On 2020-10-31 00:01:20, user Joe Feist wrote:
It is funny that the CDC has issued a statement that wearing masks to filter smoke particles around the california fires isn't recommended because the smoke particles are too small. Yet the particles are at least twice the size of the covid 19 virus particles. Can you offer any explanation?
Also what do you mean exactly when you say ultra-fine particles? What size ranges?
On 2021-07-14 11:45:44, user ak wrote:
"We don't develop long lasting immunity to the other 4 common covid viruses" how can I verify that statement?
On 2021-10-17 22:54:41, user Rob Reck wrote:
If appears that there is no differentiation given to to the amount of time that passed since a subject contracted CoVid19. Waning immunity is an issue that has been studied. Certainly more study would be a good thing. But there is enough current data to know that it does happen. People who have had CoVid19 do get re-infected.
Given the existence of even a small number of reinfections, the claim that a person who previously was infected with CoVid19 need not be vaccinated is not supported by this study.
On 2021-06-12 09:02:36, user Daksya Siddhi wrote:
One bit of information that I did not find is the data on the age of the Vitamin D measurements. Since these measurements can span from 2 weeks to 2 years prior to hospital admission, their predictive value for Vitamin D levels at time of infection can't be judged, or at very least, won't be consistent. Can this data be provided?
Additionally, it is mentioned that the most recent Vitamin D measurement is used. For those patients for whom multiple measurements are available, what is the trend - stable, increasing or decreasing? That could affect their imputed Vitamin D level at time of infection.
On 2021-06-20 12:22:57, user Hlodovic wrote:
Has anyone given consideration to the fact that Ivermectin is administered to animals for intestinal parasites (worms, mainly)? Could it be that the ivermectin used in this study killed some kind of parasite common to most humans, thereby relieving the natural defense system from that fight and allowing it to attack the virus full force. Being already exercised by the battle of the parasites, the defense system would be strong. Suddenly relieving it of that battle could be like when you go in your car, but it seems to require that you give it a lot of extra gas. You realize the parking brake is on and release it. So the car suddenly takes off, throwing you back in the seat.
On 2021-08-07 16:52:24, user varnuke wrote:
How does an anti-parasite medicine like Ivermectin have any effect on a virus? That's kind of like using an antibiotic to cure a virus. Must be some parasites involved somewhere somehow.
On 2021-10-30 13:29:02, user ??? wrote:
Currently under revision.
On 2020-07-06 22:03:04, user Charles White wrote:
Full data and release for peer review? RNA detection only or did you culture in human epithelial cells?
On 2020-06-18 07:29:29, user Hilda Bastian wrote:
Thank you for this interesting preprint. I could not figure out how these particular decedents came to be selected for this study (apologies if I overlooked the explanation). That's a critical piece of information, and it would be helpful if it were detailed in the next version.
On 2023-05-16 21:45:14, user Maria Log wrote:
This is really very strange and disappointing that you consider the use of private e-mail as an indicator of fake articles. Since my years as a PhD student I always use, and I use now and will use my personal email in all my articles. There are many reasons for that, but the most crucial one is that I (as well as any other researcher)can change my affiliation and then my institutional e-mail will be inactivated and ones who are interested in my publication will not be able to get an answer to their questions. So the use of an email linked to the organization is unfair and irresponsible. Here is a link to my google scholar profile: https://scholar.google.com/... - good luck with finding any fake articles!
On 2020-04-19 17:16:57, user Fhnuzoag wrote:
There is unfortunately little reason to think data is even partially correct.
On 2020-04-20 23:15:57, user Yaud Xatrixer wrote:
What is the maker of the testing kit? What was the specificity of it?
On 2020-04-18 11:58:31, user Mortal Wombat wrote:
Bear in mind that they actually found a 1.5% infection rate.
Their adjustment upward in the rates came from<br /> a) Weighting for demographics because Hispanics and Asians responded in much smaller numbers -- while the much lower rate of interest in those populations suggests something far from a random sample among them.
b) They think their estimate of the test's accuracy needs to be weighted against the manufacturer's.
It's no wonder it took them two weeks to publish results that took 15 minutes to come back. Had to figure out how to figure out how to get the numbers up to the level they expected beforehand. Their raw results, using the manufacturer's accuracy estimate, would've given about 1.3%. And that's _before_ accounting for any upward bias due to sample self-selection for people who wanted to get tested because they thought they'd had it already.
On 2020-04-19 05:23:12, user John Dixon wrote:
This may be stupid, but if the ad specificies what the test is for, then doesn't that render it immediately unrepresentative? If it says it's for Covid-19, then won't people be more likely to go who have had cold or flu symptoms recently and are worried they may have had it? And so the sample pool would tend to have more positives than a purely random selection of the population. Therefore the study would underestimate the fatality rate. Am I missing something? To get a random sample, wouldn't you have to leave out any specifics of what the test is for?
On 2020-04-20 20:43:45, user Kenneth Melendez wrote:
So what these people are saying is that if you did the study LAST year, that you would get .5% false positives, about 10K people if you tested all of Santa Clara. You should declare them to be asymptomatic cases, and say that there are 9.5 times the number of asymptomatic cases as confirmed cases in Santa Clara. Time to call the media.
And if you want to believe their results, then you surely want to believe the that the false positive rate (1-specificity) was accurately determined by 2 false positives out of 371 tests of old (assured non-infected) samples.
On 2020-04-18 03:41:57, user hargen wrote:
"Third, age is the one most common predictor of mortality. He did not <br /> weigh the results by age, and old people are underrepresented in the <br /> study."<br /> He wasn't measuring death rates. He was measuring infection rates.
His study may not be perfect but it sheds light on the current over counting of the mortality rate. We have tested those with symptoms and the sickest were the ones to get the first test. Talk about sampling error. Since other studies have shown over 50% of the infected people don't even know they have been infected that would tend to skew the sample to an even higher bias toward not testing people.
For example, you are one of the 50% that was infected but didn't show any symptoms. Facebook sends you a invite to get tested. Why would you leave your house, wait in line for an hour (up to 3 actually) to get tested for something you "know" you don't have. However, if you had symptoms you would be interested in getting tested. I see the bias going more to the researcher.
On 2020-04-28 23:48:54, user Sun Wu Kong wrote:
I can confirm that the paper did not mention IgM specificity for their test and also that both IgM OR IgG test strip visible results were deemed positive.
I cannot however find reference to the lower bound in the manufacturer supplied specificity, i.e. 366/371. Do you have a reference?
On 2020-04-19 00:37:25, user jemihami wrote:
I must say that there are many commenters using web data to formulate their arguments. Interesting, but of little logical use.
On 2020-04-20 02:13:11, user Joel Shore wrote:
Dean: Just as a sanity check on your claim, and since I am a simulation person, I just did a simulation in MATLAB where I asked the question "If the true underlying false positive rate were 1.5% then how many times would I get 2 or fewer false positives in a sample of 371?" Assuming I did this correctly, it looks like I get that this would happen about 8.2% of the time...So that means that the manufacturer's own data on false positives is compatible with the prevalence that they saw of 1.5% with a high enough probability that they could not possibly rule out their prevalence being due COMPLETELY to false positives with 95% confidence.
Or, in other words, it seems support your claim that the correct interval in the unadjusted case includes 0.00% prevalence (i.e., all of the reported "prevalence" being due to false positives).
On 2020-03-30 15:38:19, user Sinai Immunol Review Project wrote:
Main findings<br /> This is the first report to date of convalescent plasma therapy as a therapeutic against COVID-19 disease. This is a feasibility pilot study. The authors report the administration and clinical benefit of 200 mL of convalescent plasma (CP) (1:640 titer) derived from recently cured donors (CP selected among 40 donors based on high neutralizing titer and ABO compatibility) to 10 severe COVID-19 patients with confirmed viremia. The primary endpoint was the safety of CP transfusion. The secondary endpoint were clinical signs of improvement based on symptoms and laboratory parameters.
The authors reported use of methylene blue photochemistry to inactivate any potential residual virus in the plasma samples, without compromising neutralizing antibodies, and no virus was detected before transfusion.
The authors report the following:<br /> ? No adverse events were observed in all patients, except 1 patient who exhibited transient facial red spotting.<br /> ? All patients showed significant improvement in or complete disappearance of clinical symptoms, including fever, cough, shortness of breath, and chest pain after 3 days of CP therapy. <br /> ? Reduction of pulmonary lesions revealed by chest CT.<br /> ? Elevation of lymphocyte counts in patients with lymphocytopenia. <br /> ? Increase in SaO2 in all patients, indicative of recuperating lung function. <br /> ? Resolution of SARS-CoV-2 viremia in 7 patients and increase in neutralizing antibody titers in 5 patients. Persistence of neutralizing antibody levels in 4 patients.
Limitations<br /> It is important to note that most recipients had high neutralization titers of antibodies before plasma transfusion and even without transfusion it would be expected to see an increase in neutralizing antibodies over time. In addition to the small sample set number (n=10), there are additional limitations to this pilot study:<br /> 1. All patients received concurrent therapy, in addition to the CP transfusion. Therefore, it is unclear whether a combinatorial or synergistic effect between these standards of care and CP transfusion contributed to the clearance of viremia and improvement of symptoms in these COVID-19 patients. <br /> 2. The kinetics of viral clearance was not investigated, with respect to the administration of CP transfusion. So, the definitive impact of CP transfusion on immune dynamics and subsequent viral load is not well defined.<br /> 3. Comparison with a small historical control group is not ideal.
Relevance<br /> For the first time, a pilot study provides promising results involving the use of convalescent plasma from cured COVID-19 patients to treat others with more severe disease. The authors report that the administration of a single, high-dose of neutralizing antibodies is safe. In addition, there were encouraging results with regards to the reduction of viral load and improvement of clinical outcomes. It is, therefore, necessary to expand this type of study with more participants, in order to determine optimal dose and treatment kinetics. It is important to note that CP has been studied to treat H1N1 influenza, SARS-CoV-1, and MERS-CoV, although it has not been proven to be effective in treating these infections.
On 2025-09-29 15:17:43, user Bryan Wilent wrote:
I think this is great and as I read through it hit me how challenging this is to do. Kudos to the team.
On 2021-08-18 14:12:25, user Jessica Lyne wrote:
I am curious if Dymista alters the testing results.
On 2020-09-17 07:41:34, user Dhriti Gupta wrote:
What are the 3 phenotypes? The article has not defined the 3 types of clinical phenotypes anywhere.
On 2021-09-17 16:24:24, user Thom Davis wrote:
"Antibody neutralization titers against B.1.351 and P.1 variants measured by SARS-CoV-2 pseudovirus neutralization (PsVN) assays before the booster vaccinations, approximately 6 to 8 months after the primary series, were low or below the assay limit of quantification" is the key "real information" in this synopsis. All others are conjecture. If it isn't measurable, it isn't there.
On 2020-07-22 13:08:11, user Daniel Goldman wrote:
Why is it mathematically impossible? it's unlikely to be so, because of all the different factors that go into the test results, but mathematically impossible? If the virus has a very unique feature that results in unique antibodies, then specificity close to (and that rounds up to) 100% doesn't seem impossible at all.
Either way, the test apparently has high sensitivity and specificity so even if it's not perfect, the results seem to stand. Do you have a reason to believe that the test in question is not as valid as the citation claims?
On 2020-10-18 04:17:11, user C Jones wrote:
My family has used the self-administered oral swab at an LA City Covid testing site each time we've tested.<br /> My son (19 yrs) tested last Friday 10/09 & received Negative result.<br /> He was out late on Saturday & I had him retest on Monday 10/12, and he received a Positive result.<br /> He tested again yesterday 10/16 and received a Negative result.<br /> His father & I both tested on 10/09, 10/14, and 10/16 - all results Negative.<br /> Very confusing. How do we proceed?
On 2021-01-09 18:28:12, user Alex Backer wrote:
This study appears to have been used to Curative to justify their methodology, yet the false positive and false negative rates in the FDA report are incredibly high. Look at the numbers: https://www.linkedin.com/pu...
On 2022-01-03 14:25:00, user sad wrote:
The disrespect of these French researchers for international efforts of genomic surveillance is astounding. GISAID explicitly requests that all providers of sequences analyzed be credited, and a collaboration is encouraged. None of this happened here. <br /> And they dare name a variant based on a hospital acronym despite the Pango designation. Just mediocre and sad… Luckily other countries are more respectful.<br /> A proper analysis would have also estimated the emergence date with confidence intervals (not as done here) and the growth dynamics of the lineage.
On 2020-11-01 19:22:55, user kdrl nakle wrote:
Sample of 34?
On 2023-02-22 16:16:10, user Robert Clark wrote:
Major flaw in your analysis. <br /> You noted the report by Peterson et al included cardiac arrest cases where they survived:<br /> “This study identified 173 confirmed SCD cases (and 158 SCA cases with survival), so on average 43 SCDs per year.”
