On 2022-01-18 15:04:19, user JJackson wrote:
Figure 1a shows about a 10 day difference between the onset dates for delta and omicron cases with delta averaging mid Dec and Omicron nearer Christmas. Given that the date on the paper is 11th Jan this just is not giving adequate time for disease progression in the Omicron cases to expect ICU admissions and deaths. For a fair comparison numbers of hospitalisation, ICU admissions and deaths for Omicron should be take 10 days later than for Delta.
On 2022-01-14 20:01:53, user Ovi Constantin wrote:
No it won't, and no it's not propaganda, and no it's not because 'people took the masks' off. More than a few similar studies in multiple countries are showing - undeniably - the same thing: omicron is not just milder than delta, but also milder than the regular flu. One should look for a different explanation as to why the death rate in the US is still so high... and no, it's not because of the (supposedly lower) vaccination rate. Many countries with similar or lower vaccination rates than the US have lower covid death rates.
On 2021-06-09 16:22:28, user Vojtech Huser wrote:
Great paper about a tool that is used by OHDSI researchers.<br /> Relationship to Achilles Heel prior tool would be a good added discussion. Contribution from the community to the tool (besides core authors) can also be described.
On 2021-08-18 04:23:00, user Turncoat Don wrote:
Why don't you just make the data available to everyone? Just post a link here.
On 2020-12-03 17:33:21, user Nikita Mehta wrote:
Hello, I was wondering if RNA sequencing data for intronic variants (both canonical and non-canonical) was discussed in regards to PS3. Or at least adjusting PVS1's strength for canonical sites if possible?
On 2022-01-03 23:21:01, user Jason wrote:
Is this history not correct.. about RSV and measles? Or not conclusive about what the problem was? Few paragraphs down, after dengue discussion
On 2020-08-30 15:05:05, user Henry Johnson wrote:
Does anyone know whether similar experiments have been done with woodwind instruments. I'm particularly interested in clarinet. The instruments work differently. The sound comes out of a variety of places...
On 2020-09-10 08:52:36, user Maw Planes wrote:
How does family income bracket or socioeconomic status play a role in the level of anxiety?
On 2024-01-08 18:05:42, user jhick059 wrote:
This article was published in the peer-reviewed journal Cureus Journal of Medical Science on Dec. 14, 2023: https://doi.org/10.7759/cur...
On 2021-09-06 18:10:49, user michael gula wrote:
Study of 673,000 fully vaccinated. Comorbidities not considered. Finding : Vaccinated indiv's who were not previously infected by covid virus have a 13x greater risk of getting covid than those previously infected. Moreover, there is a 6x greater risk for people fully vaccinated to get covid than people not vaccinated and previously infected.
On 2021-09-03 19:05:14, user Dan C wrote:
Polio is many times more deadly than hCoV19 and kills younger people.
This study is not advocating for everyone to acquire immunity through infection, as you seem to think.
On 2021-09-17 10:31:14, user 4qmmt wrote:
Conclusion in Abstract:
Individuals who were both previously infected with SARS-CoV-2 and given a single dose of the vaccine gained additional protection against the Delta variant.
They clarify the meaning of this vague statement at the end of the study::
Notably, individuals who were previously infected with SARS-CoV-2 and given a single dose of the BNT162b2 vaccine gained additional protection against the Delta variant.
Model 3 discussion:
Examining previously infected individuals to those who were both previously infected and received a single dose of the vaccine, we found that the latter group had a significant 0.53-fold (95% CI, 0.3 to 0.92) (Table 4a) decreased risk for reinfection
We conducted a further sub-analysis, compelling the single-dose vaccine to be administered after the positive RT-PCR test. This subset represented 81% of the previously-infected-and-vaccinated study group. When performing this analysis, we found a similar, though not significant, trend of decreased risk of reinfection, with an OR of 0.68 (95% CI, 0.38 to 1.21, P-value=0.188).
Their conclusion in the Abstract and discussion is completely misleading. It is causing people to assume that people with previous infection who are then vaccinated with a single dose are more protected against reinfection. But individuals who were previously infected with SARS-CoV-2 and given a single dose by definition means vaccinating after infection, which they admit in the last quote shown above shows no statistically meaningful benefit.
Even worse, in order to show benefit for previously infected receiving a single dose, they included data for people who were vaccinated before a positive PCR in the cohort. That means that ~ 19% of their data was actually vaccinated who later got infected.
