-review, but I was wondering what are the main difference between your meta-analysis and Fiolet et al (https://www.clinicalmicrobi... "https://www.clinicalmicrobiologyandinfection.com/article/S1198-743X(20)30505-X/fulltext)"). It looks pretty similar or at least going in the same way.
Thanks :)
On 2020-10-23 11:44:52, user Alexander Samuel wrote:
Dear authors,
I fully agree with your introduction, discussion, and everything is done correctly in this paper. After scientific misconducts from Gautret et al. in Didier Raoult's IHU Marseille, and its transfer to USA through J. Todaro followed by Zev Zelenko's strange comments, there is clearly a situation that went out of control about hydroxychloroquine.
My comment on your work is that Recovery + Solidarity weight almost for 90% of the results, In a meta-analysis, I expect a significant effect of all (or most) studies, here it seems like the results are a new read of Recovery + Solidary, with comments on very low weighted unpublished or published clinical trials. Of course, authors mention that there is still no effect in the absence of Recovery, indirectly (published vs unpublished, high dose vs low dose). I think it would be important to not just make a "second read of recovery data" (exagerated statement, sorry for the way it is said). The discussion on the difference between high / low dose is what interested me most in your paper, and would be worth more comments or even analysis.
I would suggest more theoretical molecular biology bibliography (molecular effects of HCQ might reduce the immune reaction more than affect viral cell entry), more introduction elements on in vitro data (which clearly did not favor HCQ that much) for the next effort mentioned in this paper !
Anyways, this is a good paper since it is very honest and shows data properly, congratulations for this work.
Best regards.
On 2021-03-18 12:54:03, user H.C. So wrote:
This is an online calculator (intended for educational and research purposes only) based on the prediction model in this paper <br /> http://labsocuhk.ddns.net:8889/covid19/
Hon-Cheong SO
On 2020-04-24 04:44:30, user joe2.5 wrote:
I don't know if I'm the only one to totally miss, in this paper, the main point I should be paying attention to. Anecdotal data that started the idea that OH-chloroquine could be of value in treating Covid-19 indicated quick decrease of the viral load hen administered just at the start of symptoms or even before. I read the paper twice without being able to see any mention of the time from first symptoms to treatment. So the impression is that the study was not trying to answer the initial question.
On 2020-04-24 20:55:11, user wangkon936 wrote:
The issue with a "retrospective" study is that populations cannot be randomized. It is clear just looking at the data that the vitals and the biochemistry of the hydroxlchloroquine ("HC") or hydroxlchloroquine and azithromycin group ("HC + AZ") was inferior vs. the non HC or HC + AZ group. In other words the HC and HC + AZ groups were significantly unhealthier vs. the the non HC or HC + AZ groups. A randomized true clinical trial would have filtered this bias out, but a retrospective study structurally solidified this bias in. Thus, this study has a structurally solid bias that render's its ultimate conclusions suspect and of limited use.
On 2021-06-15 22:10:30, user Maurizio Rainisio wrote:
A major confounding factor, the referendum vote held on September 20-21 is dismissed as irrelevant. The voting sections were attended by 25 millions people, 57 % of those having the right to vote. Using the voting date in place of school opening in table 1 one can see a much better link, an average distance of a very reasonable 10 days and a much smaller variability, 16 of 21 regions being in the range 6-16 days.
Using the Google mobility estimate to measure workers' mobility is indeed inappropriate as in Italy most workers use public transportation that is not caught by Google, but this cannot justify the dismissal of the this covariate
Such a relevant policy decision like schools' closure deserves at least some confirmation. This is not provided by Sebastiani et al with their indeed poor paper, nor by some sensitivity analysis that could be performed by means of alternative methodology (eg by a deeper analysis of derivatives of the epidemic trendline that might help to better position inflexion points) or by by analyzing other similar events (eg the opposite event at the time of high schools closure in November or the school reopening in April).
On 2023-02-09 16:44:55, user lepromatous wrote:
Missing some citations here... Example: https://pubmed.ncbi.nlm.nih...
On 2020-11-18 13:37:42, user Dr Gareth Davies (Gruff) wrote:
Thank you for this important study.
I have some observations and suggestions regarding interpretation and reporting of this data.<br /> 1. A low or high P-value does not prove anything with regard to the effectiveness of an intervention. It only tells us whether we can confidently reject the null hypothesis or not. In this case, any treatment effect was obviously too small for a study of this power to measure. It does not mean there was no effect.<br /> 2. There appears to be a long time between onset of symptoms and randomisation and initiation of treatment (~10 days?). It takes up to a week for cholecalciferol to metabolise to 25(OH)D so it's not very surprising that by the time it did so, it was too late for these patients. The actions of 25(OH)D on renin gene supression and modulation of ACE2 expression need to occur much earlier to be beneficial in preventing an overactive RAS and cytokine storm.<br /> 3. The patient demographics show that the patient populations were overweight and obese, many with comorbidities (hypertension and diabetes) so again, it's unsurprising that this dose of D3 administered this late was not effective. This does not mean that D3 in general is innefective, merely that this protocol was not for patients of this type. I strongly suggest you make your conclusion statements more precise to reflect this, especially since Castillo et al have shown that administration of high dose calcidiol was very effective. Calcifediol is able to raise serum levels in hours compared to cholecalciferol.
It would be a great shame to report this as a failure of vitamin D3 to treat COVID19 in general when it was simply this protocol for patients of this type and late disease progression which failed for enitrely comprehensible reasons.
It was just too little too late.
On 2020-07-25 12:17:53, user John H Abeles wrote:
Hydroxychloroquine ( HCQ ) and Covid19
The negative observational and controlled clinical studies to date refer mainly to using hydroxychloroquine (HCQ) in serious, later stage, hospitalised Covid19 patients
In both the Solidarity/WHO study and the Recovery/UK study extremely high, even massive doses ( up to 6 times that recommended for early CoVid19 patients!) were used for unknown reasons - since the half-life of HCQ is around 21-30 days these daily massive doses could have caused very high blood levels and likely were fatal in some instances - so HCQ group deaths could have been caused by such high dose regimes, so probably skewed the results ..
Also this is likely the wrong group of patients to treat with maximum effect, in the first place — early Covid19 is the best arena for HCQ treatment in combination with zinc and either azithromycin or doxycycline...
It must be stated that no known oral antiviral for outpatients works maximally unless given quite early in disease eg oseltamivir/Tamiflu influenza; valacyclovir/Valtrex in herpes
Even iV remdesivir - a potent SARS-CoV-2 antiviral - didn’t achieve hoped for results in hospitalised patients
Later stage Covid19 patients are mostly suffering from the effects of hyperinflammation ( cytokine storm) and when viral titres are well beyond their peaks. Hyperinflammation can cause myocarditis which can certainly predispose to further cardiac toxicity.
[There are interesting thoughts that the hospitalised patients with cytokine storm / hyperinflammation in reality have a form of ADE ( antibody dependent enhancement of disease ) ie a hyperimmune reaction to a second SARS-CoV-2infection or as a result of a SARS-CoV-2 infection after a previous infection with a closely related virus]
HCQ was also used in the negative studies without added zinc which could be a design for failure, as one of the main, but certainly not only, antiviral actions of HCQ is as a zinc ionophore ie it gets zinc to enter cells much more easily where it can exert its added and established antiviral actions
HCQ is a known antiinflammatory and this action may be of some use in the hyperinflammation stage in hospitalised patients, but other more potent immunosuppressive ( and a few candidates that are nonimmusuppresive immunotherapies) could be more demonstrative in this regard.
Despite this there are some data to suggest benefit of HCQ even in hospitalised patients
For early Covid19 the usually prescribed course is for 5 to 7 days of around 400 mg daily HCQ with 100-200 mg zinc which would not invoke the long term side effects mentioned so often - and very few toxicities are reported even in long term therapy for autoimmune disorders. Any short-term arrhythmia concerns can be allayed by making sure of normal potassium blood levels
In the several thousands of outpatient Covid19 case reports published up to now , when used in early disease, there have been few if any major side effects noted.
(But in later stage, serious hospitalised patients many other drugs are also used, bringing into question the possibility of toxic interactions with HCQ. Also organ damage including myocarditis -heart inflammation-could be a particular predisposing factor in hospitalised patient toxicity predisposition to HCQ )
HCQ is a cheap, easily made generically available drug - and main manufacturers, like Novartis and Teva have donated billions of doses worldwide since the event of Covid19, so shortages, as some fear, for those taking it for malaria ( preventions or treatment) or for autoimmune diseases, like lupus or rheumatoid arthritis etc are highly unlikely
Here below are some pertinent positive references for further reading on the question of HCQ plus zinc plus either doxycycline ( my preferred choice because it isn’t associated with further small cardiac risk) or azithromycin
Note : Most of the successful reports of the use of HCQ plus zinc etc are in early stage, outpatients and not in late stage, hospitalised patients
The first link is a large data base (more than 50 studies ) on HCQ in Covid19 treatment
The second reference is an important review from a Yale University professor ...
The third and fourth are on a recent, large, well conducted observational study from Henry Ford Hospital ...
The fifth is an important outpatient study ...
https://academic.oup.com/aj...
https://www.ijidonline.com/...
https://www.henryford.com/n...
https://www.preprints.org/m...
https://www.ijidonline.com/...
https://www.preprints.org/m...
https://aapsonline.org/hcq-...
https://www.medrxiv.org/con...
https://www.preprints.org/m...
https://www.evms.edu/media/...
https://link.springer.com/a...
https://pjmedia.com/news-an...
https://www.medrxiv.org/con...
https://www.medrxiv.org/con...
https://www.middleeasteye.n...
http://www.ijmr.org.in/prep...
https://aapsonline.org/hydr...<br /> decide/
On 2021-11-18 14:20:47, user davehor1 wrote:
Table S6 Supplement looks to be missing, would be interested in seeing how you determine the total effect of vaccination on transmission.
On 2022-07-10 23:39:20, user Charles Warden wrote:
Hi,
Thank you very much for posting this preprint.
I consider the topics raised by this study to be important and interesting.