Since there has been a great increase in awareness of cardiac arrests and arrhythmia in athletes there have been a great increase in AED’s (automatic defibrillators) available and those trained in CPR.
Then many of those cases even in just the last couple of years survived who would have died previously. So you should have also counted the number of cases who had cardiac issues who also survived in the current, pandemic era.
Additionally Maron et al described other causes other than just cardiac arrest as the cause of the sudden deaths. Since the Goodsciencing report considers several kinds of serious life threatening illnesses arising in athletes you should also have done a separate count of those cases in the Goodsciencing report, again both of those who died and those who survived.
Robert Clark
On 2021-12-02 12:45:22, user drummy_b wrote:
The Study worked with a effectiveness of the vaccines against <br /> transmission between 70% and 40%. Do we have any evidence for these <br /> assumptions? Furthermore, the effectiveness against transmission and <br /> against disease is not clearly separated in the text. The study should <br /> also provide a modelling with 0% effectiveness against transmission, <br /> then we could see, what matches best with the numbers we have in the real<br /> world.
On 2021-10-19 16:11:02, user BGJ 1 wrote:
Follow the money for your answers. Also, that Kentucky study has been misrepresented badly. That study occurred in May, well before the delta variant hit Kentucky and in a population that was only about 25% vaccinated. It showed that of those that tested positive (about 24,000) about 990 of every 1,000 was not vaccinated or had Covid prior to vaccination. Of the other 10 out of 1,000, 3 had been vaccinated and 7 had Covid previously but were not vaccinated. 7 divided by 3 is 2.33 and from that some people concluded that you were twice as likely to get Covid if you had previously had Covid than you were if you were vaccinated. Very, very much taken out of context... but researchers can easily twist statistics to fit their agenda. Statistics don't lie, but people do.
On 2021-09-24 16:52:23, user Andy Bloch wrote:
It doesn't show that natural immunity is "better" than vaccines, even if there was absolutely no bias. It shows only that 2-dose vaccine-induced immunity waned (during this time period) more than natural immunity. Add a third dose a few months out and the vaccines catch up. A huge advantage of vaccines is the ability to control the dose, and spread it over time. Note that there was a significant increase in the rate of reinfections for people first infected prior to Nov 2020. If you look at Figure 1, and compare it to the rate of infection in Israel at the time, it suggests that people first infected prior to Nov 2020 had 3 times the chance of a reinfection in the study compared to those after. Click here to view some charts I made illustrating this.
On 2021-08-28 16:17:13, user Aaron Plummer wrote:
Doesn’t common sense already confirm this though. Natural immunity has already been proven to be the most effective in everything for hundreds and hundreds of years. The vaccine hasn’t even been around for a year yet. One is our natural survival instincts that have allowed humans to survive severe deadly and catastrophic events over hundreds of years, and one is man made in a lab based on hypothesis and trial and error experiments. Again common sense dictates that natural immunity will always win this debate. Too bad this administration doesn’t seem to recognize or acknowledge its effects.
On 2021-09-17 20:03:09, user USA Bottom Line wrote:
Would it be possible to include a fourth "No Immunity" group in this study? It would be extremely interesting to see how a group with no prior infection or vaccination would perform under the same conditions. The authors would be able to compute the efficacy of both vaccination and natural immunity during the study's time period. Perhaps they didn't do this because the population of "no immunity" people has become too small in Israel?
On 2021-09-15 08:46:22, user Gralin James Pritchard wrote:
"How did that go with Polio, by the way? And Tetanus? And Rubella? And Hepatitis?"
Thankfully, CoV-19 isn't even close to as severe, as hard to predict outcome-wise per individual infection, or as hard to treat as those diseases. You aren't comparing apples to oranges, you're comparing apples to automobiles.
On 2021-08-27 22:08:03, user evasmagacz wrote:
To look at the data from a different perspective:
In your first dataset:
Model 1: n = 16000 <br /> In patients who were previously infected: <br /> There were 5 symptomatic re-infections per 10000;<br /> Less than one hospitalisation per 10000, and no deaths.
In patients who were previously vaccinated, <br /> There were 124 symptomatic re-infections per 10000;<br /> 5 hospitalisations per 10000 and no deaths.
In your second dataset:<br /> Model 2: n = 46000<br /> In patients who were previously infected: <br /> There were 15 symptomatic reinfections per 10000; <br /> Less than one hospitalisation per 10000, and no deaths.
In patients who were previously vaccinated, <br /> There were 105 symptomatic reinfections per 10000 <br /> 5 hospitalisations per 10000 and no deaths.
In your third dataset:<br /> Model 3: 14000<br /> In patients who were previously infected: <br /> There were 16 symptomatic reinfections per 10000 <br /> Less than one hospitalisation per 10000, and no deaths.
In patients who were previously infected and then vaccinated, <br /> There were 11 symptomatic reinfections per 10000 <br /> No hospitalisations per 10000 and no deaths.
On 2020-05-16 20:45:51, user Celestyn LaChance wrote:
You are correct, the common theme of the underlying conditions is zinc deficiency. Zinc deficiency means low healthy red blood cell counts which means low blood oxygen levels. Covid-19 infected cells release exosomes that attack healthy red blood resulting in even lower blood oxygen levels, this is why patients can't breath and end up on ventilators. Zinc builds red blood cells and stabilizes blood so it doesn't clot. I would also suggest adding vitamin B12 to the protocol as it is also significant in building red blood cells and helps reduce anxiety. Anxiety/stress is believed to play a role in increasing the release of exosomes per this medical paper https://www.ncbi.nlm.nih.go...
On 2020-04-23 15:26:33, user Razvan Valentin Florian wrote:
According to https://jcm.asm.org/content... , the concentration of virus RNA in feces is about 4 x 10^3 RNA/ml undiluted, i.e. of the order of 10^6 RNA/l. Assuming a factor of dilution of 10^-2 of feces in wastewater, a factor of disintegration of less than 10^-1 of RNA on the way from toilet to collection point, and a factor of prevalence in the population of less than 10^-2, this leads to less than 10^1 RNA/l in wastewater at the collection point. The preprint mentions that "the quantification limit was 10^3 equivalent viral genomes per liter" and the graph indicates that they found 10^4-10^7 eq/L (probably equivalent RNA/l). This seems implausible according to the previous back-of-the-napkin computation. I would be happy if this estimate is invalidated, since if measuring concentration of virus RNA in wastewater would be possible, this would be a great tool for the management of the epidemic.
On 2020-06-07 14:24:04, user kenneth katz wrote:
ABO epitopes are post-translational modifications (diifferent patterns of glycosylation). The S protein is highly glycosylated around the region of receptor binding. Could it be the association of severity correlating with glycosylation variation be because the same glycosylation variation is applied to the S sites and affects S function?
On 2020-06-08 16:44:40, user Georg Mumelter wrote:
Thank you! Would it be possible and interesting to further analyze the risk difference by patient age and maybe gender - is the difference especially prevalent in younger or older age, male female? Should be a farily quick and easy analysis (cluster or regression) and plot.
On 2020-06-13 15:35:07, user Elena Sharova wrote:
Nice data set. Thanks for researchers. But what about co occurrence of A allele in ABO blood system and carriers of risk allele rs11385942? Allele frequencies differ by almost an order of magnitude, so what about A as disbalansed marker in rs11385942 carriers?
On 2020-06-09 16:50:01, user Arturo Tozzi cns wrote:
In this marvelous manuscript, the Authors state that SARS-Cov-2 did not undergo phenotypic modifications. <br /> It is not entirely true... there is an underrated viral component that did undergo phenotypic modifications. See this comment:
On 2021-09-16 10:25:45, user kdrl nakle wrote:
Yup, Alberto is right, the sample is really not much to speak of. I actually tend to believe conclusions but not based on this paper. Folks, you need to do a lot more work.
On 2021-06-10 09:22:10, user cat's eyes wrote:
What were the baseline characteristics of the 37 patients who survived on HCQ compared to the patients who died? From Table 1 patients who survived were generally healthier and younger than those who died. Table 4 should provide adjusted and unadjusted hazard ratios. Also, did you test for interactions between HCQ/AZM and predictors such as age and steroid use?
On 2021-06-04 13:42:50, user fauxnombre1 wrote:
Help me understand. The cumulative dose is not a product of the duration of treatment? Patients receiving treatment longer have a better survival rate?
On 2025-06-03 17:06:55, user Ruslan Salamatin wrote:
I would like to inform you that the preprint has now been published in a peer-reviewed journal.
Published in: Journal of Clinical Medicine<br /> DOI of the published version: 10.3390/jcm14113928<br /> Date of publication: 3 June 2025
Please update the preprint record accordingly.
On 2020-07-10 18:25:07, user Joanna Spencer-Segal wrote:
The authors speculate in the discussion that "It is also possible there is an effect via mineralocorticoid receptor binding in the context of SARS-CoV-2 induced dysregulation of the renin-angiotensin system." It is not clear what this means, but dexamethasone has minimal activity at the mineralocorticoid receptor, which distinguishes it from the other corticosteroids often used in critically ill patients (methylprednisolone, hydrocortisone). More clarification of what they mean regarding "mineralocorticoid effect" and rationale about why dexamethasone was chosen for this study would be welcome.
On 2021-02-03 22:16:44, user Eric Goodyer wrote:
Whilst I can see how the authors support their claim that the efficacy is good after 21 days, I cannot see any data to support their later claim that it would continue to be effective for a further 9 weeks. I am not saying they are wrong but I cannot see any data here to support that claim
On 2020-06-28 12:36:47, user OxImmuno Literature Initiative wrote:
On 2025-07-31 13:22:40, user David Freiholtz wrote:
This preprint is now expounded upon with spatial transcriptomics and flow-associated gene expression in rat aortas. It is published to ATVB and found at: <br /> https://doi.org/10.1161/ATVBAHA.125.323112
On 2020-09-01 22:49:40, user AlvaroFdez wrote:
I think this is a very in-depth, useful paper, and tool. Among other things, it proves the main shortcoming of the 6-foot social distancing rule regarding indoors given the chance of rapidly accumulating infectous quanta over time in this kind of environment.
It would very interesting to expand on the model described (well-mixed room ventilation, "ventilation outflow rate (Q), as distinct from air recirculation rate," as cited by the paper, as in many buildings there is (and will continue to be) a very strong influence of recirculation air vs outdoor air intake, and commonly used MERV or F filters in HVAC would not be enough to properly filter micrometer or less-sized aerosols, specially when generated continously). For many buildings, seems common a 80 (recirculated air)/20 (outdoor fresh air intake) ratio. There are some works considering this latter aspect (ie, FATIMA by NIST, https://doi.org/10.6028/NIS..., giving a calculation for recirculation airflow rate) that it would be nice to incorporate in this work.
On 2024-03-05 20:40:49, user Calum Polwart wrote:
An interesting approach to analysis, and good use of cross sector data.
I'd be interested to know if the authors considered use the the WHO ATC defined daily doses for calculation of their prescription numbers. Ideally they should provide an explanation to the 5d course length.
A couple of minor issues:
The version of R is incorrect - it should presumably be R4.3.1 not 4.31
The red line on the histograms are very difficult to read and perhaps the darkness of the histogram fill could be reduced?
On 2021-04-13 09:35:53, user Economy Decoded wrote:
There are also claims that there have been cases of vaccine wastage and shortage in production funds. Massive exports have also been cited as one of the reasons for vaccine scarcity. India has exported 64 million doses of vaccines to 85 countries in the form of “gifts,” commercial agreements signed between the vaccine makers and the recipient nations, and under the Covax scheme, led by the World Health Organisation (WHO). The experts have pointed out that vaccine shortages have become a problem in some parts of India due to supply bottlenecks. They claimed that vaccine makers had oversold their capacities while taking orders from all over the world. The steadily rising cases of COVID-19 and the issues related to “vaccine scarcity” are significant challenges to making India free from COVID-19. There is an urgent need to plan and prioritize providing vaccinations to achieve the target of inoculating 400 million vaccine doses by July, as stated by the Ministry of Health and Family Affairs. This piece has also taken a look at the current shortage of vaccines India is facing: We Analysed Whether The COVID-19 Vaccine Shortfall Is Due To Exports Or High Domestic Consumption https://edtimes.in/we-analy...
On 2021-08-31 14:22:02, user Shungo Y@JOJOLANDS(?)????????? wrote:
The standardized mean difference is the difference in proportions between groups divided by the standard deviation for a binary variable. <br /> https://handbook-5-1.cochrane.org/chapter_9/9_2_3_2_the_standardized_mean_difference.htm
The authors seem to use SMD simply as the difference in proportions. Therefore, we do not know if the two groups are well balanced.
On 2020-04-23 05:41:01, user FrezzaLab wrote:
Is it possible that some of these kids had already been infected, before the lock down, and passed it onto relatives?