On 2021-10-04 13:50:29, user Steve Vlad wrote:
To the study authors:
As an epidemiologist, if I was reviewing this paper for publication I would send it back to you for major revisions or reject it outright. I would not even bother looking at the results.
The major issue is that you have conditioned study group entry by an event that happens at the end of the study. I.e. you have created a cohort of unvaccinated persons who must remain unvaccinated throughout the study. This is guaranteed to introduce selection bias, more specifically immortal-time bias. This further guarantees a biased estimate. This topic has been written about many times. Cf any of many articles by Sammie Souza at McGill.
Imagine someone in your unvaccinated cohort. Soon after the initial study date they develop an infection. 5 weeks later they have recovered and decided they should have had the vaccine, so they get one. Because you have insisted this group remain vaccine free you throw them out of the group and you lose their data. You have just thrown out an infection. Do this just a few times and it is guaranteed that your ‘vaccinated’ group is not reporting as many infections as it actually experienced. This easily accounts for the effect you report.
Note that this does NOT happen with the fully vaccinated/boosted group who must receive all vaccinations prior to study entry. You capture each and every infection with no drop out. Thus you’ve created a situation where you have non-random drop-out between the groups. That is selection bias.
To get around this problem you MUST use methods such as Cox proportional hazards modeling with time-varying exposure variables so that persons can move between cohorts based on exposure to the vaccine during the study period.
Hope this helps.
On 2021-09-23 16:00:53, user 4qmmt wrote:
The point I'm making is that if there was any significant objective bias in terms of who gets tested if they have no symptoms...that bias would directly impact the outcome of the study and has to be accounted for.
I agree. People with positive PCR and no symptoms does not prove infection. See for example, Asymptomatic transmission of covid-19 https://doi.org/10.1136/bmj... (emphasis mine)
It’s also unclear to what extent people with no symptoms transmit SARS-CoV-2. The only test for live virus is viral culture. PCR and lateral flow tests do not distinguish live virus. No test of infection or infectiousness is currently available for routine use.678 As things stand, a person who tests positive with any kind of test may or may not have an active infection with live virus, and may or may not be infectious.9
If you were to do a similar PCR test and found fragments of other viruses (as we all have), would you consider all those people infected? <br /> https://doi.org/10.1186/s12...
That means that all results of the study may stem from different frequency of testing for infection in vaccinated/recovered populations.
More to your main point - if asymptomatic people can be PCR positive and defined as infected, then everyone who was not tested and did not have symptoms could have been infected also -- likewise -- PCR positive may not be infected. Thus, I agree that the idea of relying on PCR testing without clinical confirmation is very problematic for bias in all directions. They should address that. They have the clinical data.
So why not just focus on clinically confirmed cases? <br /> For example, see this study: https://doi.org/10.1016/j.e...
BTW, The Corona Committee in Israel just published a presentation of their latest research on recovered patients vs. vaccinated here:https://www.gov.il/BlobFold...
They showed patients who recovered between Dec 2020-April 2021 had a 0.43% reinfection rate with 9 (0.0049%) sever cases.
The baseline of persons vaccinated in Feb 2021 was 2.12% infection rate and 0.0132% serious cases.
On 2021-08-28 14:41:37, user RC Cyberwarrior wrote:
I have read comments based on medical studies that individuals who previously had SARS COV2 were 2 -4 times more likely to suffer adverse reactions to the covid vaccines, if vaccinated post initial infection. Some speculate this reaction was related to Antibody-Dependent Enhancement.
On 2021-09-02 09:13:39, user zlmark wrote:
There are several issues with the way the cohort in this study have been formed - the most critical one is the age distribution:
The 60+ group extremely underrepresented - the cohorts contain about 5-6% of people aged 60 and above, whereas they amount to about 31% of the vaccinated people in Israel. And since their own regressions show that the age is a major factor in infectability, such underrepresentation can seriously affect the risk ratio estimates.
On 2021-10-28 14:01:46, user n0b0dy0fn0te wrote:
It absolutely isn't logical that having had COVID is the best defence, for reasons having to do with how the immune system works.
Your immune system, when it meets a new antigen, figuratively throws everything at it to literally see what fits. Any sort of fit to the spike protein will do, even an imperfect one. The benefit the vaccine gives over natural immunity is that it allows the immune system to find the BEST fit for the antigen in question in a safe environment, something that a natural immune response can only achieve as a matter of statistics.