However, I have some comments and questions:
1) I agree that confirmation bias can be a contributing factor. However, I think true limitations in utility are also important. So, I am not sure if I completely agree with the statement "When results were not consistent with participant’s personal or family history, many participants found reasons to dismiss or discredit these results. This indicates a role for confirmation bias in responses to [self-initiated] PRS." For example, I might really want to understand the genetic basis for a disease, but the percent heritability explained by the PRS may be low and I could therefore be disappointed with the usefulness of a PRS due to a discordant result.
I have a blog post where I share my impute.me scores (along with others):
https://cdwscience.blogspot.com/2019/12/prs-results-from-my-genomics-data.html
I don't know if I would exactly say my response was "negative," but I certainly got the impression the PRS that I saw may have limited utility. In that sense, my view of the method was not positive, even if it did not evoke a strong emotional "negative" response.
Within that blog post, “ulcerative colitis” would be an example where there were different PRS for the same disease but very different percentiles (for the same SNP chip). So, I would consider that an example of the reaction that is described being due to something other than confirmation bias.
2) Did the interviewers respond when there were possible points of misunderstanding during the interview process?
It was acknowledged as a limitation in the discussion: "the researchers did not have access to participant’s PRS results and were unable to evaluate people’s understanding of their results".
However, it seems like that could be important. For example, there is a quote "Unfortunately, I do regret getting a PRS… I would have rather not known. I like uncertainty". Assuming that there were appropriate limitations to communicate, I believe a response from the interviewer might cause that quote to no longer reflect the subject’s opinion.
In general, there appears to be a noticeable emphasis on mental health in the article. My opinion is that this is an area where limitations are particularly important. If it helps, I think there are some additional details in this blog post for the book Blueprint.
In terms of my own impute.me results, I thought the "anxiety" PRS seemed reasonable (to the best of my ability to assess that). However, I also thought changes in conditions over time were important, and I thought there was potential for misuse.
3a) I think it is a minor point, but I don't remember receiving an invite to join a Zoom meeting for a discussion about my impute.me results.
I hope that I was one of the 209 candidates, but I was not sure if I could confirm that. I also noticed mention of categories like “medium” or “low” for one quote referencing a z-score of 2.5, but I only saw the continuous score distribution in the screenshots from my blog post.
3b) Perhaps more importantly, I tried to go back to sign in to check if I missed something.
In the Folkersen et al. 2020 paper, the link provided is for https://www.impute.me/. However, that link currently re-directs to a Nucleus website (https://mynucleus.com/).
Can you please provide some more information about the re-direction of the impute.me link?
For example, I submitted an e-mail to register on the new website, but I don't think I can see my earlier results anymore?
Additionally, I was confused when I couldn’t find the GitHub code provided with that paper: https://github.com/lassefolkersen/impute-me
4) Finally, but I don't think either of the 2 models that I see ("dismissed medical concerns" and "medical distrust") are a great description for myself. I think something like "curiosity" and "critical assessment" would be more appropriate for myself.
For example, I wouldn't say I distrust the healthcare system or medical research broadly, but I do think feedback and engagement is important. Thus, when I encounter problems, I submit reports to FDA MedWatch. Likewise, I contribute data/experience to projects like PatientsLikeMe.
Thanks Again,<br /> Charles
On 2021-06-30 12:12:11, user SinoBen wrote:
The language used here is seething with something I've not commonly found in the typical scientific paper.
On 2020-03-31 05:51:15, user Dmitry Shiryapov wrote:
Very interesting and promising speculations are reflected in the article. Definitely, some amendments should be done later, in conjunction with the pandemic development in Russian Federation, as a successor of Soviet Union. In any case, the authors have revealed a fertile soil for a number of publications in the future.
On 2020-04-02 09:47:58, user Muikari Giturua Wa Tiri wrote:
Its actually very easy to improve on this study because statistics out there exist on the number of people who are vaccinated. The study should possibly compare the mortality rate (possibly at some fixed point after the first case was reported) against vaccination rate. Analysing policies against numbers (mortality and morbidity) is a bit tricky in my opinion. The other thing is that I would either leave out morbidity (different countries are reporting number of infections differently....and I agree the same applies to number of deaths. <br /> Otherwise, I would say, well done to the authors. At least this is a start
On 2021-07-14 18:07:08, user Alexander Domnich wrote:
It seems that this SRMA lacks of data elaboration/transformation procedure at all. For instance, in our paper (icluded in this review) it has been clearly stated that no false positive results were detected. It is therefore obvious that the specificity is 100%. The overall specificity with 95% CIs was reported "The overall sensitivity and specificity were therefore 78.7% (95% CI: 73.2%–83.3%) and 100% (95% CI: 94.7%–100%), respectively". The authors instead stated that the specificity estimate was not reported. I agree that we had not reported the 100% specificity for each test analyzed in order to save the space. To us, it was clear.<br /> You only needed to calculate the 95% CI from the available raw data.
On 2022-06-10 15:22:41, user Tammi Kral wrote:
The published version of this manuscript can be found in Science Advances at the following DOI:<br /> https://www.science.org/doi...
On 2021-02-27 22:24:10, user ABO FAN wrote:
The latest version, version 3, seems to have the wrong reference number. For example, in the text, No. 11 is supposed to be a GTTC document that started in July 2020, but the corresponding MHLW page is from April 2020.<br /> Also, I do not think it is appropriate to use regression analysis to examine the effect of Emergency status. This is because even if an Emergency status is declared "after" the mobility and R(t) start to decrease, it will still be statistically significant. Figure 4 suggests that this is the case.
On 2020-06-13 23:46:41, user Norbert Bujtas wrote:
We have the missing component: a water soluble iodine complex! Edible and pure - patented. <br /> We have been waiting for the in vitro test fro 10 weeks but this research shows that we are on the right track.
On 2021-03-08 14:55:45, user NickArrizza wrote:
The BIRD meta-anaylsis was an independent review with no conflicts of interest, unlike this one. So is some discernment is required?
On 2020-04-17 16:39:15, user Thomas Clarke wrote:
These results would be more useful with more complete description of the propensity score used here.
The use of log(age) will I believe lead to very poor deconfounding of age-related group differences. The correlation between CFR and age varies as more like exp(age) - with an increasing effect as age increases. log(age) will make the difference between 40 and 80 the same as the difference between 20 and 40 - clearly wrong. Better (although still problematic) is to use just age, best to use a suitably fitted exponential of age. [Unless I've misunderstood what is meant here by log-transformed age, and the variable used in the analysis is actually the exponential of age].
For example: two populations of ages {20,40,80} and {40,40,40} would be viewed as similar in age-related mortality risk with this treatment whereas that is far from true.
More information about the treatment of other confounders - e.g. "admission data" which would appear to be an undefined scalar, and lesion area where the treatment of 0 is arbitrary and maybe problematic, would be appropriate.
Finally, information about the relative matching of the different groups used would help determine the sensitivity of the results to these issues: the sensitivity analysis stated does not address this. The Hosmer-Lemeshow test is helpful but in view of possible extreme nonlinearity in confounding variables I think good results could be obtained from this when in fact they are not robust.
This is an interesting analysis and it would be good to see how the results hold with more careful handling of age correlation to CFR. There may be similar issues with other parameters, but more information would be needed here to determine that, and the very strong nonlinearity of CFR with age stands out. All these concerns could be answered without additional test data, so it would be helpful if the authors could do this in more complete write-up.
On 2022-01-20 12:16:06, user Daniele Sardinha wrote:
10.4236/aid.2021.114039 foi publicado
On 2022-06-17 14:00:48, user Todd Lee wrote:
The authors are to be commended on a very important comparative effectiveness trial. Thank you! From a reporting standpoint:
Additional details worthy of reporting in Table 1 are the presence of "do not resuscitate orders" which would prevent intubation and the administration of co-interventions like remdesivir which may impact both the need for ventilation and mortality (CATCO, CMAJ 2022). Could the authors provide this information?
Additionally, the composite outcome is non-inferior. Yet, the composite contains two clinical outcomes which (a) differ in importance in that death is worse than ventilation and (b) may be related along a causal pathway in that patients who are ventilated are more likely to die. Could the authors revise the manuscript text or tables to include each component of the composite outcome separately by Day 28 or report death in the "adverse events"?
Additionally, could post-hoc subgroup analyses be performed by age, gender, vaccine status, and CRP greater than and less than 75 (recovery criteria).
I appreciate these were not pre-specified outcomes on clinicaltrials.gov, but they are essential to peer review and to contextualizing these results with the existing literature.
On 2023-04-26 15:28:46, user Matthew A Stults-Kolehmainen wrote:
There is a correction needed in the original preprint.
On lines 346-347, it should read, "Model B had a better fit index than Model A, as quantified by the cophenetic correlation 346 coefficient (c = 0.85 and 0.50, respectively)".
On 2020-08-29 21:03:28, user Sam Well wrote:
I cannot believe your work is being "advertised" as a hail mary when you conclude..."Additional results from larger randomised controlled trials are needed"
Please refer to the "sale" of your source:<br /> https://www.eurekalert.org/...<br /> https://www.dailymail.co.uk...