On 2023-09-19 08:13:05, user Robert Eibl wrote:
To my understanding both bivalent vaccines seem to work very well. I wonder if the slight differences could be attributed to the different group composition - although very comparable (but one group had about 10% more diabetics and also more heart diseases in the group). The technology of the mRNA vaccines seems to be comparable, but if I remember correctly, Moderna uses 100 microgramm per dose, BioNTech only 30, right? Could this be an explanation for the supposed better outcome with the higher dose?
On 2020-05-01 15:18:00, user Philip Machanick wrote:
Seems prior comments have been removed? Your S Korea story does not mention extensive contact tracing, a key part of the strategy.
On 2020-04-23 17:36:19, user Thomas Vacek wrote:
Critiques:<br /> 1) The study admission criteria is susceptible to truncation because it requires discharge or death for study inclusion. Patients with long hospitalizations have been excluded.<br /> 2) The study should have controlled for the length of the treatment course.<br /> 3) The propensity score correction needs to be explained and documented. We need justification that the conditional probability estimates are reasonable. Given the small sample and the exigencies involved in this study, I would want a manual coding rubric for this. Moreover, it appears to me that the PSM scores only used the baseline covariates, which were based on the patients' condition at admission to the hospital, not immediately prior to being given HC or HC+AZ. This is an important consideration, as membership in a treatment group is not known at the time of admission.
On 2020-04-22 01:02:04, user Michael Kyba wrote:
A cursory browse through Table 2 of the paper shows that the patients that would eventually comprise the HC group were the sickest upon admission, the HC+AZ patients were intermediate and the patients that would elect no HC group were the least sick. This is prior to intervention.
This sort of sampling bias highlights the importance of double blind randomization to determine efficacy. Such an a priori correlation might be due to sicker patients opting for experimental treatments at a higher rate. In any case, it would not be wise to interpret these data as indicating that the interventions cause the worse outcomes. The underlying health state is probably responsible.
Some examples follow, then a criticism of what the authors have written into their Results and Discussion.
Known risk factors include age, weight and blood pressure; and signs of severe disease include kidney damage.
Browsing through table 2 looking for parameters with lowish p-values:<br /> Mean systolic blood pressure differences between groups showed a p-value of just under 0.05 (statistically significant), with values of 136, 132, and 129 across the groups (HC, HC+AZ, no HC), but more significantly, the HC group had 34% of patients with BP information showing up in the very highest pressure group (27.8/0.804, the denominator being the fraction with information on BP in that group), while HC+AZ had 30% and no HC had 25%.
Creatinine (high levels indicate impaired kidney function) was even more divergent: HC had 17.7% in the highest group, HC+AZ 11.7%, no HC only 8.1%.
Pulse Oximetry showed the largest number of patients with low blood O2 in the HC group.
I don't like that they did not break out the age and BMI into bins, but reported only means. Interesting distributions in these parameters might be buried in the mean.
The write-up of this data is quite unusual in being very abbreviated and lacking any thought to potential problems.
The Results section of the paper does not address the issue of a priori differences in health parameters at all except for saying "There were significant differences among the three groups in baseline demographic characteristics, selected vital signs, laboratory tests, prescription drug use, and comorbidities (Table 2)". Having said this, the authors proceed as if there were no significant differences.
In the Discussion section, the only comment to this issue is to state: "Despite propensity score adjustment for a large number of relevant confounders, we cannot rule out the possibility of selection bias or residual confounding."
It is in a preprint archive, which means this is a pre-review manuscript, but even so, it is quite unusual for such a study to completely lack any address of specific and obvious limitations. After review, hopefully reviewers will require the authors to analyze and discuss the divergent a priori health of the 3 groups.
On 2020-04-23 16:10:24, user quillerm wrote:
Why are all the survey participants over 65 and such a large percentage diabetics?
On 2025-07-24 13:40:04, user Rima Obeid wrote:
Trujillo-Gonzalez et al. did a great work to define candidate biomarkers of choline intake.
On 2021-12-01 22:19:03, user Kevin J. Black, M.D. wrote:
You'll want to cite and discuss this article:<br /> Snowden JS, Craufurd D, Griffiths HL, Neary D. Awareness of involuntary movements in Huntington disease. Archives of Neurology. 1998;55(6):801-805.
On 2022-12-08 20:41:52, user Marijana Vujkovic wrote:
this paper has been published
On 2020-07-23 15:48:06, user Joseph Psotka wrote:
a couple of factors you did not take into account: 1. Florida's population is much smaller than the official one because about a third of all "residents" leave in April and May, when it gets seriously hot. 2.) Maryland and Virginia suffer from contagion from New York which increased their Re in the peak months, so your model probably underestimated as New York declined.
On 2020-07-23 13:47:00, user Gill Prager wrote:
At what Baseline outside air temperature does the 15% change in mortality occur? For how long does that temperature need to remain constant pluS/minus each degree for each subsequent rise/fall in mortality?
On 2020-04-26 15:17:51, user peopletrees wrote:
Can you post the r script that you wrote in order to process and analyze this data? I'm particularly interested in the rstanarm model specification.
On 2021-07-06 06:18:28, user Pavel Nesmiyanov wrote:
This is a one of the first articles providing direct link between quantitative IgG assay results and risk of disease. However, given the limited applicability (only one vaccine studied, wide confidence intervals, limited time frames, limited vaccine effectiveness) the results should be interpreted with a high degree of caution to avoid excessive antibody test prescription. Results of these test could provide a false sense of security in some patients or, vice versa, a false sense of low vaccine effectiveness.
On 2020-04-08 17:16:11, user buongustaio1964 wrote:
This study appears to fail control for scores of additional obvious, potential confounds. These include but are not limited to population density, dwelling density, household sizes, educational level, employment profiles...I could go on. The conclusion could reasonably be a call for more research. But that the "study results underscore the importance of continuing to enforce existing air pollution regulations to protect human health both during and after the COVID-19 crisis" is neither convincing nor warranted.
On 2022-01-06 17:05:32, user SE Justus wrote:
Where/how do those who have recovered from the disease (naturally immune) fit into this study?<br /> Thank you.
On 2022-01-06 22:05:45, user Faithkills wrote:
Failure to include those with acquired immunity from recovery makes this of little use and exposes a likely bias of the researchers.
On 2023-08-13 18:29:56, user Zrinka Starcevic wrote:
The authors present a well-designed study with few weaknesses that should be adressed before publishing or discussed in the manuscript. The strength of this study is inclusion of patients from a younger age group, as opposed to studies that have been published about the subject so far. The English in the manuscript is written in a professional manner and is in need of minor changes. A more detalied introduction would be something I would suggest as well as more information on the choice of inclusion criteria. Furthermore, limitations in the study are in need of further investigation and elaboration. Lastly, I commend the authors on this study and encourage further work on the subject.
On 2021-03-19 14:42:27, user NermeenHM wrote:
I am so impressed with the extent of effort exerted on this paper and how it was deployed on such a large number of participants in the Arab world! Frankly, I never expected anything to come out of our part of the world with this high level of proficiency and accuracy + all this amount of participation. That’s quite a big number to be disregarded or dismissed particularly when, being a part of the Arab world myself, I know that it reflects a great deal of what we see around us and hear from friends, neighbors, colleagues and relatives. These results explain so much about how people think in this part of the world, also a lot more about the “why?” and the “who?” which were missing from the blurred and (usually) foggy picture when it comes to accurate figures and surveys. We’ re always “undocumented” in so many ways even with a pandemic looming high above our heads! Indeed, the issue of Covid vaccination is not something to be trifled with or treated lightly! I would highly recommend two things:
First: I quote the conclusion, “With the highly dynamic nature of the pandemic and vaccine production process and the interplay of ever-changing factors that affect vaccine acceptance, our study needs to be replicated at a later time to measure the change in public acceptance.” Yes please, that would be something really beneficial + informative.
Second: Due to the great importance of the topic and the rapid impinging of Covid on the<br /> world map and our societies, you should accept this paper to help others make use of its findings.
On 2022-07-14 07:16:04, user Marek Widera wrote:
This work has been published in J Infect Dis. 2021 Oct 13;224(7):1109-1114.
On 2021-10-27 22:37:44, user yury g wrote:
(1) Would you consider showing separately the hazard ratios in the Appendix by time-between vaccination and infection - e.g. for (a) less than three months post vaccine, and for (b) greater than three months post vaccine? This might contain a useful signal for the public health discussion around risks of waning immunity against infection in general population....... (2) Would you consider showing separately the hazard ratios in the Appendix for (a) infections taking place before the delta variant took hold, and (b) infections taking place after the delta variant took hold? Many thanks
On 2020-04-07 13:48:42, user Erin Beaver, MS, LCGC wrote:
I am a genetic counselor. I have been following the ABO COVID19 outcome correlation. I know many are discounting the data because they can’t fathom how ABO is associated with susceptibility to a respiratory pathogen. As a genetic counselor, I started thinking in a genetic linkage type of way and looked to see what was located near ABO blood group genes on chromosome 9. It turns out there is a gene, GBGT1 that sits next to ABO blood group and so this is a relatively conserved haplotype for polymorphisms in those genes. GBGT1 encodes a glycolipid called Forssman glycolic is which is thought in humans to be a major attachment site for pathogen binding to cells. This gene is highly active in lung tissues. I find all of this interesting a something worth investigating, but as a clinical genetic counselor with no access to a research lab, I don’t have the means to investigate my theory that perhaps GBGT1 aka FS glycolipid plays a role in infection from COVID19. Thoughts? Anyone that can look at this relationship?
On 2020-09-01 21:00:35, user Brian Gardner wrote:
What is catching my eye here is the second morphological alteration: spherocytes.
Assuming that controls were in place for spherocytosis, this seems to indicate (along with other findings showing decreased hemoglobin), that there may be an elevated risk for severity for those with spherocytosis.
On 2025-07-29 02:44:01, user Qiwen Yang wrote:
The article has been published at: https://doi.org/10.1093/ehjqcco/qcaf064
On 2023-02-10 20:50:43, user Onuralp wrote:
This preprint shows a very useful application of NLP for annotating clinical trial outcomes and makes the derived labels publicly available on their platform. We have previously used these annotations to assess the relative importance of human genetics evidence, and would appreciate if authors can cite our work where relevant.
On 2020-08-12 06:45:37, user Mohammad Khaja Mafij Uddin wrote:
This is really a great job!!!<br /> I have just started a project in which we will find the use of saliva sample as alternative to nasal swab from the suspected COVID-19. we are collecting saliva directly in to sterile container by stimulating with flocked swab. We are keeping the swab under the tongue for approx 2 min and then collect the saliva. So far we found 90% similary among the positive cases with nasal swab. Could you please let me know how long time is better for saliva collection (2 or 3 or 5 min?)<br /> Thanks <br /> Dr. Md K M Uddin
On 2020-07-08 11:38:25, user peter kilmarx wrote:
Congrats on your bibliometric analysis. Here's a reference for you: Grubbs JC, Glass RI, Kilmarx PH. Coauthor Country Affiliations in International Collaborative Research Funded by the US National Institutes of Health, 2009 to 2017. JAMA Netw Open. 2019 Nov 1;2(11):e1915989. doi: 10.1001/jamanetworkopen.2019.15989.
We found that publications coauthored by US-affiliated and non-US-affiliated investigators had a higher mean citation index (1.99) than those whose authors were only US affiliated (1.54) or non-US affiliated (1.35).
On 2020-11-22 01:11:32, user Mahan Ghafari wrote:
Your phylogenetic analysis is flawed: you cannot estimate a unique TMRCA for two independent introductions like this. Your constructed phylogenetic tree (fig.4) is blatantly incorrect (what's going on with the branches on the red clade B1??). I suggest you retract the preprint immediately and correct the fatal flaws in your analysis. Also, you are not the first group to study the phylogenetics of Iran and you should appropriately acknowledge earlier contributions.
On 2021-06-02 17:51:00, user Jørgen K. Kanters wrote:
The paper has now been accepted and published in Scientific Reports 11(1) 1-11 (2021)
On 2020-10-17 19:49:43, user Clayton Bigsby wrote:
The study is 100% inconclusive and warrants further investigation. The clinical trial that it references to: http://www.isrctn.com/ISRCT... second paragraph, line 1, first sentence on "Who can participate?" It says: "Adults (aged over 18 years) hospitalized with definite COVID-19 and not already receiving any of the study drugs." However, it fails to report any additional demographic information about said "adults" and raises more questions about how these results were achieved.
The other clinical trial: https://clinicaltrials.gov/... and the sponsor of that trail was in located at the Institut National de la Santé Et de la Recherche Médicale, France and it too fails to mention the demographic data of the participants. However the Institute for Demographic Studies, abbr. Ined in France has published their results:
https://www.rfi.fr/en/franc...
"For example, of the 3,523 deaths due to Covid-19 recorded in France on Tuesday evening, “84 percent of deaths are people over 70,” Robine says, adding 19 percent are over 90.