This becomes especially important when dealing with variants, and particularly variants with mutations on the spike protein, because the better the fit to the original variant, the better equipped it is to deal with those tiny mutations in the spike protein as they accumulate, meaning that the controlled environment necessarily gives a statistically better fit against variants as mutations accumulate.
Another important factor is the way the immune system responds. In particular, the way T lymphocytes respond.
So, just the post-it note version of the T-cell response: Your immune system is made up of several components, among which are lymphocytes known T cells. These are white blood cells involved in some responses to foreign bodies. They can replicate really rapidly and differentiate for different purposes. This is good. What's not so good is when it goes wrong. In particular, there are some situations in which the T-cells can into very rapid replication and differentiation, and get a bit out of control. The result is premature apoptosis. Apoptosis is the normal death a cell undergoes when it's fulfilled its function (as an aside, most cancers are a failure of this process; your cells become immortal). The end result of this is a kind of toxic soup, and the T-cells start attacking everything, you included. This, where the immune system starts attacking you, is what we mean by autoimmune.
When your immune system encounters a foreign entity, it throws literally everything at it, including any T-cell it can manufacture. Once your immune system finds a working solution, everything else switches off and production is dedicated to the working antibodies, at which point your T lymphocytes engage in the task of clearing out dead, infected cells.
This means, of course, that the quicker your immune system finds the solution, the quicker T-cell differentiation switches off.
SARS-CoV-2 has now been shown to trigger an autoimmune T-cell response, and it looks not terribly improbable that this accounts for most of the more severe symptoms, particularly cytokine storm driven organ damage.
The problem with thinking something logical when you don't understand the variables from which any premise is derived is that you'll almost always be wrong. In this case, the faulty premise is not understanding the difference between basic immune response versus primed immune response.
On 2021-08-31 22:30:55, user Fully wrote:
Thank you for the interesting and easy-to-understand study - and the clear results: Recovered people are actually much better protected against the now predominant delta variant of Covid-19 and thus less contagious than vaccinated people, even if the infection occurred more than 6 months ago.<br /> Policymakers in Europe, who grant recovered people the same rights as vaccinated people for only 6 months after their infection, should now remove their 6-month rule based on your study results.
Thank you for this from someone who has recovered since one year, who does not want to be vaccinated, because he did well with the disease - me.
On 2021-09-15 08:59:40, user Gralin James Pritchard wrote:
https://patents.google.com/...<br /> "The new corona vaccine contains graphene oxide, carnosine, CpG and new corona virus RBD; binding carnosine, CpG and neocoronavirus RBD on the backbone of graphene oxide.."
A SARS2 vaccine from China does.
On 2021-05-13 15:56:02, user Tatiana Araujo Pereira wrote:
It has been more than one year since the Coronavirus Disease 2019 (COVID-19) outbreak started. We already have effective vaccines around the world, but the imbalance between supply and demand allows Sars-CoV-2 to spread and mutate faster than mass immunization, especially in less developed countries. The arise of more transmissible variants is very worrying and motivates the search for biomarkers that enable early assessment of possible critical cases as well as therapeutic targets for the disease. In this sense Flora et al [1] performed laboratory and proteomic analysis of the plasma sample from a cohort of 163 COVID-19 patients admitted to Bauru State Hospital (São Paulo, Brasil) divided in three groups: “a) patients with mild symptoms that were discharged without admission to an ICU; b) patients with severe symptoms that were discharged after admission to an ICU; c) critical patients, who were admitted to an ICU and died”. The results point to a high concentration of ferritin (FTN) and absence of the IREB2 protein in volunteers exhibiting severe and critical symptoms, indicating that iron homeostasis would be a possible