On 2022-04-11 18:32:10, user ReviewNinja wrote:
Thanks you for this fast publication. This publication confirms:<br /> - that people can be reinfected with BA.1 after delta infection<br /> - that people can be reinfected with BA.2 after BA.1 (but that this seems rather a rare event)
However, this publication shows some clear limitations that would need some discussion:<br /> - This publication gives an advice on testing policy, but does not discuss the testing policies at the moment of the study. This is important as this policy changed over the period of the study and was different during some periods for vaccinated and non-vaccinated individuals. Also a correction for testing behavior over time per age group would be useful. <br /> - The publication compares the number of reinfections (01/12 to 10/03) to the vaccinated population on 10/03. As the advice for vaccination for children 5-11 only came out on 15/12, this is an overestimation for the whole study period. The same is true for boosters in the younger age groups. <br /> Vaccination % at the different periods in the study: <br /> %For each age group (age in 2021) on: 01/12, 01/01, 07/02 and 10/03<br /> 5-11y (2 doses): 9 (probably most already 12y), 10, 20, 41<br /> 12-17y (3 doses): 0.5, 2, 11, 33<br /> 18-44y (3 doses): 7, 25, 70, 75<br /> 45-64y (3 doses): 13, 56, 88, 89<br /> The changing vaccination rate over time should be taken into account, or this comparison should not be made. Furthermore, most measured reinfections were in the first study period (<feb 7:="" 91="" of="" the="" 96="" reinfections).="" some="" other="" points="" to="" discuss:="" -="" the="" conclusions="" (and="" abstract)="" are="" rather="" strong.="" to="" advise="" a="" change="" in="" (pcr-)testing="" policy,="" at="" least="" reinfection="" versus="" residual="" pcr-detection="" should="" be="" compared="" discussed.="" reinfection="" during="" this="" short="" period="" measured="" in="" this="" paper="" is="" 0.16="" and="" 0.01%="" (with="" off="" course="" all="" biases="" and="" limitations).="" we="" know="" from="" a="" challenge="" study="" that="" 1="" 3="" young="" people="" (in="" these="" conditions="" in="" this="" small="" study)="" still="" test="" (low)="" positive="" after="" 28="" days="" for="" example="" (https:="" <a href="www.nature.com" title="www.nature.com">www.nature.com="" articles="" s41591-022-01780-9).="" -="" how="" was="" the="" n-gene="" cut="" off="" determined="" here?="" (it="" would="" be="" of="" added="" value="" to="" also="" confirm="" which="" percentage="" really="" resulted="" in="" detectable="" virus="" (specially="" for="" study="" period="" 2).)="" additionally,="" a="" look="" at="" the="" viral="" loads="" might="" be="" of="" added="" value,="" as="" done="" by="" the="" study="" by="" stegger="" (ref="" 9).="" they="" suggest="" a="" more="" transient="" infection="" upon="" reinfection="" with="" ba.2="" after="" ba.1.="" (would="" be="" nice="" to="" know="" the="" testing="" indications="" for="" these="" people="" as="" well.)="">
On 2021-11-01 21:20:05, user JS wrote:
Any plans of clinical efficacy trials regarding:<br /> 1) prevention<br /> 2) transmission (effect of index patient using the spray agains infecting contacts)<br /> 3) early treatment (efficacy of antibody spray started after infection against symptomatic illness)?
On 2024-12-10 13:41:12, user xPeer wrote:
Courtesy review from xPeerd.com
Summary<br /> The paper investigates whether urinary prostaglandin levels can be used as biomarkers for predicting labour, both at term and preterm. It involved a cohort study measuring prostaglandin metabolites in pregnant individuals, divided into several groups. The study concludes that while certain prostaglandins increase during labour, none of them show significant changes before labour onset, thus limiting their utility as predictive biomarkers. Additionally, several non-prostaglandin eicosanoids were explored, opening new potential avenues for further research.
Potential Major Revisions<br /> - Validity of Biomarker Prediction: The study asserts that the measured prostaglandin metabolites do not significantly change before labour onset, thus cannot be relied upon as predictive markers for labour. This raises doubts about the foundational hypothesis and merits a deeper exploration or re-framing of the research focus .<br /> - Sample Size and Group Classification: The number of participants in certain subgroups was limited, which may affect the reliability of the results. Specific sub-groups, especially those with preterm labour, should be expanded to enhance statistical power and conclusiveness.<br /> - Comparative Differences in Biomarker Levels: It's essential to clarify the lack of significant differences in prostaglandin levels between preterm labour and threatened preterm labour groups to avoid generalizing results. This would involve in-depth discussion on the clinical nuances and the potential impact on clinical practice.<br /> - Extended Data Analysis: The paper's discovery of new eicosanoids demands rigorous validation and replication in larger cohorts to substantiate these findings and confirm their relevance to labour prediction.
Potential Minor Revisions<br /> - Typographical and Formatting Errors: Ensure consistency in terminology and correct minor typographical errors such as the inconsistent representation of certain molecular names across different sections.<br /> - Detailed Data Presentation: Present the raw data and statistical methodologies more transparently in supplementary materials. Consider adding error bars in figures where statistical significance is discussed, providing a clearer depiction of variance and confidence intervals.<br /> - Clarity in Methods Section: Improve the descriptions of the experimental protocols, especially the mass spectrometry-based lipidomics analysis, to enhance reproducibility and understanding.<br /> - Graphs and Tables Enhancement: Ensure all graphical representations are adequately annotated, and employ color-coding where necessary to distinctly identify the different study groups and highlight significant differences.
AI Content Analysis for Post-2021 Works:<br /> - Estimated AI-Generated Content: Approximately 10% of the text, especially the repeated summarizations and some data interpretations, exhibit patterns that could be characteristic of AI-generated content.<br /> - Assessed Epistemic Impact: Given the AI content detected, the fundamental arguments and conclusions of the work remain sound. However, reliance on AI for section summarizations could introduce bias toward over-simplification and generality in explanations.<br /> - Recommendations: Review and potentially rephrase sections suspected of AI generation to ensure academic rigor and depth are maintained.
Recommendations<br /> - Focus Future Research: Redirect the focus towards the newly identified eicosanoids, ensuring their potential as labour biomarkers. Validate these findings with larger and more diverse cohorts to overcome sample size and variability issues observed in the current study.<br /> - Engage in Collaborative Studies: Collaborate with other research institutions to compare findings and standardize methodologies, thus enhancing the robustness of the research outcomes.<br /> - Integration with Clinical Practice: Develop a framework to integrate novel biomarker research into clinical trials progressively, ensuring findings translate into practical tools for predicting and managing labour, especially preterm labour conditions.
On 2021-03-09 14:22:05, user Alexis Alomoto wrote:
I would like to know, in which countries or where were the participants chosen to carry out this study?
On 2020-04-04 23:54:42, user Sinai Immunol Review Project wrote:
Keywords: chronic obstructive pulmonary disease, COPD, smokingE-2, risk factors
Summary: In bronchial epithelial samples from 3 different cohorts of individuals, ACE-2 gene expression was found to be significantly increased in both COPD patients and smokers relative to healthy controls. Across all test subjects, ACE-2 gene expression was also highly correlated with decreased forced expiratory volume in 1 second (FEV1), which may explain the increased COVID-19 disease severity in COPD patients. Former smokers were also found to show decreased ACE2 expression relative to current smokers and had no significant difference when compared to non-smokers.
Limitations: While the upregulation of ACE-2 is an interesting hypothesis for COVID-19 disease severity in COPD patients, this study leaves many more unanswered questions than it addresses. Further studies are required to show whether the specific cell type isolated in these studies is relevant to the pathophysiology of COVID-19. Furthermore, there is no attempt to show whether that increased ACE-2 expression contributes to greater disease severity. Does the increased ACE-2 expression lead to greater infectivity with SARS-CoV-2? There is no mechanistic explanation for why ACE-2 levels are increased in COPD patients. The authors could also have considered the impact of co-morbidities and interventions such as corticosteroids or bronchodilators on ACE-2 expression. Finally, given the extensive sequencing performed, the authors could have conducted significantly more in-depth analyses into gene signature differences.
Importance and implications: This study attempts to address an important clinical finding that both smokers and COPD patients show increased mortality from COVID-19. The novel finding that ACE-2 expression is induced in smokers and COPD patients suggests not only a mechanism for the clinical observation, but also highlights the potential benefit of smoking cessation in reducing the risk of severe COVID-19 disease.
On 2021-10-22 04:59:41, user Dave wrote:
The conclusions do not support the results. Excluding patients with CT > 35 was done post-hoc and this subgroup analysis should be secondary to the ITT population when analyzing the primary endpoint. Twice as many patients in the control group were excluded based on this criteria than in the IVM group which means there is no favorable outcome on viral negativity when you look at all the randomized patients.
If you look at how the clinical trial was registered, there were many exclusion criteria but the CT > 35 for the first 2 tests were not one of them. It seems suspicious to me that the authors would come up with this arbitrary threshold, which conveniently resulted in a positive result. This doesn't make sense either because the authors mentioned 3 definitions of covid negativity: a CT > 30, CT > 35, and CT > 40. You would think that the authors would exclude patients with CT levels 31-35 if they would later define those patients as being covid-negative, but they did not for unknown reasons.
Finally, the diagnostic test the investigators used defined a negative covid test as CT > 40. Not 30 or 35 but 40. You can see this from the EUA documents the company submitted to the FDA. It's also important to understand that the diagnostic test was validated as a limit test, meaning that it could only precisely and accurately tell whether a sample was covid-positive or negative. The test could not accurately and precisely distinguish between a CT of 35 and a CT of 36.
Hopefully the authors will address these points during peer review.
On 2020-04-24 16:08:53, user Rajendra Kings Rayudoo wrote:
To<br /> Prof.Dankmar Boehning<br /> I'm.from india and IAM f glad to hear a realistic approach to realtime infectious cases including asymptomatic and presymptomatic.and interested to know how it works<br /> Please explain how can I calculate the cases in india through your model .<br /> Regards <br /> Rajendra
On 2022-09-22 05:17:40, user Mehrdad Pedram wrote:
A peer-reviewed version of the above article has been E-published online ahead of print by the Journal of Autism and Developmental Disorders back on February 27, 2022:
https://link.springer.com/a...
Panahi Y, Salasar Moghaddam F, Babaei K, Eftekhar M, Shervin Badv R, Eskandari MR, Vafaee-Shahi M, Pezeshk H, Pedram M. Sexual Dimorphism in Telomere Length in Childhood Autism. J Autism Dev Disord. 2022 Feb 27. doi: 10.1007/s10803-022-05486-2. Epub ahead of print. PMID: 35220523.
On 2021-08-09 21:26:26, user CdSS wrote:
Where can I get the reasons why PhDs answered "probaly not/definitely not"?
On 2021-08-22 13:09:40, user Dan Elton wrote:
A major reason for hesitancy, which is sadly not mentioned in this paper, is the lack of FDA full approval. Once again the FDA is exhibiting a lot of dysfunction and showing they can't do cost benefit analysis at all. We've had what is effectively the largest Phase IV trial in history yet the FDA won't approve it. The risks are tiny - like a few in a million - like the risk of driving for a few months.
A lot of people are holding out for the full approval. See survey results i tweeted here: https://twitter.com/moreisd...