Although younger people come down with serious enough cases to be admitted to ICUs, data show they are far likelier to make a recovery. Less than 2 percent of deaths in France have been patients under age 50."
Mixing the deaths from +80 year olds with pre-existing conditions, with -30 year olds just to claim that a potential treatment doesn't work is pretty messed up and deceptive.
On 2020-03-25 15:27:05, user Sinai Immunol Review Project wrote:
While RT-PCR is being used currently to routinely diagnose infection with SARS-CoV-2, there are significant limitations to the use of a nucleic acid test that lead to a high false-negative rate. This article describes ELISAs that can measure IgM and IgG antibodies against the N protein of SARS-CoV-2 to test samples from 238 patients (153 positive by RT-PCR and 85 negative by RT-PCR) at different times after symptom onset. The positivity rate of the IgM and/or IgG ELISAs was greater than that of the RT-PCR (81.5% compared to 64.3%) with similar positive rates in the confirmed and suspected cases (83% and 78.8%, respectively), suggesting that many of the suspected but RT-PCR-negative cases were also infected. The authors also found that the ELISAs have higher positive rates later after symptom onset while RT-PCR is more effective as a diagnostic test early during the infection.
The authors make a strong case for using a combination of ELISA and RT-PCR for diagnosis of infection with SARS-CoV-2, especially considering the dynamics of positivity rates of RT-PCR and ELISA. Fewer false-negative diagnoses would improve infection control and patient management.
On 2020-04-02 20:13:43, user Sinai Immunol Review Project wrote:
Main findings: The authors analyzed 4000 test results from 28 COVID-19 patients of which 8 were confirmed severe COVID-19 cases and 20 were confirmed cases of mild COVID-19 infection. They found that the overall level of serum CRP increased in all cases irrespective of the disease severity. They observed that serum cystatin C (CysC), creatinine (CREA), and urea, biochemical markers of renal function, were significantly elevated in severe COVID-19 patients compared to mild patients.
Critical Analyses: <br /> 1. Figure duplication in panels G and H of Figure 2 <br /> 2. Survey area is limited to one center.<br /> 3. Small number of participants in the survey.<br /> 4. Elderly people in severe groups and relatively younger people in the milder group. The baseline parameters may differ in both groups, considering the age difference.<br /> 5. Although not clearly stated, this is a cross sectional study and interpretation of results is difficult. The markers that were found to be significantly different between groups are very non-specific. Renal failure and high LDH are not surprising findings in critically ill patients. <br /> 6. There is a very minimal description of the patient's baseline characteristics. It would be important to know for example what were the symptoms at presentation, how long patients had symptoms for before inclusion in the study, duration of hospitalization before inclusion. This would help interpret whether results reflect difference in severity of disease or simply a longer course of disease/hospitalization. <br /> 7. It is unclear what the authors mean in the discussion when they mention “which may be the result of prophylactic use of drug by doctor” (Discussion section, line 6). Type of the drug used is not specified.
Relevance: This study offers insights on some laboratory markers of mild vs severe cases of COVID-19 infection. Glomerular cells highly express ACE2 which is the cellular receptor for SARS-CoV-2, and impaired kidney function might represent a marker of virus-induced end organ damage.
Reviewed by Divya Jha/Francesca Cossarini as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn school of medicine, Mount Sinai.
On 2021-08-25 06:23:02, user L Wong wrote:
This pre-print was submitted to the peer reviewed "Japanese Journal of Radiology" and was accepted on 6th of Jan, 2021. The content had been revised according to the reviewers suggestion and comment and the title of the article was revised as "Convolutional neural network in nasopharyngeal carcinoma: How good is automatic delineation for primary tumor on a non-contrast-enhanced fat-suppressed T2-weighted MRI?”. Readers can find the latest version of the article in the link:
.
On 2025-04-29 13:39:34, user Guignabert wrote:
Dear Dr. Sajid Shahul and colleagues, <br /> Reference 3 is incorrect and should be replaced with the following: Guignabert C, Savale L, Boucly A, Thuillet R, Tu L, Ottaviani M, Rhodes CJ, De Groote P, Prévot G, Bergot E, Bourdin A, Howard LS, Fadel E, Beurnier A, Roche A, Jevnikar M, Jaïs X, Montani D, Wilkins MR, Sitbon O, Humbert M. Serum and Pulmonary Expression Profiles of the Activin Signaling System in Pulmonary Arterial Hypertension. Circulation. 2023 Jun 13;147(24):1809-1822. doi:10.1161/CIRCULATIONAHA.122.061501. Epub 2023 Apr 25. PMID: 37096577. <br /> Thank you.
On 2021-12-25 08:38:40, user Eslam Maher wrote:
The authors investigate whether Machine Learning (ML) algorithms fare better compared to traditional Cox models in big data. They selected Glioblastoma and gliosarcoma from SEER as the basis of their data set. There are two main points that are worth considering here, (1) statistical, and (2) clinical.
(1) a- Glioblastomas are relatively rare diseases, therefore, readers need to bare in mind that the hypothesis studied here may not be relevant to their work that is usually mono-institutional or multi-institutional. Unlike the huge SEER database, we never actually have such numbers at hand to analyze in survival models.
There is no doubt that Cox would outperform ML models in smaller samples. ML is gaining popularity in the medical community that is hugely inflated and unnecessary.
b- Unlike ML approaches, the performance of Cox models is heavily dependent on its assumptions. This includes the proportionality of hazards between levels of a given variable, which the authors do not seem to have investigated this assumption before running the model.
Another assumption is how the model was selected in the first place. The authors say they have run Cox univariably to decide upon the variables that would be used in the final mode. It is unclear whether a "significant" variable is considered as such at 5% alpha. Regardless of the alpha level, automated stepwise methods are notorious, this is because they are very popular among physicians and not professional statisticians and epidemiologists. Stepwise methods do not allow modelers to think about the model at hand. Plus, some causal variables may not be statistically significant, while some nuisance variables may be coincidentally significant due to high N. Automated regression using p-values is a bad idea because it also ignores multiplicity problems.
(2) a- 22.6% of the cases included had no surgery, how then were they diagnosed as glioblastomas if no tissue samples were available? It is unclear if surgeries comprised craniotomies and biopsies or the former alone.
b- All glioblastomas and gliosarcomas are grade IV tumors, however, for some reason, grade is a variable included in the models with levels of grade I, II, III, and IV!
c- Reference categories in the authors' models were selected alphabetically rather than clinically. For Site, there are 14 levels using ICD-O classifications. Such classifications are not meant for clinical correlations. For example, all Lobar sites (frontal, pariental, occipital etc) are part of the Cerebrum. There are only 2 cases available for cauda equina glioblastomas, which is nonsensical to include as a separate level in the model (which puts more constraints in the model's degrees of freedom while also resulting in unstable ratios).
d- Finally, the median survival for glioblastoma patients as noted by the authors was eight months. Looking for model accuracy at 120 months is just insane.
This would have a been a neat paper had the authors run a proper Cox model rather than run a straw man, and designed their study with a neuro-oncologist. Even then, please note that this preprint is concerned with the performace of these models IN BIG DATA only, so do not extrapolate to the data you are routinely working with.
On 2021-12-28 14:49:56, user Bob Horvath wrote:
There is a typo in the confidence interval reported here: "36.7% (95% CI: 69.9 to 76.4%)", since the confidence interval needs to incorporate the value of 36.7%.
Also, this paper defines vaccine effectiveness (VE) as protection against infection. As can be seen from some of the tweets on this study, that is confusing readers who don't realize the EUA granted in the U.S., for example, is based on definitions of effectiveness related to hospitalization and/or death. It would be very helpful to many to have this even very briefly clarified in your paper, that, for example, even if the VE was 0% (or even negative, as some of the threads here claim is being shown after 90 days) according to the definition used in this study, as long as it had more than 50% effectiveness against hospitalization and death, that it would still be used in the U.S.
On 2021-12-25 16:28:07, user 101nemesis wrote:
The actual study itself and none of the referenced articles and studies implies that negative VE% = increase in chance of infection.
You're making that assumption based on no actual foundation aside from an utterly basic interpretation of the graph despite the fact that this study used the very same graph to state it proves their claim that there should be MORE widespread vaccinations. <br /> So it's clearly not what you think it is.
That being said, the graph definitely needs more clarity.
On 2021-12-28 00:53:06, user Drew wrote:
Two issues need to be corrected for in the data before any real conclusions can be drawn. First, is there a relationship between age stratification, higher vaccination status and higher symptomatic disease - i.e., Simpson's Paradox. Second, was there a behavioral reason that impacted the results? For example, if vaccinations were required for admittance to crowded venue during the initial spike in Omicron cases, it would have skewed the results toward negative effectiveness.
On 2021-02-20 21:09:56, user Rony wrote:
The paper is now published in PLOS ONE:<br /> https://journals.plos.org/p...
On 2021-11-23 13:37:54, user FailedPolitics wrote:
So what are politicians waiting for? Why is the common D3 deficiency in elder care homes still normal?
On 2025-09-24 08:57:19, user Sophie PILLERON wrote:
This paper states that it uses the Globocan dataset; however, Globocan does not provide cancer incidence trends data. I suspect that the authors actually used CI5 data instead, which are available up to 2017.
In addition, this paper is very similar to another one ( https://pubmed.ncbi.nlm.nih.gov/34866023/ <br /> ), which the authors did not cite. The main differences between the two are the age groups analysed and the fact that the cited paper used data only up to 2012.
I would also recommend specifying the data source in the abstract, as this information is useful for interpreting the findings.
A justification for grouping all individuals aged 50+ together is needed, as this is a very heterogeneous age group. While I understand that the main focus of the paper is on the younger age group, the comparison would be more meaningful if the age categories used were more relevant.
I also suggest authors to reconsider the use of statistical testing. The study aim being descriptive, the use of statistical test is not needed as no a priori hypothesis are tested.
On 2022-12-24 03:16:24, user ArCH wrote:
Published version<br /> https://www.frontiersin.org...
On 2021-10-01 15:08:14, user Vince Dhimos wrote:
The developers should now do a comparative study with other competing vaccines.
On 2021-10-31 00:18:35, user Syed wrote:
The study itself does not cite the FDA for the definitions of severe adverse events (for vaccinations, not for severe COVID-19). They only specifically state that severe adverse events, while they include life threatening events among others, are defined by much more broad guidelines. Table S3 of Supplementary Index does not have any associated or detached citation to the FDA for their definition of SAE, and the recommendations for the Guidelines are non binding. So, it seems like the study design chose to define SAE by their own standards rather than the FDA, likely leading to a higher count of SAE.
Also, this toxicity report is from 2007, and not an updated recommendation for this vaccine type trial. Regardless, the study design didn’t use this definition.
On 2021-09-01 13:11:23, user Dr. van Nostrand MD PhD DDS wrote:
You're correct. The placebo, ideally, should contain everything but the active ingredients.
On 2021-08-19 07:37:44, user dixon pinfold wrote:
The bulk of these comments cover in a more or less cogent manner the various ways the survey results could be wrong—the portion, that is, concerning respondents who reported holding doctoral degrees. No one questions the other findings, which are all congenial to ordinary educated prejudices.
Few are dissatisfied with the survey's respondents having self-selected, which I view as the chief problem with it. I am inclined to say quite flatly: Not a random sample, not valid. But then, if self-selection were the main objection in these comments, all the education-category results would fall under similar doubt, not just one. Is that why this objection seems not to have occurred to many?
I read anxiety and indignation into the tone of most of the comments. I confess to a slight doubt about the depth of their sincerity. I feel quite certain that if the survey showed a mere 1% of doctorate holders were vaccine-hesitant, the commenters would instead be saying "See? The more educated you are, the less likely you are to be vaccine-hesitant" and would express at least qualified approval of the survey.
Needless to say, these are mere opinions of mine. I should be interested to hear other people's.
(N.B. I myself have received two Moderna doses and mention it to establish my bona fides, not wishing to be pilloried for a lack of it.)
On 2020-04-10 07:07:16, user Red Sage wrote:
One explanation re New York's higher stats is lack of health insurance leads to delays seeking medical assistance when illness gets serious
On 2021-03-19 17:43:57, user Kebbiet wrote:
Wait.....what were the mother's antibody titres BEFORE the vaccination? "Covid naïve" could be asymptomatic natural antibody formation after a year of frontline care provided during the pandemic. As with PCR testing, a negative result is only good at the time the test sample was obtained. As soon as the patient leaves the testing site, they may be exposed and turn positive from that exposure. To establish true Covid naivety, we would need to know whether there were detectable maternal antibodies immediately before administration of the 1st shot. A negative antibody test 6 months prior is of no value in establishing a direct connection of neonatal antibodies to the vaccine. We already know that Covid+ mothers have given birth to babies with detectable antibodies. We are missing a correlation step in this analysis.