therapeutic target. These results are in line with previous researches, which also identified FTN levels directly related to the severity of the disease [2-5]. Ferritin is an iron reservoir protein, keeping it in its core shell to protect cells against oxidative stress. There are other proteins inhibiting iron redox reactivity in the body, helping with metal ions transport (Transferrin), import to (Divalent Metal Transport) and export from (Ferroportin) the cell [6, 7]. Due to its role in iron homeostasis, FTN is used to indirectly assess iron status in the body. Ordinarily, high levels of FTN mean iron overload [8]. However, circulating ferritin can be elevated independently of iron overload in inflammatory processes, in which it acts as immunosuppressant and proinflamatory modulator [4, 9, 10]. IREB2 is an Iron Regulatory Protein (IRP). When iron levels are low these proteins are able to attach to an untranslated region of mRNA known as Iron Responsive Elements (IRE). Through this mechanism it regulates expression of transferrin receptor and ferritin. In iron overload conditions the affinity of IRP for IRE is not enough to keep the attachment and the protein degrades or takes another role. IREB2 represses ferritin translation when bounded to IRE in FTN-mRNA and degrades in iron overload conditions [6, 11-13].<br /> Because of observed data, Flora et al [1] concluded that “increasing the expression of IREB2 might be a therapeutic possibility to reduce ferritin levels and, in turn, the severity of COVID-19”. Nonetheless, there is no data about iron status in the plasma of the subjects. So it is impossible to be sure whether the high levels of FTN and absence of IREB2 are associated with iron overload. In this case, suppressing ferritin production could culminate in greater oxidative damage, and even increase the risk of opportunistic infections, since intracellular segregation of iron is one of the main strategies to defend host against parasites [14]. In macrophages, this mechanism induces production of nitrogen and oxygen reactive species helping immune defenses [15, 16], but in chronic inflammation it affects iron recycling [17]. Another way to limit iron availability involves its main regulatory hormone hepcidin, which inhibits iron exit from the cell [18]. Hepcidin expression is induced by interleukine-6 (IL-6), which is produced in Sars-CoV-2 infection [19]. Also, Sepehr Ehsani identified a hepcidin mimetic in protein S region that plays a fundamental role in membrane fusion [20]. In this context it is important to verify the possibility that high levels of FTN are not associated with iron overload and only then consider increasing in IREB2 expression as a therapeutic strategy against COVID-19.
AUTHORS<br /> Pereira, T A and Espósito, B P.<br /> Institute of Chemistry – Univesity of São Paulo.
REFERENCES<br /> 1. Flora DC, Valle AD, Pereira HABS. et al. Quantitative plasma proteomics of survivor and non-survivor COVID19 patients admitted to hospital unravels potential prognostic biomarkers and therapeutic targets. MedRxiv; doi: https://doi.org/10.1101/202....<br /> 2. Cavezzi A, Troiani E, Corrao S. COVID-19: hemoglobin, iron, and hypoxia beyond inflammation. A narrative review. Clin Pract. 2020 May 28;10(2):1271.<br /> 3. Bellmann-Weiler R, Lanser L, Barket R, et al. Prevalence and Predictive Value of Anemia and Dysregulated Iron Homeostasis in Patients with COVID-19 Infection. J Clin Med. 2020;9(8):2429.<br /> 4. Colafrancesco S, Alessandri C, Conti F, Priori R. COVID-19 gone bad: A new character in the spectrum of the hyperferritinemic syndrome?. Autoimmun Rev. 2020;19(7):102573.<br /> 5. Perricone C, Bartoloni E, Bursi R et al. COVID-19 as Part of the Hyperferritinemic Syndromes: the Role of Iron Depletion Therapy. Immunologic Research, vol. 68, no. 4, 2020, pp. 213-224.<br /> 6. Halliwell B and Gutteridge JMC. Free Radicals in Biology and Medicine. 4th ed., Oxford: University Press, 2007.<br /> 7. Grotto HZW. Metabolismo do ferro: uma revisão sobre os principais mecanismos envolvidos em sua homeostase. Rev. Bras. Hematol. Hemoter., vol. 30, no 5, 2008, pp. 390-397.<br /> 8. World Health Organization, Centers for Disease Control and Prevention. Assessing the iron status of populations. 2nd ed., World Health Organization, 2007. ISBN: 978 92 4 1596107 (electronic version).<br /> 9. Ruddell RG, Hoang-Le D, Barwood JM et al. Ferritin functions as a proinflammatory cytokine via iron-independent protein kinase C zeta/nuclear factor kappaB-regulated signaling in rat hepatic stellate cells. Hepatology. 