It's easy to demonstrate that holding up the approval is leading to hundreds of thousands of unnecessary cases and a lot of unnecessary suffering and death.
also see <br /> https://www.slowboring.com/...
On 2025-02-13 03:06:12, user Metin Çinaroglu wrote:
Update on Manuscript Status
This manuscript was initially preprinted as part of its submission to another journal. Following substantial revisions, including the removal of one author (with consent) and significant modifications to the manuscript, it was subsequently resubmitted and accepted for publication in BMC Public Health. It is now in the process of publication.
Since medRxiv does not allow withdrawals, we would like to note that this preprint does not fully reflect the final published version. Readers are encouraged to refer to the forthcoming article in BMC Public Health for the most updated and peer-reviewed version. Once available, we will provide the DOI for the published article.
For transparency, we acknowledge the differences between this preprint and the final published manuscript and appreciate the understanding of the research community.
On 2021-06-30 07:27:50, user AF wrote:
Also, neither loss of taste or loss of smell (both also mentally extremely burdensome symptoms) were not accounted for, although the prevalence of this symptoms is in the top 10 symptoms in the ONS study (https://www.ons.gov.uk/peop... "https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/bulletins/prevalenceofongoingsymptomsfollowingcoronaviruscovid19infectionintheuk/4june2021)")
On 2021-05-16 16:45:43, user Richard Vallée wrote:
This is exactly as expected because of GIGO issues with medical records. As a result most medical records dealing with Long Covid symptoms are invalid, are missing most of the relevant data and feature too much arbitrary speculation.
There was no coding until a few months ago. A LC coding requires a positive test. Most long haulers did not get a positive test, more than half from surveys and research, as most people were denied a test for most of the pandemic. Most physicians are still not able to recognize LC, let alone from the start. Many physicians who may recognize some of the more typical cases would not use this coding as they don't believe in it. Most long haulers had multiple experiences of gaslighting and having a mix of anxiety, depression and vague "psychological issues" on their record, there is no chance that medical records accurately reflect reality. Many are simply not going back to see a medical professional because their experience was too awful, they lost all trust in medicine, at least for the time being, and anyway reality was not recorded at the time and there's nothing they can do to change that.
This is like having a security system where cameras are active but most of them are pointed at a wall and none are recording anyway, it writes straight to /dev/null. Once the event that needs to be analyzed has occurred, it's too late, nothing was recorded. A system has to be switched on in order to work. It was explicitly kept off. So now the whole first year was entirely wasted because no one was actually paying attention and it's an active process, it requires people to pay close attention, react and adjust to new information, which still has not happened.
There was an opportunity to do this correctly from the start. Many people predicted Long Covid, as early as April 2020, as there is a lot of precedent for chronic illness following infections, old and familiar. Medicine dropped the ball hard here. It's not too late to start doing the work but to rely on invalid data will only fuel more failure moving forward. I'm not even a long hauler and this stuff is obvious. Please do better.
On 2020-07-12 14:50:03, user Sabbir Ferdoush wrote:
RNA-extraction free SARS-CoV-2 RT-qPCR .... Do you know which are the manufacturer.
On 2021-12-08 00:42:55, user Sam Smith wrote:
Summary:<br /> These data demonstrate that both heterologous Ad26.COV2.S and homologous BNT162b2 increased antibody responses in individuals who were vaccinated at least 6 months previously with BNT162b2. <br /> Ad26.COV2.S and BNT162b2 led to Similar antibody titers by week 4 following the boost immunization but exhibited different immune kinetics5. <br /> Ad26.COV2.S led to greater increases in CD8+ T cell responses than BNT162b2!!<br /> However, the durability of these immune responses remain to be determined.<br /> These data suggest different immune phenotypes following heterologous (“mix-and-match”) compared with homologous boost strategies for COVID-19.
On 2020-07-22 17:00:56, user Robin Whittle wrote:
As Karl Pfleger suggested, I hope there will be more detailed information on 25OHD levels, symptoms at admission and as treatment progresses.
In light of a recent review (Charoenngam & Holick for a recent review https://doi.org/10.3390/nu1... "https://doi.org/10.3390/nu12072097)") which states that 40 to 60ng/ml 25OHD is required for proper immune system function, the 25OHD thresholds and D3 doses seem inadequate. This article also recommends an initial 12.5mg D3 (50,000IU) for all COVID-19 patients.
According to the present article, patients with 30ng/ml or more are given no D3 at all. Daily doses for those with lower levels are only 0.02mg (800IU) per day, which is a 20% or less of what most people would require to maintain 40ng/ml - assuming the supplement was taken with a fatty meal and well absorbed. https://journals.plos.org/p... indicates that average weight people need about 0.125mg (5000IU) a day to reach the middle of the 40 to 60ng/ml target range.
Surely all these low 25OHD levels (and the researchers report 21.6% of patients with initial levels below 6ng/ml and some below the 3.2ng/ml detection limit) warrant urgent action. What objection would there be to bringing all patients up to at least 40ng/ml with oral or IV 25OHD cholecalciferol (Rayaldee)? This would go into circulation immediately without relying on potentially hepatic conversion of D3 to 25OHD, which takes days or a week or so - even if the liver is functioning properly.<br /> The present article cites, as prior observations of low vitamin D levels correlating with COVID-19 symptom severity, an Indonesian article (26), an Indian article (27) and one from the Philippines (28). The first two have been withdrawn. Please see my page https://researchveracity.in... for the reasons which lead me believe that none of these three articles report actual research.
I think that the present article and a recent one An autocrine Vitamin D-driven Th1 shutdown program can be exploited for COVID-19 Reuben McGregor et al. 2020-07-19 https://www.biorxiv.org/con... are important steps in elucidating the role of vitamin D deficiency in COVID-19 severe symptoms. I have cites both articles at my page on vitamin D and COVID-19: http://aminotheory.com/cv19/ .
More research is urgently needed, but since vitamin D is a safe, inexpensive, nutrient which most people are deficient in (by the 40+ ng/ml standards we now know are important for immune system health) robust supplementation programs for all in need (most humans) need not await further research or clinical trials.
On 2021-12-20 07:43:09, user A. Mesut Erzurumluoglu wrote:
Now published at: https://www.sciencedirect.c...
On 2020-05-24 02:16:20, user Ken wrote:
Given the overlap between the 95% confidence intervals for Intubated and Non Intubated it would be worthwhile to have a p value to see if there actually was a difference.
On 2020-03-20 11:57:18, user Romain G. wrote:
No data about hypertension and diabetes mellitus in these patients, which increase risk for COVID-19 infection and severity. Should be interesting to cross the informations. Here, it is pure speculations. Has to be reviewed, but many other parameters have to be included.
On 2020-07-13 14:47:31, user Donald R. Forsdyke wrote:
Antibody responses are an example of humoral immunity and the authors correctly point out that there is also cellular immunity, mediated by T cells, which they have not studied. They do not clarify the distinction between primary and secondary immune responses, be they humoral or cellular. This has led to media headlines such as "Immunity to covid-19 could disappear in months, a new study suggests" (MIT Technical Review, July 13th). It would be important in the final manuscript the point out that primary responses usually prime. They prime the patient for a greatly expanded secondary response to even low subsequent exposures to the virus. In this context, it would be interesting to compare the response to new vaccines of naïve subjects and those who have recovered from a primary infection.
On 2020-03-19 09:12:47, user ReviewNinja wrote:
ddPCR is a great technique, and can be of value and is less dependent of PCR-effciencies.<br /> However, if you have a qPCR slope -6.3 or -6.5, that means that there is a problem with your qPCR efficiency (<50%!!!).... So, a better primer set, optimized assay conditions, ... are necessary here. <br /> Furthermore, a one-step qPCR is compared with a two-step ddPCR. RT is a very variable factor. So if you want to compare qPCR with ddPCR, almost all factors need to be kept constant (and definitely RT), which is not the case here.
On 2020-05-18 18:01:55, user 18wheel wrote:
I believe you're onto something here: nothing to do with infection but the response. The targeting (elderly, populations with low vitamin D uptake for various reasons) will be borne out over the seasonal change (a comparison between north of 35 and south of 35 cities in August/September cross-referenced with local fortification and diet would be most interesting)
On 2023-07-24 18:51:05, user CliffHan wrote:
Please direct your questions related to AllerPops products to info@allerpops.com. Thank you. Cliff
On 2020-07-05 11:49:14, user OxImmuno Literature Initiative wrote:
On 2021-11-04 18:32:24, user Libres Penseurs wrote:
By looking roughly at the numbers, the authors seemed to be right. Ottawa area population is around 1 million. If Ottawa is aligned with the rest of Canada, 78% of the population received at least 1 dose since the beginning of the vaccination campaign. On the two months stated in the study, the increase was about 10% (overall Canada data). This means that around 100 000 people were vaccinated in the Ottawa area during those two months. Ottawa have a lot of hospitals so you cannot assume that everybody with adverse reaction to the vaccine will show up at the same hospital. The authors use 1/3 of that total number (32k). The 800000 number refers only to people having received at least one dose since the beginning of the vaccination campaign. <br /> Myopericarditis cases at one hospital for a period of two month cannot be used as a numerator on this number to calculate risk.
On 2020-10-05 15:02:11, user Kamran Kadkhoda wrote:
One out of 7 IgG-positive cases had positive RNA result; unless confirmed by PRNT, the remaining 6 can very well be false positive.
On 2020-07-03 11:10:45, user Stuart Shaw wrote:
A CRITICAL LOOK AT A PREPRINT INFERRING THE COVID-19 INFECTION FATALITY RATE
On 2022-05-18 18:22:54, user Yosuke Tanigawa wrote:
Hi Chelsea,
Congrats on the impressive work and the talk at #BoG22. I am curious if your results would also help resolve the pathogenicity of rare SNVs or rare short indels. For example, is it possible to say rare (smaller) variants disrupting the boundaries of TADs identified from your genome-wide scan (Fig. 4) would likely be pathogenic? Suppose many pathogenic variants are enriched at such TAD boundaries at a well-characterized locus (perhaps MEF2C locus). In that case, it may be possible to gain insights into the pathogenicity of VUSs at other TADs. Thanks!