On 2021-06-22 16:51:16, user Timothy Dennis wrote:
Humanigens lenzilumab is much further along that this one. $HGEN is a much better bet at this time with EUA for US & UK submitted.
On 2020-10-22 13:36:33, user Olaf Lange wrote:
This is comprehensive study, which answers many topical questions. Still I am wondering about one part. If I start to observe an empty room and than at a time zero people start breathing I would assume, that the particles, which are able to transport a virus, increase. But they drop by 30% even without purifiers. Do we look at the right parameters, which are able represent the increasing production of respiration?
Another explanation is that the humans acts as filters themselves, as stated in the text. Actually they would filter even more, than they produce. In this case, experiments with empty rooms, with and without purifiers might be a good supplement to determine absorption rate of the humans.
On 2021-02-02 22:45:20, user Elizabeth McNally wrote:
We are running similar ELISA assays after vaccination and not seeing this same robust IgG response. I would like to see more data prior making any recommendations about deviating from the vaccination protocols followed in the clinical trials.
On 2021-07-27 14:19:13, user Marco Biraghi wrote:
I think there's a mistake in the year: <br /> (data were collected in the period September 1st-November 30 2021).
On 2021-04-09 15:25:22, user David Rubin wrote:
Entyvio (vedolizumab) is selective to a T cell subset and doesn't affect your B cell immune response. Early data in IBD show no difference in titers after mRNA vaccinations.
On 2022-11-10 06:25:14, user David Hinds wrote:
This paper has been published: https://doi.org/10.1038/s41...
On 2021-11-06 19:21:58, user Eleutherodactylus Sciagraphus wrote:
This preprintincludes data from human subjects that are under ethical scrutiny. The <br /> majority of patients enrolled were not informed nor agreed onparticipating in the study. The Brazilian National Comission forResearch Ethics (CONEP) has been bypassed, documents have been tampered, and the situation is now under investigation.
References supporting this statement (both in English and in Portuguese):
https://brazilian.report/li...
https://www.emergency-live....
https://www.dire.it/14-10-2...
On 2025-04-23 07:12:26, user Johannes Rainer wrote:
The peer-reviewed and published version of this preprint is available here: https://doi.org/10.1038/s43856-025-00856-0
On 2022-01-19 19:56:15, user Victor Yman wrote:
This is a preprint of an article published in Nature Communications. The final authenticated version is available online at: https://doi.org/10.1038/s41...
On 2020-05-02 22:05:03, user Diego Fleitas wrote:
The problem is that in their weight, they multiply by three the Hispanic population, which has a very high level of prevalence, 4,9%. That changes dramatically the final output.
On 2021-09-13 23:40:58, user Tom Wenseleers wrote:
Regarding the line "Ad hoc methods to estimate the relative transmissibility of particular SARS-CoV-2 lineages are a computationally efficient alternative (1–3), but have typically relied on models in which one or two lineages of interest are compared to all others and cannot capture the complex dynamics of multiple co-circulating lineages.": this is not quite accurate - ref (1) - Davies et al. Science 2021 (https://science.sciencemag.... "https://science.sciencemag.org/content/372/6538/eabg3055)") actually also uses multinomial (mixed) models to model the competition among >2 co-circulating lineages and estimates the pairwise transmission advantages. Likewise, Campbell et al. Eurosurveillance 2021 also used multinomial models, https://www.eurosurveillanc..., as did Vohringer et al., https://www.medrxiv.org/con.... Best to rephrase this part to make it more accurate, and adequately cite previous work that used multinomial models to estimate the growth rate advantage of different lineages. I also wouldn't call such a model "as hoc", as it's the analytical solution expected with several competing lineages with different transmissibility in an asexual population. Also worth mentioning perhaps why https://www.nature.com/arti... did not succeed in identifying any major mutation under selection (I presume this is due to low statistical power of that phylogenetic RoHO test statistic used).
On 2020-05-07 10:51:23, user Concerned Citizen wrote:
How is this different or improve on a paper that came out earlier almost a month ago and was already published in a peer-reviewed journal (strangely also does not seem to have cited that paper): https://www.medrxiv.org/con...
On 2021-09-29 11:57:21, user kdrl nakle wrote:
Awesome, confirms what I have always suspected and it relates well to earlier research into European intro of SARS-CoV-2 (5-6 R0).
On 2020-07-09 05:04:08, user Hesham wrote:
Based on your validation data (p1 of the supplemental material), you had better sensitivity/LOD for E, N1, and N2 than you did for IP2/IP4. Therefore if you were able to detect IP2/IP4 in the March 12, 2019 samples (Fig 2A in your results), you should have been able to detect E, N1 and N2. But you didn't ! This is not consistent with the presence of SARS-Cov-2 and would never qualify as a positive result.
I would question the wisdom of publishing such tentative data, especially in the current environment. There are people such as Tom Jefferson of Oxford who are citing your work as "proof" to support outlandish claims about the origins of this virus. I fear this article is causing more harm than good.
On 2024-05-04 17:43:46, user VINOD KUMAR CHAUHAN wrote:
This paper has been published with changes in the title of the paper. Kindly link the published paper to the preprint.<br /> Published paper link: https://bmcmedinformdecisma...
On 2023-11-05 07:39:12, user Anikó Lovik wrote:
This preprint has now been accepted for publication in The Lancet Regional Health - Europe. The final version can be accessed here: https://www.thelancet.com/j... or through DOI: 10.1016/j.lanepe.2023.100756 or
On 2021-12-21 00:17:11, user lbaustin wrote:
Were the "reinfections" in people who were symptomatic both times, or is it possible that one or both of the tests were false positives? It could well be that people are being tested more now, or that the cycle threshold has been raised, either of which results in more false positives.
On 2021-10-05 13:12:28, user Benjamin Paradis wrote:
Interesting. Are we seeing similar results with studies that use other methodologies than self-reporting?
On 2022-12-09 13:17:21, user Maja wrote:
I applaud the authors for their meaningful work on reporting COVID-19 trials. The results are fascinating. Only 19% of COVID-19 clinical trials were published within three months of completion, which shows how much work has to be done regarding research transparency, publishing trial results, and responsibility while conducting clinical trials. Timely publication of results and avoiding research waste in clinical trials should be a priority, especially during global public health emergencies, such as the COVID-19 pandemic.
On 2021-10-13 01:57:34, user zega wrote:
In results " 6/6,846 (0.09%) patients" "April 1, 2020 - March 31, 2021 time period" Not just asymptomatic, pretty much vast majority of infected kids are not in the equation, 6846, that is the number of subjects in study, there was milion of kids PCR-DETECTED and that is small fraction judging by NEJM paper... that is worse then cherry-picking, that is finely refined selection...
On 2021-12-26 20:00:42, user Lee Jimmy wrote:
I read the preprint and could not find any mention of mask use/non use nor was the type of "activity" at this gathering spelled out. Anybody know anything about these details ? Do I need new reading glasses? Etc.
On 2021-06-20 14:25:52, user Ricardo S R wrote:
Do you have data on which patients had anosmia? Since the primary olfactory cortex is involved, would be interesting to know if this volume loss is related to plasticity/wallerian degeneration-like phenomena.
On 2020-05-25 16:37:02, user James Lesther wrote:
Interesting results, though this paper seems to replicate this previously published work, which came to similar conclusions much more comprehensively almost 2 weeks ago:<br /> https://www.medrxiv.org/con...
On 2020-05-01 05:08:22, user Adapt Research wrote:
Hi, far too early to be speculating on this. The high GHSI countries are also the high GDP ones and the high air traffic ones. The number of tests is mostly correlated with the number of cases, not the GHSI. It may yet be the case that high GHSI countries end up with less deaths per capita than low GHSI ones. We are nowhere near the end yet, and don't know what will happen in Africa where the largest concentration of low GHSI countries is. The correlations are interesting, but we're not able to draw conclusions yet.
On 2024-10-31 12:46:20, user None wrote:
This has now been published in HGG Advances: https://doi.org/10.1016/j.xhgg.2024.100375
On 2022-01-14 21:44:55, user JJ wrote:
The results are interesting and valid - but in my opinion, this is true only until the moment when the testing strategy started to differ for vaccinated and unvaccinated individuals (since about the end of summer 2021, vaccinated individuals did not have to test even if in close contact with a PCR-positive person while unvaccinated had to do so). This naturally lead to the increased difference between the numbers of unvaccinated than vaccinated PCR-positive individuals, which is a major source of bias that should be, in my opinion, removed.
On 2020-11-14 02:00:10, user Melimelo wrote:
Hi, very interesting article. Which software did you use for initial qualitative coding and subsequent text mining? are there particular commands or functions in a given software package that were useful? are you sharing your code anywhere (eg github?)
On 2020-05-13 01:25:02, user Joe Exum wrote:
N.C. is projected to need more ICU units than it has capacity in August? Is this correct?
On 2020-10-27 00:19:10, user Critical Dissection wrote:
Dear author,
Thank you for posting this article! It was truly very informative and will likely have important implications in resolving disorders of the heart, or possibly in other diseases and organs one day. I appreciated how thoroughly you expanded upon the criteria, explained considerations and acknowledged limitations, particularly in the discussion section. Additionally, patients' medical history and data were depicted very well through the tables in the Results section, so this was helpful in providing additional background. Overall, the methods and discussion sections were very detailed and provided excellent insight on this topic.
I have some feedback and recommendations for this study and article that I believe will help to improve clarity and reach a wider audience. First, it may be helpful to include more background about atrial flutters and ablation techniques in the introduction section. This would allow a more diverse audience of readers to understand the paper's contents without referring to external sources. Further, the results were not explained in great detail, so it was slightly difficult to interpret the figures presented. There was a more substantial mention of these results in the discussion section, but there may be some merit in including a direct explanation of each figure. Lastly, the small sample size likely caused bias in the results, as mentioned in the study limitations. The study would reach a larger category of patients if the criteria were less specific, so I would love to see a follow-up study, perhaps with expanded scope.
Overall, this article was very interesting! I do not have much background in the field, so I found some parts difficult to understand without reviewing external sources, and I believe there are some improvements that could be made to make this article more accessible to the public and the study more generalizable. Thank you, and I hope to see some future studies on this topic!
On 2020-10-22 21:10:27, user Critical Dissection wrote:
Dear author,
After reading your article, here are my comments. I will start out with positive; the abstract was greatly laid out. I like how it is broken down to individual parts. It helped me navigate that section better. Your discussion section hits a variety points discussed in the paper and wrap it up nicely. Now to discuss certain things that were missing. Presentation is very important, and the paper lack the proper flow to achieve that presentation, for example table 1 was not present as a unique table but broken down into two pages which can be confusing for some. The figures were not explained, and conclusion had to be made from the caption and some information. A major issue in deciding if this method works is the sample size and lack of a control population. Further trials would have to be done as indicated in the study limitations, bias should be minimized in next group and a control group containing patients needing ablation but never had one before would be recommended.
On 2021-05-21 04:28:38, user Irem Karaman wrote:
Published version of this manuscript: https://www.tandfonline.com...
On 2020-09-06 01:19:56, user Jack Winters wrote:
I've done a lot of modeling of physiological systems (e.g., writing a textbook on physiological modeling and control, Emeritus Professor of Biomedical Engineering), and implementation of the core SEIR model is straightforward (e.g., set up Matlab and JavaScript versions, as classic forward dynamic simulations). I'm aiming to use (and perhaps improve) this model. But I've dug around, and despite manifold data and supplementary info, I cannot find any examples of representative parameters (e.g., sigma, alphas, gamma1&2, and so on - it's not a large list). I know they're fit (e.g., by state), but there should be "typical values" available. Maybe for Oregon (where I live now)? I'm less worried about Beta, essentially the input signal (surprised AI methods (vs stat fitting) aren't being used for it, but that's a separate matter). Did I miss something? Can someone help?
On 2020-08-04 08:17:28, user OxImmuno Literature Initiative wrote:
On 2020-09-13 00:32:10, user Jacques des Anges wrote:
As a reference you can look at excess deaths in 2020.
https://www.cdc.gov/nchs/nv...
There are way more deaths this year compared to the previous years. Whether those people died of pneumonia with COVID or just COVID only is not really relevant. A lot more people have died this year in the US as well as other countries than previous years that are likely due to the pandemic.
On 2020-08-04 10:47:13, user Tomasz Marczyk wrote:
As I understand children 0-14 years of age are responsible for 1,27% spread of the disease (11 of 890 cases).<br /> I really don’t understand why there is no such conclusion in this paper.