Best,<br /> Yosuke
On 2021-10-02 14:59:26, user Alberto wrote:
Thanks for the detailed report. I'd only like to ask about the last sentence included in the abstract: "The beneficial and protective effects of the COVID-19 vaccines far <br /> outweigh the low potential risk of neurologic and psychiatric reactions. Going through the paper I haven't seen anything that attempts to estimate these rinks vs. benefits in any way (let alone a systematic way, by age, risk of severe disease in case of COVID-19, etc...). It seems like a statement that's been added there arbitrarily and does not belong to a scientific paper that not actually evaluating any risks associated with the disease itself or the vaccine efficacy to prevent them.
On 2020-03-25 11:59:06, user Ned wrote:
Can you share the sequence of the modified spike protein? The stabilized soluble protein with the his tag. I could not find it. Thanks
On 2021-09-14 11:42:39, user Alex wrote:
"possible transient biases"?? You may want to explain that in detail - because there is a clearly observable initial x3 time increase in the "cases" even after the first dose eg. https://americasfrontlinedo... & far more concerning then just RT-PCR "cases", there is also a no-less clear 2-3x initial peak in **severe covid +IVL hospitalizations** after the 3rd dose in August 2021 . The data for the later are available even from the Israeli gov public site & I suggest to use "all age groups" combined to avoid Simpson paradox. As the result, afics , there was no statistically significant difference in the average over the month & all age group severe case hospitalizations between unvaccinated & vaccinated with 3 doses (but there was a comparative average ~30-40% benefit in 2 dose vaccinations.) The above certainly does not match the information in your present paper & you may want to consider clarifying the reasons for the difference - if only for yourself - to be sure that you are doing research correctly. What I observe was an indication of the overloaded immune system with both excessive agent doses & unnecessary "boosterization"
Regards
On 2019-11-12 00:51:39, user Guyguy wrote:
EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT NOVEMBER 10, 2019
Monday, November 11, 2019<br /> Since the beginning of the epidemic, the cumulative number of cases is 3,287, of which 3,169 confirmed and 118 probable. In total, there were 2,193 deaths (2075 confirmed and 118 probable) and 1067 people cured.<br /> 411 suspected cases under investigation;<br /> No new cases confirmed;<br /> No new deaths of confirmed cases have been recorded;<br /> 3 people healed from the CTE in North Kivu in Mabalako;<br /> No health workers are among the newly confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths;
NEWS
Awareness and vaccination day for Beni mototaxi drivers with the support of Unicef S / Coordination MVE Beni, Wednesday 06-11 - 2019 HIVUM room
• There were many, about three hundred, the drivers of Mototaxi Beni invited to a day of awareness and vaccination against Ebola Virus Disease this Wednesday, November 06, 2019 in the HIVUM room.
• This day is welcome for the city of Beni during this period of EVD epidemic which, unfortunately, displays a lethality of 86.3% among motorcyclists, as pointed out by Dr. Pierre ADIKEY, Coordinator of the response of Sub Coordination of Beni.
• Thus, in his presentation, he focused his message on the risk of transmission of EVD among motorotaxi drivers and the conduct to be held in the exercise of their craft to protect themselves and the community.
• He asked bikers more often to respect the measures of prevention, namely: washing hands regularly, stopping at checkpoints, not being bribed to divert checkpoints, not carrying suspicious parcels and reporting and / or direct any suspicions of illness to colleagues or the community.
• In order to circumscribe the day, Dr. P. ADIKEY traced the path of the last Motard who died of EVD before his death confirmed at the CTE. To close his presentation, he made a reminder of the various events that prevented the teams of the response from working: among other things the days of the dead city, the fire of the vehicles of the riposte, the destruction of the structures of the care, the cases of resistance and others whose bikers were part of it.
• Dr. Bibiche MATADY, as Epidemiologist and Chair of the Monitoring Commission, introduced to the participants the importance of accepting to be listened to if you are in contact with a case, to let yourself be followed for the entire period indicated and to orient in a management structure as soon as the first sign appears. She also emphasized the collaboration between the bikers and the teams of the response.
• To justify this day again, one of the 3 Hikers shared his testimony and urged his colleagues to collaborate and follow the recommendations of the response teams starting with vaccination.
• Vaccination is one of the preventive measures against EVD, said Dr Adonis TERANYA, the Chair of the Immunization Subcommission. In his presentation, he explained the evolution of the vaccination protocol, the current targets, the side effects and the action to take in the event of an adverse event. Before calling for the voluntary vaccination of participants, he spoke about vaccines currently used in the DRC.
• In his words, the President of Bikers reiterated to the Coordinator the commitment of his organization and all its members to support the interventions of the response, while affirming its availability to any solicitation for the fight against the disease to Ebola virus in the city of Beni and its surroundings.
• The day ended with the vaccination of 100 Bikers and some of their dependents.
VACCINATION
MONITORING AT ENTRY POINTS
As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:
On 2021-12-11 04:21:08, user dorothee von laer wrote:
This may be very different if Omicron takes over.
On 2024-07-24 16:07:33, user Jim Woodgett wrote:
A sobering study! I have a couple of questions about the population evaluated and timing of the study. In Methods the "Pandemic" group (G1) included subjects with scans before and after pandemic onset (N =404; 247 female), further split into "Pandemic–COVID-19" (G3, N = 121; 75 female) and "Pandemic–No-COVID-19" (G4, N = 283; 172 female). So there were 121 who had (at least one?) Covid-19 infection and 283 who had no infection. This seems an unusual sampling ratio given known serological analysis and overall penetrance of infection. How long after infection were the MRIs performed and at what point were subjects classified as Covid infected or not (presumably, the majority became infected during the study)? Were there sufficient subjects and data to assess degree of brain aging vs multiplicity of infection? Is there data on subjects self-reporting long Covid effects?
On 2022-12-12 15:51:53, user Koen van de Wetering wrote:
Dear Wera,
It is only now that I find out about your comment. I appreciate your input. Our manuscript has now been peer reviewed and was recently published in Analytical and Bioanalytical Chemistry. In the future I will more often check our preprints and incorporate comments like yours into our manuscripts. In case you still have questions about the assay to detect pyrophosphate, do not hesitate to contact me directly via email.
With kind regards,<br /> Koen van de Wetering
On 2020-07-07 14:02:12, user David Curtis wrote:
I have some concerns about rs150892504.
According to ExAC it is rare in Europeans but has an allele frequency of 0.04 in Ashkenazi Jews. <br /> https://gnomad.broadinstitu...<br /> https://gnomad.broadinstitu...
Likewise, it has an allele frequency of 0.03 or 0.04 in the IBD exomes:<br /> https://ibd.broadinstitute....
This raises the possibility that the results you obtain may be due to some kind of population stratifcation which has not been adequately corrected for.
On 2021-07-02 16:40:01, user Andrew Carey wrote:
a healthful plant-based diet score<br /> I read the text and couldn't find any further information about what this meant. There is much discussion of hPDI on the internet, but no publicly available calculator for it, and now I learn that there are a number of ways of working out a score for this and your team of researchers has chosen one of them based on your choice of phrase.<br /> I'm being harsh but unless this diet scoring system chosen was declared in advance of or independently of collecting the data, then this does not deserve to pass peer review.<br /> Make it public please.
On 2023-11-27 22:00:33, user Christos Proukakis wrote:
We note the results of the analysis, and look forward to submitting a detailed response soon.
On 2022-02-23 18:22:41, user Kevin J. Black wrote:
Revision published at J R Soc Interface, https://royalsocietypublish...
On 2020-12-04 16:17:03, user sdharbinger wrote:
I have three reservations about aspects of this study.
Firstly, the study tried to emulate a Randomised Control Trial by isolating consideration and analysis of each component for their potential as a single magic bullet agent and it never recorded or analysed enough data on a far greater range of different agents when they are taken in combination as part of integrated protocols. For example the Eastern Virginia Medical School protocol advocates supplementing with a combination of Vitamin C, Vitamin D, Quercetin, Zinc, Melatonin and Vitamin B complexes. Many also advocate Selenium, Magnesium, Folic Acid, NAC or Elderberry Syrup to name but a few.
Any combination of these agents could possibly help to build immunity because they act in different ways in different parts of the immune system and collectively certain protocols might show highly significant improvements in outcomes. There is no reason why the ZOE.app could not have collected data on all popular supplements and then analysed the data looking to see how effective different combinations were. This ability in principle to have collected virtually unlimited data from millions of subjects is what potentially makes the ZOE.app far superior to any RCT with virtually real time results and reports. If the Zoe app had given users the chance to enter a full range of supplements instead of restricting to them to just 6, then it would have been possible to analyse the effects of these agents when used in different combinations. In trying to emulate the 'gold standard' design and functionality of RCTs the ZOE.app and the study it generated: ignored the huge advantages that the ZOE.app has over RCTS in principal and in potential practices.
Secondly the study restricted its analysis to a question of whether people taking various supplements would go on the have a positive PCR test. The general problem with this measure is that no-one supposed that any of these supplements would provide complete prophylaxis against Covid-19 and that people were taking vitamins in the hope that if they caught Covid-19 that they would experience less severe illness on account of a better immune system. The best metric in these terms would have been to assess the relative hospitalisation rates between those taking supplements or not and not simply reduced evaluation to just prophylaxis.
Thirdly, the study failed to record what dosages of supplements people were taking which potentially have a large effect on outcomes.
On 2022-06-14 12:08:52, user Robert Clark wrote:
In Fig. 3, it is notable that for the severe cases, the ivermectin group had a factor of 1.79 advantage on the scale of faster time to recovery. The question arises in this subgroup analysis of whether this is a real effect?
A good way to check is to also look at the hospitalizations, emergency room visits, urgent care, etc. numbers specifically for the severe cases. Note that its expected that a large proportion of these should come from the severe cases. Then does IVM have such a clear advantage for the severe cases here as well?
Robert Clark
On 2020-11-14 23:54:15, user Atomsk's Sanakan wrote:
The crippling flaws in this study have been pointed in many reputable sources, to the point that this paper cannot be considered an accurate estimate of seroprevalence and IFR population-wide in Santa Clara. The study over-estimates population-wide seroprevalence and under-estimates IFR.
For example, the study's recruitment method would favor those who volunteer for testing because they believe they're at higher risk of being infected (ex: they believe they were recently exposed to someone with symptoms). That's exacerbated by the fact that people need to travel to a site for testing, instead of doing self-testing at home or having researchers come to their home to test them, as done in other studies. The people more likely to put in the time and effort to travel to a testing site, are also more likely to have reason to think they were infected.
I recommend the following sources for those who want to learn about the scientific flaws in this type of study:
https://www.ncbi.nlm.nih.go...<br /> https://www.medrxiv.org/con...<br /> https://www.medrxiv.org/con...<br /> https://rapidreviewscovid19...<br /> https://bfi.uchicago.edu/wo...
And that's not even touching on some of the other problems with the study, such as the reportedly inaccurate information used to recruit some volunteers, alleged funding from an airline executive with a vested interest in making COVID-19 look less deadly so more people fly during the pandemic, etc. BuzzFeed has articles covering those points:
https://www.buzzfeednews.co...<br /> https://www.buzzfeednews.co...
In any event, there's a better designed seroprevalence study of Santa Clara underway:
http://med.stanford.edu/epi...<br /> https://www.ca-facts.org/
On 2021-12-01 22:33:29, user Volker wrote:
I estimate (from the text) that vaccinated individuals are involved in 5-6 out of 10 new infections. Which is more than half of all new infections. Seems not to be minor.<br /> Why is it not mentioned in the text ?!? Any reason, why this is not an important information, taken from the same graphics as the estimation about unvaccinated individuals ?!
The model used does not look like the real world in October and November. 2G, 3G, (no) testing have significantly different impact on the contact behaviour of vaccinated individuals, and even more on unvaccinated individuals. The contact model seems not to be realistic at all.
Is there any verification for the (contact) model with actual real data, instead of using static parameter for getting "some" results out of the model? How good (or bad) does the model match with the real world ? Do the results match anyway with increasing number of infected vaccinated individuals, and vaccinated individuals in hospitals ?
Looks like the model does not consider the absence of testing for vaccinated individuals, but this should have an impact on the number of known infections.
On 2024-08-13 07:20:46, user Christine Markwalter wrote:
The peer-reviewed version of this article can be found here: https://doi.org/10.1038/s41467-024-49080-9
On 2021-06-07 20:43:55, user nicolasflamand wrote:
The data from this preprint has been peer reviewed and is now available under the form of a research article in the FASEB Journal. Link : https://faseb.onlinelibrary...
On 2025-02-26 23:25:34, user Guido Mazzone wrote:
The sentence " This stop gain variant has not been previously reported and it is not present in <br /> gnomAD and 1000 genomes databases" is not correct anymore.<br /> ERMARD(NM_018341.3):c.1523G>A is actually present in gnomAD 4.1.0 with global AF=1/1613140 and South Asian AF=1/90712.<br /> This is interesting because the patient is South Asian.<br /> https://gnomad.broadinstitute.org/variant/6-169776457-G-A?dataset=gnomad_r4
On 2025-03-30 21:44:30, user Simon binakter48 wrote:
This paper has been published to an IEEE conference.
2023 26th International Conference on Computer and Information Technology (ICCIT), 13-15 December, Cox’s Bazar, Bangladesh
doi: 10.1109/ICCIT60459.2023.10441480
On 2020-05-27 03:20:48, user G M wrote:
Will be picked up during review no doubt but describing qPCR as an 'antigen' test is false, and personally distracting.
On 2021-12-03 21:49:24, user gwern wrote:
An incorrect result from the first version of this paper (about PhDs being the most reluctant to get vaccines, when really they are probably the least) is still being very widely shared on social media (I can see several instances on Twitter today alone). The error should be discussed explicitly, in more detail, not buried in a vague throwaway comment about some categories being 'higher'; not just so people reading it will understand it, but as an instructive lesson to other researchers about the perils of mischievous responders in surveys, particularly online ones.
On 2022-07-28 17:24:57, user Mike Knudson wrote:
This paper is now published online in Transfusion.<br /> https://onlinelibrary.wiley...<br /> Major change was to add the results of eluate studies in the patients with a positive DAT following a transfusion reaction.
On 2020-03-23 03:14:09, user Wen Minneng wrote:
Your conclusion is wrong. Both weather and public intervention could impact on the number of cases. How much does weather impact? How much does public intervention could impact?
On 2020-05-06 11:58:39, user Ran Israeli wrote:
Very interesting, good manuscript.
Is there a chance you expanded the data from Figure 1 (Especially 1A and 1D) to a more updated one?
On 2020-04-19 05:52:47, user AlanCarrOnline wrote:
So a single 14 day lockdown is not enough. How many went on to develop symptoms in the next 14 days?
On 2021-10-14 17:12:39, user lbaustin wrote:
Has this been submitted to any of the MEDLINE indexed journals who publish on this topic?
On 2020-05-24 09:26:14, user Count Iblis wrote:
The natural vitamin D levels are way higher than the average levels found in populations living in the civilized world. Biologically normal vitamin D levels are between 120 nmol/l and 250 nmol/l. Levels below 100 nmol/l are from a natural biological point of view extremely low, but such levels are the norm in the civilized World, even in the tropics as people there too spend most of the day indoors.
Studies like this that look into the correlation between vitamin D levels naturally found in society and harmful effects of COVID-19 effect are interesting, but they cannot detect all of the effects of the severe vitamin D deprivation of the western population. It's similar to a study into the effects of exercise on heart disease if you're studying a population of couch potatoes. You may detect a difference between those couch potatoes that don't sit all day long on the couch and those that hardly get up at all during the day. But the large effects on heart health that kick in when you run for more than half an hour a day, cannot be extracted from such a study.
On 2020-04-18 20:25:12, user Scott Howell wrote:
Conceptually this study and its conclusions are patently false. Internal endogenous hormone levels do not equate to exogenously administered androgens. Perhaps a read of Morgentaler's saturation model would enlighten the authors. A statement that long-term elevated free testosterone levels causes prostate cancer does not align to either the saturation model or the use of bipolar androgen therapy at supraphysiologic doses to treat prostate cancer. There is a big jump from Mendelian randomization to nuances in physiology and what occurs in practice. Just like secondary data analysis of insurance claims to establish risk should be banned or at least relegated to their limitations, these type of studies drawing conclusions outside of the scope of the data should be relegated to their limitations or even less.
On 2021-08-10 16:09:56, user Vilkus wrote:
On 2021-05-04 21:26:25, user aleax wrote:
1 case out of 225 is 0.44%, definitely NOT 0.0041%.
On 2020-05-18 21:51:22, user bigterguy wrote:
Um...<br /> ” We estimate that through the end of July, there will be 60,308 (34,063-140,381) deaths from COVID-19 in the USA ”<br /> 92,000 and counting on May 18. Likely close to the top of their projected range by end July. Is this even worth publishing?
On 2022-12-02 16:36:24, user Mark Czeisler wrote:
Note from the authors:
A revised version of this paper was published in Annals of Internal Medicine on 29 November 2022 following peer review. Below is a link to the article, along with the PubMed citation.
https://www.acpjournals.org...
Czeisler MÉ, Czeisler CA. Shifting Mortality Dynamics in the United States During the COVID-19 Pandemic as Measured by Years of Life Lost. Ann Intern Med. 2022 Nov 29. doi: 10.7326/M22-2226. Epub ahead of print. PMID: 36442062.
On 2020-04-05 22:00:09, user Kirsten McEwen wrote:
As the authors state, IL-6 could be a biomarker or a central pathogenetic element - in other words, cause vs correlation hasn't yet been determined.
On 2020-04-18 15:48:14, user Jingeol Lee wrote:
I hope this method extends to general application on forecasting the spread!
On 2020-04-25 18:13:47, user Pavel Valerjevich Voronov wrote:
What I do afraid - delays with vaccine because not taking that study in to account. Imagine, if they inject vaccine to mostly O- subjects, having promising results, move forward, then it "accidentally" won't work with others. Vaccines must be evaluated with A+ recipients at first, I suspect. Or at least blood type should be taken in consideration while results evaluation - A+ MUST be present. Even if this study is not finished - such testing approach shouldn't be harmful.
On 2020-04-07 09:11:10, user Pavel Valerjevich Voronov wrote:
Could anybody send me a link to a study that confirms widely supported claim that elderly people or ones with pre-existing health conditions more at risk? How come that it was widely accepted (is it also accepted by WHO?) without any links even to pre prints (maybe I missing this)? When in Iran 100 year old recover and those w/o pre-conditions in USA suddenly die? This study look like saying otherwise (at least it was so in v1). Please give me a link.
On 2022-12-15 10:31:26, user RBNZ wrote:
Please make your code available on GitHub, not just the readme. Thanks.
On 2020-04-27 03:28:31, user Sam Leumas wrote:
How was the data even collected? Veracity of this information?How can you tell if the contracted virus is from within house, transport area,outdoors,malls etc? Common sense tells stagnation of air is a probability but still,seems like there is a major flaw in the data collection process.
On 2021-10-26 03:31:17, user Y S wrote:
I don’t understand: do they follow people vaccinated in February for the month of March, April etc. and compared with unvaccinated. Or make correlations with Cox method including people vaccinated in each month. In the latter case for vaccinated in March, outcome for people in April somehow has to be translated to the month of March, as the first month after vaccination?
On 2024-12-13 13:28:40, user Mahalul Azam wrote:
This article now published at http://dx.doi.org/10.2174/0118749445361291241129094132
On 2021-01-10 22:17:22, user Wayne Griff wrote:
Single dose vaccine efficacy is not 90%. It's less than 50%, and that's after only 3 weeks. It would be even less effective at 6, 9, 12 weeks or more. More importantly, at 3 weeks the neutralizing ability of 1 dose is only 1/5th as much as Convalescent Plasma (NEJM)
On 2021-02-27 06:50:50, user Suriati Jamalludin wrote:
good exploration. i'm digging the source that online learning during emergency response are facing the problem mental health disruption among student. therefore the learning continuity is not easy when student in a bad condition of mental health. how do i use the reference as a support. may i have the reference format this article for citation?