On 2021-11-02 20:37:00, user Amanda wrote:
VAERS data should not be used to determine causation - we are told again and again. It should be used to find safety signals so further RCTs can be done. That is what we are told. yet here the CDC have used VAERS data to determine there is no causation. Second, the all cause mortality of (assuming approx) 150,000,000 people from 300,000,000 doses would be 1,290,000 if every single death was reported. Only 4,472 deaths were reported. Yet we know there would have been at least 1,290,000 deaths anyway. Your paper basically says that because 4,472 is less than 1,290,000 that that proves the vaccine is safe. This is the worst science I have ever seen. Clearly the required parameters of full reporting aren't even met. You'd be better off comparing death rates per dose or person with previous years, which you rejected on the grounds that deaths are required to be reported, so the reported numbers are going to be elevated compared with previous years. What you are saying is that previous years reporting is under-reported. Surely then that should also be investigated and raise a red flag? Second, death reporting is similar in other European countries, showing your doctors have no more time to spend half an hour filling out a death report when they don't think it is related to the vaccine than anyone else. At best, this proves further investigation is necessary through randomised controlled trials. At worst, it says there is no evidence for safety of the vaccines. If the vaccine death rate truley were 4.472/150,000 people, (= 0.003% or one in 33,000) then the original clinical trials would not have detected it with a sample size of 18,000. The idea of VAERS is to detect rare safety signals. This paper outright dismisses the signal, that death reporting per dose has increased by orders of magnitude higher than other vaccines in other years. I actually can't believe comparing all cause mortality to reported deaths is used to infer vaccine safety, by all places the CDC. Who is peer reviewing this? I'd like to contact them.
On 2020-04-08 12:59:52, user Giuseppe De Natale wrote:
The large range of the estimates only depends from the range for IFR we tested. However, the internationally assumed IFR=0.2% gives the estimate (at March 25th) of 3.3 million people. Today, the number of cases would be, assuming the same IFR, some 7 million people. The only way to have a more meaningful estimation would be to test for infection and/or antibodies a representative, random sample of population. This is what we are recommending.
On 2021-02-19 20:02:18, user Miguel Blacutt wrote:
Note from authors: The title of this manuscript was previously, "I want to move my body - right now! The CRAVE Scale to measure state motivation for physical activity and sedentary behavior".
On 2021-07-23 22:14:04, user John Ivy Ping wrote:
Mask didn't work in 1918 because less than half wore mask, however, those cities that did have mask. Mandates did fair better than those without.
Cloth mask are not 100% effective and air tight suit is.
On 2021-07-19 17:09:19, user yuk wrote:
Believe it or not before 2020 superflab is right. Go a google search for "masks prevent infection vs vaccination", then in tools pick custom date range between 2010 and 2019. you see a great deal of debate was out about the 2010 move to have all healthcare workers taking a vaccine for the flu. People that wanted to opt out were arguing they could just wear a mask.
So instead of debating what many believe is politically motivated science, how about we look at the science before 2020?
Here is an interesting read that comes from the CDC and was based on research from before 2020.
https://wwwnc.cdc.gov/eid/a...
"Respiratory etiquette is often listed as a preventive measure for respiratory infections. However, there is a lack of scientific evidence to support this measure."
"In pooled analysis, we found no significant reduction in influenza transmission with the use of face masks"
"The effect of hand hygiene combined with face masks on laboratory-confirmed influenza was not statistically significant "
"There is limited evidence for their effectiveness in preventing influenza virus transmission either when worn by the infected person for source control or when worn by uninfected persons to reduce exposure. Our systematic review found no significant effect of face masks on transmission of laboratory-confirmed influenza."
"Finally, although our review focused on nonpharmaceutical measures to be taken during influenza pandemics, the findings could also apply to severe seasonal influenza epidemics. Evidence from RCTs of hand hygiene or face masks did not support a substantial effect on transmission of laboratory-confirmed influenza, and limited evidence was available on other environmental measures."
On 2022-08-10 17:46:53, user Prajwal Mani Pradhan wrote:
Thank you for all the comments and reviews. We have updated and <br /> published the study in a peer-reviewed journal. The updated study can be
accessed here at no extra cost:
On 2020-07-16 20:57:09, user Kate Webb wrote:
Really interesting- are the samples from MIS-C all before IVIG?
On 2020-05-14 12:31:40, user Riccardo Pecori wrote:
Very nice work. A couple of questions for the authors: <br /> 1 - in the self-collected samples (Triton experiment) what is the volume of PBS in which the swabs are rinsed? <br /> 2 - would it be possible to get the written instructions for self-sampling? It would be beneficial for the standardization of the sampling.
On 2020-03-28 01:06:18, user Sinai Immunol Review Project wrote:
Summary: Analyzing the eGFR (effective glomerular flow rate) of 85 Covid-19 patients and characterizing tissue damage and viral presence in post-mortem kidney samples from 6 Covid-19 patients, the authors conclude that significant damage occurs to the kidney, following Covid-19 infection. This is in contrast to the SARS infection from the 2003 outbreak. They determine this damage to be more prevalent in patients older than 60 years old, as determined by analysis of eGFR. H&E and IHC analysis in 6 Covid-19 patients revealed that damage was in the tubules, not the glomeruli of the kidneys and suggested that macrophage accumulation and C5b-9 deposition are key to this process.
Limitations: H&E and IHC samples were performed on post-mortem samples of unknown age, thus we cannot assess how/if age correlates with kidney damage, upon Covid-19 infection. Additionally, eGFR was the only in-vivo measurement. Blood urea nitrogen and proteinuria are amongst other measurements that could have been obtained from patient records. An immune panel of the blood was not performed to assess immune system activation. Additionally, patients are only from one hospital.
Significance: This report makes clear that kidney damage is prevalent in Covid-19 patients and should be accounted for.
On 2020-07-26 06:33:24, user Aurora Fontanilla wrote:
X-linked recessive gene carriers (mothers of G6PD deficient) should also be considered in the study as they may already be considered as immunocompromised. If so, they may easily spread the virus to their children G6PD deficiency.
On 2021-08-07 16:14:30, user Dmitry Pruss wrote:
Isn't it a time-of-testing confounding effect? In Israel, percent of positive tests increased from 0.1% in the beginning of the study period to 1.5% in its end, which would likely result in an artifactual increase of positive in those vaccinated (and tested) earlier...
On 2025-03-14 16:31:28, user Andrea Bellavia wrote:
The paper is now published on EBPH https://riviste.unimi.it/index.php/ebph/article/view/28145
On 2021-04-26 03:17:28, user YingYing Irene Wang wrote:
The Journal of Deaf Studies and Deaf Education - Accepted for publication, DOI: http://doi.org/10.1093/deaf... --- online publication is under process. It will be online shortly. Thanks.
On 2024-02-26 15:44:36, user Anthony Dallosso wrote:
Hi - supp figure S3 is mentioned in the text but I can't see it in the Supplementary info link. Is this available somewhere please?
On 2022-08-03 13:35:17, user V Morris wrote:
Abstract needs editing for clarity, i.e., this "In all, 243 subjects were infected with COVID-19, of whom 97 had been wearing masks and 146 had not. " where no data on total number of people in studies is provided so it could be interpreted as masks not being very effective in preventing infection.
On 2020-02-10 20:08:48, user Marc Bevand wrote:
93.6% of cases (1029 out of 1099) are still in the hospital. Their outcome (death or recovery) is not known yet. This is why the case fatality rate observed (1.4%) so far is low..
For comparison, the two other studies with 41 and 99 cases had only 17% and 58% cases still in the hospital at the time of their writing. More cases had resolved, this is why their case fatality rate was higher (15% and 11%).
On 2020-04-25 14:55:25, user Ivan Berlin wrote:
Fontanet et al. Cluster of COVID-19 in northern France: A retrospective closed cohort study<br /> medRxiv preprint doi: https://doi.org/10.1101/202...<br /> Commentary about the finding of lower prevalence of anti-SARS-CoV2 seropositivity among smokers compared to non-smokers.<br /> Ivan Berlin, Daniel Thomas, Anne-Laurence Le Faou, Paris, France<br /> This is a correctly run retrospective closed cohort study aimed to assess the prevalence of anti-SARS-CoV2 seropositivity among a group of 661 individuals in a region of France with high COVID-19 incidence rate. Seropositivity and clinical symptoms (questionnaires) were assessed. No RT-PCR data are provided about the presence or absence of SARS-CoV2. <br /> To note that among the 878 individuals first invited, only 326 (37%) agreed to participate. Further, the sample was completed by 345 individuals. This recruitment history cannot exclude selection bias e.g. smokers or former smokers were more likely to decline participation than nonsmokers.<br /> Of the 661 participants 452 (68,4%) reported respiratory symptoms and could be considered as having COVID-19. Among the 661 participants only 171 had anti-SARS-CoV2 seropositivity (25.9 %).The discriminative ability of the serological determination seems to be weak with respect of the clinical symptoms in particular between no symptoms and minor symptoms according to Suppl. Table 1: No symptoms: 13.9%; Minor symptoms: 16%, Major symptoms 37.7 % (but Minor symptoms: 26% according to Table 2. <br /> The reported smoking rate is 10.4 % (69/661). Out of the 661 individuals tested, among nonsmokers 167 (25.7%) and among the smokers 5/69 (7.2%) were tested serologically positive. No definition of “smokers”, no data about former smokers, no biochemical verification of smoking status are provided. It cannot be excluded that there were some occasional smokers, recent or long-term quitters in the nonsmoker group. <br /> Page 8 last paragraph: “Smoking was found to be associated with lower risk of infection ”after adjustment for age and occupation. No adjustment for gender was done, however the sample’s consists of largely more women than men (women: 62% men : 38%,) which is the opposite in the general population in France. The authors use “infection” for seropositivity all over the manuscript. However, infection can be implied if SARS-CoV2 RT-PCR is positive. The fact that 452 reported clinical symptoms of infection and only 25.9 % were seropositive leads to the question what are the factors contributing to seroconversion i.e. having a good immune response to SARS-CoV2. This is not explored in the paper (no SARS-CoV2 RT-PCR). A proxy answer to this question would be to provide detailed clinical and demographic information in Suppl Table 1, not only serological information. More specifically, what is the distribution of smokers and nonsmokers according to the clinical features and serological findings.<br /> Because of the low seropositive rates (25.9%) and lack of direct SARS-COV2 detection one cannot conclude about factors contributing to the seroconversion. One can hypothesize that the higher seropositive rate among nonsmokers can be due, among other factors, to the higher percent of women. <br /> In this sample the percent of women is higher than that of men contrary to other reports of individuals with COVID-19. In large samples, men have higher smoking rate than women and more men have COVID-19 than women. More than one third of the sample is <=17 years old; the smoking prevalence in this group is usually very low. It is likely that the nonsmokers with seroconversion are mainly women. One can hypothesize that smokers have a lower seroconversion rate that non-smokers explaining the lower percent of smokers with seropositivity.<br /> The observed lower anti-SARS-CoV2 seropositivity rate among smokers in this sample is an interesting unexpected but secondary finding. Before drawing any conclusion about this finding and generalize them, further studies are needed aiming to assess specifically the incidence of COVID-19, SARS-CoV2 infection and anti-SARS-CoV2 seropositivity among well documented smokers, correctly classified former smokers versus lifelong never smokers.
On 2021-05-14 15:19:36, user Misha Kogan wrote:
First controlled trial! Excellent news. Our real life experience with no funding is not so far off. At GWCIM over last 3 years 15 patients who stayed with program demonstrated 70% response rate with 4 patients showing very significant improvement. Funding is a key. Of 44 patients who came through out clinic most dropped out due to cost and logistics.
On 2019-11-30 17:27:53, user Guyguy wrote:
EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT NOVEMBER 28, 2019
Friday, November 29, 2019<br /> • Since the beginning of the epidemic, the cumulative number of cases is 3,309, of which 3,191 are confirmed and 118 are probable. In total, there were 2,201 deaths (2,083 confirmed and 118 probable) and 1077 people healed.<br /> • 335 suspected cases under investigation;<br /> • No new confirmed cases;<br /> • No new deaths among confirmed cases;<br /> • No cured person has emerged from CTEs;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 163 (5% of all confirmed / probable cases), including 41 deaths.
NEWS
Organization of a press conference on the situation and evolution of the Ebola Virus Disease in Beni
• The Beni Ebola Sub-Coordination in North Kivu organized a press conference on Ebola Virus Disease on Friday, November 28, 2019;<br /> • This press conference was moderated by the acting coordinator of this sub-coordination, Dr. Tosalisana Michel, who confirmed that the activities of the response continue to be carried out in Beni, despite the prevailing security situation;<br /> • He reported that the response to the last indigenous case recorded in Beni is still weak as the maximum contact is still out of sight;<br /> • On this occasion, Dr. Tosalisana called on the people of Beni and the surrounding areas affected by this 10th epidemic to accompany the teams of the response in their field work in order to spare this city from any new contamination.