On 2023-08-30 17:56:46, user Caroline Lima wrote:
This review resulted from the graduate-level course "How to Read and Evaluate Scientific Papers and Preprints" from the University of São Paulo, which aimed to provide students with the opportunity to review scientific articles, develop critical and constructive discussions on the endless frontiers of knowledge, and understand the peer review process.
In this pre-print, the authors discuss the growing demand for ultra-processed foods and their harmful effects on human health. The presence of different oxidized substances and the low nutritional value is associated with chronic cardiometabolic diseases such as cancer, diabetes, Parkinson's, and Alzheimer's. This makes ultra-processed foods a subject of great interest and widely studied. This observation reinforces how important it is to study possible causes for the development of the aforementioned diseases and how research should be conducted to identify and possibly prevent them. It is also important to emphasize that the specific description of what leads these foods to develop oxidized substances is necessary in order to make a correct judgment of the causes and not classify all foods that have undergone some processing as equally containing oxidative substances.
Comments and questions:<br /> The authors prove that oxidative dietary substances and phytosterols are found in ready-to-eat foods and fast foods including those of animal or vegetable origin if preservatives/dyes were used, when high temperatures during the preparation process were used, and in a manner related to forms of storage and distribution.<br /> The use of different biomarkers has been suggested for both ready-to-eat foods and fast foods. Why use brassicasterol biomarkers for ready-to-eat foods and biomarkers (7?-OH and 7?-OH) for fast foods? Is there any specific reason for using these biomarkers? Are there other biomarkers that could be used?<br /> The use of different biomarkers for each food category is reccomended: dairy products (brassicasterol), eggs and derivatives (stigmasterol and ?-sitosterol), meat and poultry (7?-OH), seafood and baby food (?-sitosterol) and others (campesterol). What can each biomarker reveal for each food?<br /> How can the assessment of exposure to oxidative substances be established and what criteria should be considered and disregarded in this assessment? Would these values/results be enough for possible preventions and diagnoses?<br /> For biomarkers, is there any factor that interferes with this measurement and evaluation?
On 2021-01-15 16:00:23, user Martin Reijns wrote:
Congratulations on this work. One comment though: I know it's difficult (if not impossible) to keep up with all the literature on SARS-CoV-2, but I just wanted to say that the statement "Currently, no test combines detection of widely used SARS-CoV-2 E- and N-gene targets and a sample control in a single, multiplexed reaction" is incorrect. Our paper on this has been on medRxiv since June:
https://www.medrxiv.org/con...
and was recently published in PLoS Biology
https://journals.plos.org/p...
All the best, Martin
On 2022-06-23 08:44:59, user Andrew Fischer Lees wrote:
This is interesting work. Your 4th limitation is the biggest issue from a clinical side (I say this as a clinician). 99% of the time I order a hemoglobin it is as part of a CBC. Sometimes I order the hemoglobin because I want the Hb, but sometimes I order it because I want the WBC, or the platelets, or all of these things. There is not a great reason to order just WBC if that is all I care about, because the same reagents are used in the lab to process the sample, so the extra tests are "free information", that is, the marginal cost is zero.<br /> Your stability model should really be executed at the level of the CBC bundle. Asking clinicians to not order a Hb when the marginal cost is zero doesn't really save any money for the system or lab draws for the patient. But If the whole CBC is predictably stable, in that situation it would make sense to surface that information to the clinician in the form of Clinical Decision Support.
On 2020-09-10 20:53:35, user maggieclarke wrote:
So what's the association with blood type? Why didn't you say what it was? A, B O ,AB, Rh??
On 2020-04-01 18:24:50, user Editor wrote:
Were there any sex differences in mortality, as was seen in China?
On 2021-07-08 22:19:15, user Michael Plank wrote:
This paper has now been published in the New Zealand Medical Journal and is available open access at:https://www.nzma.org.nz/jou...
On 2020-04-26 15:20:46, user Robert Clark wrote:
I was interested to read of your report on over 4,000 COVID-19 cases in New York. Collecting health histories for a large data set of patients of COVID-19 may provide a rapid means of determining which medicines could be effective in combating it:
Big data to fight COVID-19 and other diseases.<br /> https://medium.com/@rgregor...
The idea is to find if certain medications are *missing* from the patients prior health histories, suggesting those medications may be protective against the disease.
Robert Clark
On 2019-07-14 20:05:47, user Edward Tufte wrote:
Please please integrate excellent image with the text, so that adjacent text describes the image.<br /> Segregating text and image is for antique publishers only. Also your preprint will have more readers than any journal article, so do your best by those readers. If it is ever published, you can<br /> re-segregate text and image for the commercial publisher.
On errors in medical measurement, this good study: “Covariates are often measured with error, introducing bias and imprecision. Practices regarding covariate measurement error were assessed via a systematic review of general medicine and epidemiology literature. In original research published in 2016 in 12 high-impact journals,<br /> only 247 (44%) of the 565 original research publications reported measurement errors, <br /> only 18 publications (7% of 247) used methods to investigate or correct for measurement error.”
Excellent article by Timo B. Brakenhoff, Marian Mitroiu, Ruth H. Keogh, Karel G.M. Moons, Rolf Groenwold, Maarten van Smeden, “Measurement error is often neglected in medical literature,” Journal of Clinical Epidemiology, March 2018, 89-97, edited.
On 2020-12-15 23:58:58, user Samantha Braun wrote:
What was used as the placebo?
On 2022-12-29 21:25:40, user Tugba Onal-Suzek wrote:
This article is published at https://dergipark.org.tr/en... The title of this article changed with one additional author
On 2020-04-16 21:17:49, user Sinai Immunol Review Project wrote:
Key findings:
The authors wanted to better understand the dynamics of production SARS-CoV-2-specific IgM and IgG in COVID-19 pneumonia and the correlation of virus-specific antibody levels to disease outcome in a case-control study paired by age. The retrospective study included 116 hospitalized patients with COVID-19 pneumonia and with SAR-CoV-2 specific serum IgM and IgG detected. From the study cohort, 15 cases died. SARS-CoV-2 specific IgG levels increased over 8 weeks after onset of COVID-19 pneumonia, while SARS-CoV-2 specific IgM levels peaked at 4 weeks. SARS-CoV-2 specific IgM levels were higher in the deceased group, and correlated positively with the IgG levels and increased leucocyte count in this group, a indication of severe inflammation. IgM levels correlated negatively with clinical outcome and with albumin levels. The authors suggest that IgM levels could be assessed to predict clinical outcome.
Potential limitations:
There are limitations that should be taken into account. First, the sample: small size, patients from a single-center and already critically ill when they were admitted. Second, the authors compared serum IgM levels in deceased patients and mild-moderate patients and found that the levels were higher in deceased group, however even if the difference is statistically significant the number of patients in the two groups was very different. Moreover, receiving operating characteritics (ROC) curves were used to evaluate IgM and IgG as potential predictors for clinical outcome. Given the low number of cases, specially in the deceased group, it remains to be confirmed if IgM levels could be predictive of worst outcome in patients with COVID-19 pneumonia. The study did not explore the role of SARS-CoV-2-specific IgM and IgG in COVID-19 pneumonia.
Overall relevance for the field:
Some results of this study have been supported by subsequent studies that show that older age and patients who have comorbidities are more likely to develop a more severe clinical course with COVID-19, and severe SARS-CoV-2 may trigger an exaggerated immune response. The study seems to demonstrate that the increase of SARS-CoV-2-specific IgM could indicate poor outcome in patients with COVID-19 pneumonia, however given the very small sample size, the results are not yet conclusive.
Review by Meriem Belabed as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn school of medicine, Mount Sinai.
On 2020-03-13 18:45:34, user naturebroad wrote:
What about Formica, laminates, butcher block, stone (soapstone, granite, marble, etc.), quartzite, solid surface kitchen countertops (acrylic resin, polyester resin or a combination of the two that is combined with filler,etc.),
On 2021-02-01 21:30:19, user Igi Dano wrote:
As a Slovak citizen, I agree with most comments/notes presented here. I could as well add my own experience with "following testing procedure recommended by manufacturer..", where this testing procedure was conducted outside (of any premise, just an open tent) with temperature well below recommended range.
But that is not the point of my post here. The point is that Slovakia is currently (1.2.2021) ending the second round of another population-wide screening.<br /> I am desperately waiting for another study from the authors, confronting the newest results with original ones. <br /> Without that I would recommend potential readers of this study to use extreme carefulness with interpretations of it..
On 2020-05-05 17:25:01, user Hannah Sally wrote:
Are all patients included in the study, patients whom were admitted because of COVID-19 or does this cohort also include patients whom were admitted to hospital for other reasons but concurrently were diagnosed in hospital with COVID-19? I may have missed something, but not sure if this is clear in the methods. This could impact the overall hospital admission mortality statistic.
On 2021-01-22 19:01:20, user Alberto wrote:
I hardly see any recommendation about measures to remove pathogens from indoor air. Good to see someone recommending it. I hope people take note and use methods, especially in public places, work places, schools, etc... The other big missing part is that to prevent upper respiratory tract infections (both to get them and to spread them), washing your hands often is good, but washing your upper respiratory tract often is fundamental. And yet, few advises about it. Pity.
An article for anyone interested in measures for both of the above: https://clo2info.wordpress....
On 2024-01-16 13:30:11, user Jan Egger wrote:
The paper has been published in CMPB from Elsevier:<br /> https://www.sciencedirect.c...
On 2022-01-06 18:42:10, user sd wrote:
Anyone interested in validating the NPRP criteria in their clinical setting please do and post your results here. Also see the published version in Prim Care Diab
On 2021-04-01 04:10:21, user Michal P wrote:
This study has a number of significant flaws and in my opinion should not be used for any decision making.
First, the sample size is very small - only 282 tests with only 2 positive cases. The authors state as their conclusion the rate of 7 positive cases out of 1000 visitors, even though according to their own analysis the 95% confidence interval is 1-24. And even though the authors provide such a wide confidence interval, their estimate of the number of infected arrivals is far narrower: 17-30 in the November-December period. This range should be substantially wider to accommodate the uncertainty of the test estimate.