Repatriation in Goma of the remains of two agents of the riposte who died during the Biakato attacks
• The mortal remains of two agents registered by the coordination of the response to the Ebola Virus Disease outbreak during the attacks on the night of Wednesday 27 to Thursday, November 28, 2019 in Biakato Mines in the province of Ituri have repatriated this Friday 29 November 2019 from Beni to Goma;<br /> • A strong delegation from the General Coordination of the Response, led by its coordinator, Prof. Steve Ahuka Mundeke, rushed to Goma Airport to receive these bodies which were then taken to the General Goma reference Hospital morgue. <br /> • Long before, teams from the Mangina and Biakato sub-coordination evacuees arrived in Goma. Since Thursday, November 28, 2019, a few dozen people from these two sub-coordination who were attacked were brought back to Goma for their relocation, said the general coordinator of the response the Prof. Steve Ahuka.
VACCINATION
• The vaccination commission is in mourning. A service provider and a driver of his team were killed on the night of Wednesday 27 November 2019 following attacks at the Biakato living base in Ituri;<br /> • 2nd day without vaccination activity with the 2nd J & J vaccine following the disorders initiated by young people related to the security situation in Beni;<br /> • 821 people were vaccinated with the 2nd Ad26.ZEBOV / MVA-BN-Filo vaccine (Johnson & Johnson) in the two Health Zones of Karisimbi in Goma;<br /> • From the start of vaccination on August 8, 2018 with the rVSV-ZEBOV vaccine, until November 27, 2019, 255,373 people were vaccinated;<br /> • Approved October 22, 2019 by the Ethics Committee of the School of Public Health of the University of Kinshasa and October 23, 2019 by the National Ethics Committee, the second vaccine, called Ad26.ZEBOV / MVA-BN -Filo, is produced by Janssen Pharmaceuticals for Johnson & Johnson;<br /> • This new vaccine is in addition to the first, the rVSV-ZEBOV, vaccine used until then (since August 08, 2018) in this epidemic manufactured by the pharmaceutical group Merck, after approval of the Ethics Committee on May 20, 2018. has recently been pre-qualified for registration.
MONITORING AT ENTRY POINTS
• Sanitary control activities are disrupted in the Beni and Mangina sub-coordinations in North Kivu, as well as Mambasa and Biakato in Ituri following the demonstrations of the population who decry the killings of civilians and the attacks of armed innocents who took target response teams;<br /> • Since the beginning of the epidemic, the total number of checked travelers (temperature rise) at the sanitary control points is 121,813,958 ;<br /> • To date, a total of 109 entry points (PoE) and sanitary control points (PoCs) have been set up in the provinces of North Kivu and Ituri to protect the country's major cities and prevent the spread of the epidemic in neighboring countries.
As a reminder, the recommendations of the MULTISECTORAL COMMITTEE OF THE RESPONSE TO EBOLA VIRUS DISEASE are as follows:
On 2024-04-28 19:43:09, user Laura Mihalidesz wrote:
I am a TSW sufferer and made a signifacant change to the worse in my condition when TS were introduced to my life 30 years ago, stopping the usage a age 26 and going into TSW the symptoms are uncoparable to eczema. This study is important to understand what harm can TS cause in the long run and after 9 years in TSW I still suffer from symptoms. The importnce of this research is not a question but answer to many patient's questions and finding and developing treatment methods.
On 2022-01-21 23:03:48, user COGSx86 wrote:
Vaccine durability is a key to understand why the vaxxed are out numbering the unvaxxed. Losing the proper anti bodies and exposing them more to these foreign invaders.
These occurrences of covid in the vaxxed group helps to show the correlation of individuals who waited to long for the boosters.
On 2020-04-04 17:14:06, user uzay emir wrote:
Also Turkey results are contradictory to this. Turkey has a different strain than Iran.
On 2020-04-04 20:39:58, user Arthur H wrote:
There definitely seems to be a correlation, but no correlative facts can override poor hygiene, bad general health and obesity. Aside from this I believe there are other things in common with populations which tend to persevere.
On 2020-04-19 00:43:04, user JK wrote:
Model is surely under estimating cumulative deaths by Aug 4th - trajectory suggests 80k - 90k...believe this was one of the earlier IHME projections
On 2020-04-06 07:06:24, user Tom T Walker wrote:
Many of the State projections radically changed when updated 4/5. For example Colorado's peak date went from 4/17 to 4/4, hence an ICU deficit of 762 to a surplus of 421. Other states had similar swings in the opposite direction. Wondering if there might have been some data entry issue. Is Colorado really suddenly 1-day past it's peak date?
On 2021-01-07 21:56:18, user Joseph Guinness wrote:
Hello, thanks for conducting this interesting study. We conducted a similar study last year and found similar results:<br /> https://researchers.one/art...
One potential issue with your design is that by taking the top 50 finishers at each race, you may be preferentially selecting people who respond more to Vaporflys: the so-called "super-responders". Put simply, if someone is a super responder, they are more likely to finish in the top 50 when they switch to vaporflys. This is somewhat ameliorated by the fact that a runner would have to finish in the top 50 in a race without the Vaporflys, but not completely.
For example, suppose two runners finish 49th and 50th in Boston without the Vaporflys, then they both switch to Vaporflys for Chicago, but one of them is a super responder and the other isn't. Then the super-responder is more likely to finish in the top 50 in Chicago, while the non-super-responder is not. If that happens, the super-responder gets kept in the study, while the non-super-responder gets dropped. Of course, it doesn't have to work out way, but the odds are tilted towards keeping the super-responder and dropping the non-super-responder.
We addressed this issue in our study by sampling runners according to a performance standard before the Vaporflys entered the market.
I'm guessing that if you addressed this issue, the results wouldn't change a lot, but it's something to consider.
It was a bit difficult to follow your description of how the analysis was done, specifically how you controlled for marathon difficulty and conditions of a specific race in a specific year. It might be helpful to write down a statistical model or go through the calculation for a few runners.
Overall, this is really interesting. We can appreciate (from experience) how tedious it is to comb through hundreds of race photos and identify the shoes runners wore.
On 2021-05-06 12:22:51, user Steeve Asselin wrote:
The old adage I feel applies here: It is not because we can do it that we should do it...Has thoughts ever been given to the potential of such innovative process to be misused by Life Insurance Companies to increase or worse, deny life insurance to a person because that innovation "estimated" (because it is an estimation NOT a calculation) that the probability of this person to die is above 50% in the coming years...
On 2020-04-19 08:34:23, user V Ferreira wrote:
Good morning are there any studies concerning interaction with water?
On 2020-04-11 21:57:12, user H van Woerden wrote:
I think that this is a really important paper as it starts to explore the cost effectiveness of different approaches.
I am concerned about the effect of the fall in average incomes over the next decade on life expectancy and analysis of that issue by this team would be helpful. Particularly the fall in income for lower socio-economic groups.
On 2020-06-02 10:57:42, user Bruce Nelson wrote:
The sample unit was the household. One person was tested per household. But SARS-CoV-2 is clustered by household, leading to possible underestimate of prevalence?
On 2020-10-22 03:50:45, user Shelley G wrote:
When I look at Predicted Case Rate, I cannot find MO. It does show up on the death rate chart. Am I just missing it or is MO missing from the Case chart?
On 2020-09-24 14:19:51, user Michael Bishop wrote:
You say other countries have found SARSCOV2 in sewers from samples up to 6 months before official cases. Do you have a citation for that? Any thoughts on a mechanism by which it could be detectable in sewers and yet extremely low cases and low test-positivity? Authors of the work under discussion should follow-up with more recent sewer samples... we know SARSCOV2 was spreading rapidly in April, May, June... do their sewage numbers track that?
On 2021-04-26 13:56:45, user Zorak wrote:
2 deaths in 200 cases. As far as we know, it is the same ratio of "untreated" cases. There's no improvement with this treatment.
On 2020-04-06 11:13:41, user japhetk wrote:
I think this is another voodoo correlation study of BCG which keeps appearing one after another. BCG may be effective or not effective, but that cannot be revealed by country analyses due to many uncontrolled and complex factors.
The problems of this study's analyses, they are not controlling when the infection spread in the country properly.
Other analyses are controlling that (for example, number of patients (or deaths) 10 days after the 100th patients were detected, was used as a dependent measure). In this study, only the 3 categorical classification is used, which is apparently not appropriate nor objective.
Also, probably, the most accurate available BCG measure is "how long the country has advanced the BCG vaccination measure" (the year when the country stopped the BCG vaccination (or now, when the BCG vaccination is currently conducted in the country) - the year when the country started it). UK for example, advanced BCG for more than 50 years, so the majority of the have been experienced with BCG. So, the "current" "past" "never" classification is not appropriate.
I controlled these measures and have done the analyses.
The results were as follows.<br /> The partial correlation between "how long the country has advanced the BCG vaccination measure" and number of patients in the 10th day (when 1st day is 100th patients were detected in the country) after controlling the population of the country. P = 0.455, partial correlation coefficient = -0.116).
The partial correlation between "how long the country has advanced the BCG vaccination measure" and number of deaths in the 10th day (when 1st day is the 100th patients were detected in the country) after controlling the population of the country. P = 0.111, partial correlation coefficient = -0.243).
But the partial correlation between "how long the country has advanced the BCG vaccination measure" and when the 100th patients were detected in the country after controlling the population of the country was P = 0.078, partial correlation coefficient = 0.281.
Also "how long the country has advanced the BCG vaccination measure" is robustly and negatively correlated with GDP of the country after controlling the population of the country (p = 0.019, partial correlation coefficient:-0.292).
But the correlation between GDP of the country and when the 100th patients were detected in the country after controlling population of the country was more robust (p = 0.001, partial correlation coefficient: -0.438)(the greater the GDP, the faster the 100th patients appeared).
And the correlation between "how long the country has advanced the BCG vaccination measure" and when the 100th patients were detected in the country disappeared when the population and GDP is also controlled (p = 0.322).<br /> Most of correlations are tendencies levels and disappeared or substantially got weaker after GDP is controlled.
So, my guess is probably, there are number of spurious correlations going on authors' analyses due to lack of important control variables.
The higher GDP countries can do more tests, they are more popular from the <br /> tourists from Asia, but they were less inclined to use masks as far as I heard and less alert.
The list of potential confounding variables, as far as I can see is endless and diverse.<br /> Such as numerous nutritional components, the foods of western rich countries include.<br /> The temperature. <br /> How many Chinese (ratio) is included in the nation (apparently Taiwan, China (except Wuhan) and other countries where Chinese consist most of nations were as alert as possible). <br /> Preference of wearing masks.<br /> Popularity of religion. (Religious ceremonies are cited as the popular source of the cluster of infections).<br /> The strength of individual rights and freedoms.<br /> The factors related to Western rich countries.
In the case of Diamond princess, Japanese was apparently not invincible.<br /> About 300 patients were Japanese and 180 patients were from Western rich countries in the case of this ship, and among them, 7 Japanese died and 2 from Canada and UK died. Japanese were not biological invincible from this coronavirus, please stop spreading this rumor through country based correlation studies… Just please wait for RCT studies.
On 2021-12-31 16:37:47, user Chris Holm wrote:
I think this part is very important. "We observed no difference in the LoS for patients not admitted to ICU,nor odds of in-hospital death between vaccinated and unvaccinated <br /> patients."
So, the unvaccinated doesn't spend more time in <br /> the hospital (except for those admitted to the ICU). And in any case, <br /> the unvaccinated are not more likely to die from covid. Good to know.
On 2020-05-07 20:20:44, user Gregory Kreiss wrote:
6% positive cases for 5-19 years old versus 8.5% for 20-49 years does not look like similar but an increase of 40% for the middle ages adults!<br /> Also one of the major limitation of this study is that we do not know wether the infected children are part of household where one of the adult has been also infected (cluster effect) and if it is the case who has infected who. To be conclusive the children should have been selected randomly within the population and not part of the household members.
On 2020-06-15 22:51:11, user Marm Kilpatrick wrote:
One more quick comment. The paper indicates that those tested were asymptomatic but in the Methods and other sections it's not clear how this was verified. Were those being tested asked to report on whether they currently had symptoms? If so, were they not tested that week? Do you have information on when those that tested positive developed symptoms? This data is rare and would be very valuable. Thank you!<br /> marm
On 2022-02-06 23:31:27, user Danilo Vieira wrote:
I consider that the lack of education in PGx among clinicians makes implementation difficult, but I don't think this barrier is 'extremely' relevant.
On 2020-06-12 20:05:26, user Bob wrote:
public interest has followed ecological studies
I think they meant epidemiological
On 2020-06-02 05:55:45, user OxImmuno Literature Initiative wrote:
On 2020-07-26 17:35:19, user Dude Dujmovic wrote:
Very interesting paper but I think emphasis on waning humoral immunity is misplaced in most recent papers. This infection will be controlled by memory lymphocytes not by present antibodies. .
On 2020-05-20 12:50:05, user Neil Oxtoby wrote:
Minor correction to your text on page 5 "subtyping studies using longitudinal sMRI...": SuStaIn (PMID:30323170) uses cross-sectional sMRI.
On 2021-11-17 05:34:19, user V Deepak Bamola wrote:
This preprint is under review at 'Experimental Biology and Medicine'<br /> @medrxivpreprint:Effect of Bacillus coagulans Unique IS-2 in Inflammatory Bowel Disease (IBD): A Randomized Controlled Trial https://t.co/hH32BrOdYT #medRxiv
On 2025-10-21 00:30:29, user CDSL JHSPH wrote:
Hello!
I really enjoy reading your paper. It is inspiring that model-based techniques such as MCP-Mod and FP1 work better than traditional Dunnet test in determining the minimum effective duration (MED) in phase II trials. It offers reliable and efficient insights into estimation of optimal antibiotic treatment durations.
Its application to advancing WHO’s End TB targets makes it a significant contribution. The methodology is convincing. It clearly outlines the limitations of traditional pairwise comparison methods, emphasizing why a shift toward model-driven designs is necessary. The experiments are well designed. It would be more convincing by applying real world data in the models. And this is the most important limitation and what I highly recommend to dig in the future.
The writing is logical and ideas are well- presented. It follows the modern scientific literature structure. The main takeaway for other researchers I think is that rather than developing entirely new tools, researchers can improve and reuse existing and proven frameworks to solve similar problems. This helps reducing redundancy and deeper developing a proven foundation.
On 2020-05-09 23:51:12, user Sinai Immunol Review Project wrote:
Main findings<br /> The humoral response to SARS-CoV-2 infection has been largely studied in the context of antibody distribution in the peripheral blood of COVID-19 patients. However, little has been explored that evaluates immunophenotyping of B cells in patients with different clinical courses of COVID-19. Here, Woodruff et al. investigated B cell populations by spectral flow cytometry to understand the protective and non-protective humoral responses using PBMCs from 9 critically ill and 8 mild patients with COVID-19.
Comparing CD45+ hematopoietic cells from 22 healthy controls and 17 COVID-19 patients, the authors found an expansion of CD19+ B cells in COVID-19 patients with a significant increase in CD138+ antibody-secreting cells (ASCs) among other B cell subpopulations: transitional, naive, double-negative, and memory. Interestingly, a greater abundance of these mature, CD138+ ASCs, which are often associated with protection during a vaccine-induced response, was found in COVID-19 patients with worse outcomes. Previously, this group described, in flaring systemic lupus erythematosus (SLE), an activated IgD-CD27-double negative B cell population that they characterized as part of an extra-follicular (EF) response. The comparison of the PBMCs across COVID-19 samples revealed two clusters: one that strongly upregulated the EF response pathway (EF-CoV), and one with a low EF response but a high transitional B cell signal (Tr-CoV).
Within the EF-CoV cluster, ASC expansion correlated with enriched ASC maturation and an increase in the active naïve (IgD+CD11c+) and a subset of the double-negative (DN2: IgMlo IgD- CD11c+ CD21-) cell compartments. The composition of the double-negative component with skewing to the ASC-associated DN2 group in the EF-CoV cluster appeared identical to the B cell landscape of patients with active SLE. Similar to the increase in IL-6 and IP-10 during active SLE, association with upregulated IL-6 and IP-10 and poor prognosis for COVID-19 was also found in this study. Higher serum IL-6 and IP-10, a CXCR3 ligand, and expression of CXCR3 by B cell subpopulations belonging to the EF-CoV cluster, supports the notion that peripheral homing of B cells to inflamed tissue sites, as described in both the lung and kidneys, takes place in COVID-19 patients.
A minor subset of B cells in the EF-CoV cluster were CD21lo transitional B cells. These cells were enriched in the Tr-CoV cluster and associated with mild disease. They shared several B cell immaturity markers, such as high levels of CD10 and CD38, and expressed high levels of surface IgM and muted surface IgD, which indicate extrafollicular homing. A longitudinal comparison of two ICU patients in each cluster (two EF-CoV patients and two Tr-CoV patients) revealed that the paucity of CD21lo transitional B cells in the EF-CoV was associated with higher severity of disease and a decrease in PaO2/FiO2 ratio (a measure of gas exchange efficiency). EF-CoV patients had higher levels of CRP, which correlated with a low frequency of transitional B cells, a high number of DN2 B cells, and elevated serum IL-6. Importantly, these patients faced poorer outcomes.
Limitations<br /> Aside from the small sample size in the primary study and in the longitudinal follow-up, this report relies on surface markers to assess B cell heterogeneity in COVID-19 patients and characterize potential autoimmune subpopulations that are also present in SLE patients. However, there are limitations to the scope of coverage that flow cytometric analyses can provide. Single-cell RNA sequencing (scRNAseq) can provide a broader expression profile to distinguish subsets based on transcriptomic expression, as opposed to relying on existing, classical categorizations as done in this study. Therefore, higher granularity in the evaluation of cell-type heterogeneity may yield more precise assessments of cell-type similarities and differences between COVID-19 and autoimmune disease.
Importantly, the characterizations of B cell subpopulations in this study have largely been correlative. Trends with clinical outcome or existing prognostic markers are insufficient to define the roles that these cell types may play in the pathogenesis of COVID-19. Without additional studies (and accounting for the general lymphopenia already reported in COVID-19 patients), it is unclear whether these phenotypes are by-products of abnormal or absent T cell help or actual reactions to/consequences of SARS-CoV-2 infection.
Lastly, since this report identified similar B cell subsets in both critically ill COVID-19 patients and SLE patients, additional serological studies exploring any evidence of autoreactivity in EF-CoV patients with high IL-6 are warranted.
Significance<br /> Using a specialized flow cytometry panel for B cell analysis, the authors provide a description of the B cell landscape in COVID-19 patients. Understanding the role of potentially pathogenic B cell modules could be crucial for designing immuno-modulatory therapies that target pro-inflammatory or potentially autoimmune phenotypes seen with SARS-CoV-2 infections.
Reviewed by Matthew D. Park and Miyo Ota 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 14:55:39, user Mmd wrote:
How Can I access the data?
On 2022-02-19 00:11:02, user Sam Smith wrote:
Breakthrough cases were defined only from day 8 (in each arm as well as in the control group), to exclude early infections due to exposure before vaccine is effective.
Was 8 days too early?
Was control group a good idea, instead randomly been given a vaccine or not be given a vaccine?
On 2020-06-08 10:42:04, user J Sato wrote:
Thanks for the detailed analysis. Here is a similar and simpler one. Hope you can work on the other countries as well.<br /> https://www.jsatonotes.com/...
On 2022-11-11 09:33:21, user S Venkata Mohan wrote:
This article was published with the following citation
Surveillance of SARS-CoV-2 genome fragment in urban, peri-urban and rural water bodies: a temporal and comparative analysis<br /> p. 0987 | Hemalatha, Manupati; Tharak, Athmakuri; Kopperi, Harishankar; Kiran, Uday; Gokulan, C. G.; Mishra, Rakesh K.; Mohan, S. Venkata doi: 10.18520/cs/v123/i8/987-994.
Due to DOI issue we are not able to link
On 2021-09-15 14:55:56, user Geoff Bridges wrote:
There are many, many different types of PCR tests all of which are very accurate at detecting SARS-CoV-2 even the original Drosten et al test was quite accurate but has since been improved.<br /> The problem is that governments haven't requested the amplification or CT rate of all positive tests so we don't know whether the person tested is infectious or not. A low CT rate up to 20 is probably infectious, a mid CT rate of around 25 is possibly infectious and a high CT rate 25 to 45 probably not infectious.<br /> A study in the US suggested that 85% to 90% of positive cases are not infectious.<br /> https://www.nytimes.com/2020/08/29/health/coronavirus-testing.html<br /> A further PCR or LF test should be done a day later after self isolating on the 25 to 45 group to ascertain the trajectory of the virus in the person to see if they are coming OUT of an infection and therefore not infectious or going IN to an infection and therefore infectious.<br /> It is the lack of CT rate information which is causing the "casedemic" and NOT a fault with the PCR tests per se.<br /> The ONS Dataset, Coronavirus (COVID-19) Infection Survey: technical data, https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/datasets/covid19infectionsurveytechnicaldata shows the CT rate for a random number of people around the UK. If they set the upper limit of an infection at 25 then approximately 60% of cases would potentially not be infectious which could be confirmed with a Lateral Flow test 24 hours later. <br /> This would give an accurate view of how many people are actually “infectious” whilst giving those with positive test results but “not infectious” to carry on with their employment and lives and would avoid the problems with a “casedemic”.
On 2021-05-09 00:18:01, user Minga wrote:
The focus on a comparison between household vs non household contacts hide the lack of any comparison between schools, offices, or factories contacts vs non job-related contacts.
On 2021-01-17 01:45:40, user Oguzhan Alagoz wrote:
AN updated version of this paper is published by Annals of Internal Medicine:<br /> https://www.acpjournals.org...
Full updated citation is:<br /> Alagoz, O., Sethi, A. K., Patterson, B. W., Churpek, M., & Safdar, N. Effect of Timing of and Adherence to Social Distancing Measures on COVID-19 Burden in the United States: A Simulation Modeling Approach. Annals of internal medicine, M20-4096.
On 2023-10-06 12:35:59, user Ashok Palaniappan wrote:
An expanded, significantly revised and advanced version post peer-review is now available [open-access]:<br /> Muthamilselvan S, Raghavendran A, Palaniappan A. Stage-differentiated ensemble modeling of DNA methylation landscapes uncovers salient biomarkers and prognostic signatures in colorectal cancer progression. PLoS One. 2022 Feb 24;17(2):e0249151. doi: 10.1371/journal.pone.0249151. PMID: 35202405; PMCID: PMC8870460.
On 2020-04-23 06:40:04, user Sergey Morozov wrote:
Very actual study that brings new information to fill in the gap on the histological features of lungs in those who died of COVID-19. The paper seems methodologically correct and based on multicentre (2 hospitals) study with histological assessment performed by 2 pathologists blinded to the results of each other. For better compliance GPP, I would suggest to add the information of immediate cause of death to the description of the study population; the results of analysis of concordance of the results of tissue evaluation performed by 2 pathologists, who were involved to the study. As pre-existing chronic obstructive pulmonary disorders are described in 3 patients, could these cases influence the results of pulmonary fibrosis assessment? It would be nice also, if the past-malignancies localizations also were described. The statements are logical and are based on the described results. This study is rather explorative by nature and larger studies are necessary to make an association between different aspects that characterize the disease flow (including co-morbid pathologies, medications used, laboratory deviations, etc) with histological features<br /> observed in pulmonary tissues much clear.<br /> I have no conflict of interests in the regard to this review.
On 2021-07-02 23:04:45, user Ali Salehinejad, PhD wrote:
The peer-reviewed published article (open access) of this preprint can be found below:<br /> https://www.sciencedirect.c...
On 2021-01-20 16:40:59, user Le Bon wrote:
It's not about changing the outcome. They just can't conclude to the absence of any usefull effect. A viral clearance which disappear when the treatment is stopped is not proved useless. It just means that you treated not long enough.
On 2020-06-25 20:47:26, user J Chapman wrote:
Any testing on HLA B27?
On 2024-11-05 11:16:52, user Brechje de Gier wrote:
Published in Eurosurveillance: https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2024.29.40.2300739
On 2020-04-14 04:35:34, user Gianguido Cianci wrote:
Some of your colleagues have reviewed your ref 1 and pointed out some serious pitfalls. How do those valid criticisms affect your review of this preprint?
Also, you list Ref 1 as published in Microbiology (2020). I cannot find it and the DOI points to a preprint. Could you clarify, please?
On 2020-05-01 18:03:57, user Hannibal Lecter wrote:
I disagree, There is no research based resource allocation crunch associated with distributing HCQ to frontline doctors. You are not stopping Gilead to research Remdesvir, just because some doctor has access to prescribe HCQ to their patient. The medicine is used by millions of Lupus and Arthritis patients and so questioning its safety profile seems a little pedantic at this point. We are talking about a 10-14 day course of the medicine to reduce viral load. That's it. No one is talking about chronic use.
On 2020-11-19 12:22:03, user Bruno Gualano wrote:
Thank you, LB. This is in fact a limitation while working with severe patients in a quaternary hospital.
On 2020-06-08 09:03:15, user Paul McKeigue wrote:
All code used in the statistical analysis and the Rmarkdown source of this manuscript is available on a github repository (https://github.com/pmckeigu... "https://github.com/pmckeigue/covid-scotland_public)")
On 2020-04-14 11:02:19, user Philip Davies wrote:
This is a very interesting pre-print. BUT, I think the data in table 3 has been mixed up (deaths for low v high dose are incorrect). The authors need to correct this and then ensure the tables are correct everywhere else. I have asked the authors to look at this and re-issue a corrected version (I also question whether the qSOFA results (table 1) were meant to be for values >2 rather than <2.
This is important. It could mean that lower dose chloroquine is not only safe but could prove to be statistically better than placebo (will need the full 28 days analysis to know that).
Dr Phil Davies