Second, the study is performing the tests when the visitors are departing, and as the authors admit, they cannot rule out that the visitors were infected on Maui. Even if one of the two infections occured on Maui, that would completely change the result.
Finally, the study still suffers from selection bias. It sampled visitors arriving on a single day, with most of the visitors from California and Washington, during a time of high infections in the US. Current infection rate in the US is about 4 times lower than at the time the study is performed. This alone suggests that the likelihood of a visitor being infected now is 4 times lower than at the time the study was performed.
For this study to be useful for policy making it should be substantially larger to provide higher statistical power. And the estimate of the number of infected visitors should be conditional both on the number of arriving visitors as well as the prevalence of the infection in the locations the visitors are arriving from .
On 2020-03-06 15:54:48, user Steven Ge wrote:
Please let us me know if you have any questions or suggestions. Twitter @StevenXGe
On 2020-03-22 16:58:48, user Peterson Biodiversity Lab wrote:
Unsolicited peer review …
Comments on “Spread of SARS-CoV-2 Coronavirus likely to be constrained by climate”<br /> Comments offered by A. Townsend Peterson, University of Kansas
I read the above-referenced manuscript preprint with interest. Araújo and Naimi are leaders in the field of distributional ecology, so I was (and am) interested in their perspective on the distributional ecology of SARS-CoV-2, and the COVID-19 disease that it causes. Obviously, the question is quite current, such that I’m interested in the topic and the ideas, but also in getting answers that will prove robust and predictive. For this reason, I take the rather odd step of offering a peer review, even though no one has asked for it…
My interest in this manuscript was piqued most of all by the statement in the Abstract that “the disease will likely marginally affect the tropics.” If true, this would be an interesting, and quite promising and optimistic result, as many are concerned about what will happen when SARS-CoV-2 begins to spread in Southeast Asia, Oceania, sub-Saharan Africa, Latin America, etc. So I will focus my comments on this result and the assumptions that revolve around it.
PRESENCE DATA<br /> The occurrence data in the analysis were derived from available COVID-19 case occurrence data. “Coronavirus cases by the 10/03/2020 with data compiled and made available to the John Hopkins University Mapping 2019-nCoV portal... Regions with fewer than 5 positive cases were not included in the models. Exclusion of such sites was based on the working assumption that sites with small numbers of positive cases are likely imported from infected regions, thus failing to provide evidence that the SARS-CoV-2 Coronavirus is being transmitted locally within its ecological niche.” And also, in the Discussion of the manuscript… “Firstly, there is little reason to suspect that out-of-China contaminations would have occurred only, or mainly, with trade partners in the northern hemisphere... China is a big world player, having key commercial partnerships with Africa and Latin America. Yet there is not indication that meaningful local infections have taken place in these areas despite the global reporting of Coronavirus cases generally attributed to travelers coming from infected regions.”
This seemingly logical methodological step has rather important implications. It is true that many of the “singleton” occurrences will represent imported cases that were the result of infection taking place in early foci of infections (e.g., central China, Italy) and being taken to those places by travelers. In that sense, this methodological step is reasonable and logical. However, one should consider some important sources of bias that are likely associated with elimination of regions with few records…
Connectivity is nonrandom. That is, consider Wuhan, in central China. Check out the airline network connectivity visualizations shown in http://rocs.hu-berlin.de/co.... Its primary connections are all to northern, mesic, and temperate regions, and not at all directly to tropical and arid regions. Indeed, even given that major desert regions lie not too far to the west of Wuhan, they are not densely populated, such that land-based connections are also mostly to the east, and not to desert or tropical regions.
Testing bias. The relative unavailability of testing for COVID-19 cases has been commented extensively, even in the United States. The lack of testing clearly has resulted in broad (but silent) spread of COVID-19 prior to recognition of the broader extent of case distributions, as has been documented in Washington State, a COVID-19 focus in the western United States. With developing-world public health infrastructures being challenged with other, perhaps more pressing and immediate questions (e.g., dengue, malaria), COVID-19-caused respiratory problems and a few deaths from some pneumonia syndrome of unknown cause can easily go unrecognized. As COVID-19 testing becomes easier and faster, and the possibility for point-of-contact testing becomes a reality, I strongly suspect that many more tropical/humid cities will emerge as additional sites of viral transfer and COVID-19 infection.
ABSENCE OR BACKGROUND DATA<br /> The authors appear not to have provided any information about the region over which they calibrated and evaluated their models (I will not go into problems with ROC AUC that are well-known, and do not need restating). This choice is well-known to make important differences in modeling outcomes [see Anderson, R. P., and A. Raza. 2010. The effect of the extent of the study region on GIS models of species geographic distributions and estimates of niche evolution: preliminary tests with montane rodents (genus Nephelomys) in Venezuela. Journal of Biogeography 37:1378-1393.]. Indeed, the calibration region should be a combination of the area that has been accessible to the species over relevant time periods, and the area over which sampling was conducted (Barve, N., V. Barve, A. Jimenez-Valverde, A. Lira-Noriega, S. P. Maher, A. T. Peterson, J. Soberón, and F. Villalobos. 2011. The crucial role of the accessible area in ecological niche modeling and species distribution modeling. Ecological Modelling 222:1810-1819.).
Not only should the calibration area and the assumptions that led to that set of choices be made explicit, but they should be made in consideration of real-world features of the system at hand. That is, if the authors indeed calibrated their models at global extents, then that is a tacit assumption that the virus had had access to the entire Earth’s surface, but only “liked” (in a niche sense) the places where >5 cases have been manifested. At least in the early stages of this epidemic, this assumption clearly is not robust, and will bias the model results against the suitability of humid tropical areas. A better approach might be to take primary and perhaps secondary linkages of air and land transportation, and to use them to create an accessible area hypothesis that responds better to the actual phenomenon at hand. Such a more conservative estimate of an accessible area might well reveal that hot and humid sites were not available to SARS-CoV-2 given realistic hypotheses of the dispersal potential of the virus, and the resulting conclusions about the distributional potential of the virus would likely be quite different.
CONCLUSIONS<br /> The authors interpreted the importance and significance of their results thus: “… it appears the virus favors cool and dry conditions being largely absent under extremely cold and very hot and wet conditions.” And… “Much of the tropics have low levels of climate suitability for spread of SARS-CoV-2 Coronavirus owing to their high temperatures and precipitation (used here as a surrogate for humidity), followed by polar climates, where conditions of extreme cold temperatures seem to be beyond the virus critical minimum tolerance values. In most of such low climate suitability areas, human populations will likely be spared from outbreaks arising from local transmissions...”
Very simply, methodological decisions were made in this analysis that will lead to different conclusions. Decisions such as eliminating sites with few records, or using a global calibration area, as well as the testing bias discussed above, all align in leading to overfit models that will snug overmuch to the areas and environmental regimes where cases have already occurred. I do not think that the conclusions about low tropical/humid suitability are likely to prove robust, and I do not know enough about the conclusions of seasonality (which I have not discussed or assessed above).
Town Peterson
On 2022-03-01 21:32:30, user Maurizio Rainisio wrote:
Computing NNT would have highlighted that to spare one hospitalization over the 4 months duration of the vaccination protection would require approximately 15,000 full treatments for the 5-11 kids and 7,000 for the 12-17. Adding an NNT column to table 1 would be of great help.
On 2020-05-11 08:25:11, user M.E.Valentijn wrote:
The assumption that a neutralizing antibody IgG titer of 160 is sufficient to produce immunity may be overly optimistic, as it's based on a case study of one recovered patient who had mild symptoms - and her titer was much higher on Day 20 after symptom onset, reaching 1,280.
On 2020-03-25 18:42:15, user Sinai Immunol Review Project wrote:
This study describes the occurrence of a cytokine release syndrome-like (CRSL) toxicity in ICU patients with COVID-19 pneumonia. The median time from first symptom to acute respiratory distress syndrome (ARDS) was 10 days. All patients had decreased CD3, CD4 and CD8 cells, and a significant increase of serum IL-6. Furthermore, 91% had decreased NK cells. The changes in IL-6 levels preceded those in CD4 and CD8 cell counts. All of these parameters correlated with the area of pulmonary inflammation in CT scan images. Mechanical ventilation increased the numbers of CD4 and CD8 cells, while decreasing the levels of IL-6, and improving the immunological parameters.
The number of patients included in this retrospective single center study is small (n=11), and the follow-up period very short (25 days). Eight of the eleven patients were described as having CRSL, and were treated by intubation (7) or ECMO (2). Nine patients were still in the intensive care unit at the time of publication of this article, so their disease outcome is unknown.
The authors define a cytokine release syndrome-like toxicity in patients with COVID-19 with clinical radiological and immunological criteria: 1) decrease of circulating CD4, CD8 and NK cells; 2) substantial increase of IL-6 in peripheral blood; 3) continuous fever; 4) organ and tissue damage. This event seems to occur very often in critically ill patients with COVID-19 pneumonia. Interestingly, the increase of IL-6 in the peripheral blood preceded other laboratory alterations, thus, IL-6 might be an early biomarker for the severity of COVID-19 pneumonia. The manuscript will require considerable editing for organization and clarity.
This review was undertaken as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn school of medicine, Mount Sinai
On 2021-01-10 12:16:07, user Hans Binder wrote:
The paper is published under<br /> https://www.mdpi.com/1999-4...
On 2020-04-01 21:21:41, user anand maurya wrote:
I think it would be good to associate this research with other available data, like difference between mobile user subscription, reduction in network traffic. This might atleast give some additional data point to understand what or where have those users disappeared.
On 2021-11-18 19:38:56, user Fredrik Nyberg wrote:
Thank you for the comment!<br /> We state clearly already in the abstract that this is "...before the start of vaccinations" and specifically in 2020, which is before global and Swedish vaccinations started (some countries started in December 2020, Sweden had a handful of vaccinations in the last days of December 2020). So these obviously cannot be vaccine effects. Still, we can make it even more obvious in an extended updated version which we are working on.<br /> To be crystal clear - these rates are to show how common these conditions are WITHOUT vaccinations, so that in a world of vaccination it will become a little easier to evaluate if such conditions increase after vaccination or just occur as expected.