2009 Mar;49(3):887-900.<br /> 10. Chen TT, Li L, Chung DH et al. TIM-2 is expressed on B cells and in liver and kidney and is a receptor for H-ferritin endocytosis. J Exp Med. 2005;202(7):955-965.<br /> 11. Kuhn LC and Hentze MW. Coordination of Cellular Iron Metabolism by Post-transcriptional Gene Regulation. J Inorg Biochem, vol. 47, no 3-4, 1992, pp. 183-195.<br /> 12. Schalinske KL, Chen OS, Eisenstein RS. Iron differentially stimulates translation of mitochondrial aconitase and ferritin mRNAs in mammalian cells. Implications for iron regulatory proteins as regulators of mitochondrial citrate utilization. J Biol Chem, vol. 273, no 6, 1998, pp. 3740-3746.<br /> 13. Tong W.-H and Rouault TA. Metabolic Regulation Of Citrate And Iron By Aconitases: Role Of Iron-sulfur Clusters Biogenesis. Biometals, vol. 20, no 3-4, 2007, pp. 549-564.<br /> 14. Gan Z, Tang X, Wan Z et al. Regulation of macrophage iron homeostasis is associated with the localization of bacteria. Metallomics, vol. 11, no 3, 2019, pp. 454-461.<br /> 15. Ratledge C and Dover LG. Iron metabolism in pathogenic bacteria. Annu Rev Microbiol, vol. 54, 2000, pp. 881-941.<br /> 16. Schaible UE and Kaufmann SHE. Iron and microbial infection. Nature Reviews Microbiology, vol. 2, 2004, pp. 946–953.<br /> 17. Castro L, Tórtora V, Mansilla S, Radi R. Aconitases: Non-redox Iron-Sulfur Proteins Sensitive to Reactive Species. Acc Chem Res. 2019 Sep 17;52(9):2609-2619.<br /> 18. Martínez-Pastor M and Puig S. Adaptation to iron deficiency in human pathogenic fungi. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research, vol. 1867, no 10, 2020.<br /> 19. Liu W, Zhang S, Nekhai S, Liu S. Depriving Iron Supply to the Virus Represents a Promising Adjuvant Therapeutic Against Viral Survival [published online ahead of print, 2020 Apr 20]. Curr Clin Microbiol Rep. 2020;1-7.<br /> 20. Ehsani S. Distant sequence similarity between hepcidin and the novel coronavirus spike glycoprotein: a potential hint at the possibility of local iron dysregulation in COVID-19. Biol Direct, vol. 15, 2020, p. 19.
On 2020-12-13 09:54:35, user @nsmartinworld wrote:
This is now infamous as Sweden’s hospitals are at capacity.
On 2022-02-03 17:13:18, user Brian R Wood wrote:
Has the study accounted for the fact that if Omicron has less severe symptoms than Delta or COVID-19 Classic, the number of reported infections is likely to be significantly lower? Additionally, I would speculate that those who got vaccinated and boosted are also more likely to be tested than those who did not, but just speculation, no data to back it up.
On 2021-12-27 00:30:26, user ferkan wrote:
"The negative estimates in the final period arguably suggest different behaviour and/or exposure patterns in the vaccinated and unvaccinated cohorts causing underestimation of the VE. This was likely the result of Omicron spreading rapidly initially through single (super-spreading) events causing many infections among young, vaccinated individuals."
On 2020-04-14 14:03:10, user Chris Pericone wrote:
The death data in table 3 are the reverse of what is described in the results section. I assume the high and low dose columns were mistakenly switched in that table?
On 2020-08-04 08:23:19, user OxImmuno Literature Initiative wrote:
On 2022-01-08 18:02:39, user Eithan Galun wrote:
We are waiting for comments and critics,<br /> Eithan Galun in the name of all authors
On 2020-06-07 21:50:15, user Wei Gu wrote:
Peer reviewed version at Clinical Infectious Diseases:
Clinical Infectious Diseases, ciaa599, https://doi.org/10.1093/cid...<br /> Published: 21 May 2020<br /> https://academic.oup.com/ci...
On 2020-04-18 19:50:29, user Oliver Van Oekelen wrote:
"Raw data will be available in GEO."
When will the data be uploaded? This preprint was posted almost two months ago. Would be amazing to fuel collaborative efforts across the globe and increases the impact of this work...!<br /> Thanks
On 2020-11-19 07:37:44, user Juan Miguel Antón Santos wrote:
I am glad to inform everyone that our paper is already peer-reviewed and published. It now includes information on 15111 patients.
You can find it here:
https://doi.org/10.1016/j.r...
Please cite this article as:
Casas-Rojo JM, Antón-Santos JM, Millán-Núñez-Cortés J, Lumbreras-Bermejo C, Ramos-Rincón JM, Roy-Vallejo E et al.. Clinical characteristics of patients hospitalized with COVID-19 in Spain: results from the SEMI-COVID-19 Registry. Rev Clin Esp. 2020;220:480–494.
On 2021-07-29 08:16:26, user Enzo wrote:
Comparing the rates of severe adverse events such as VTE or TCP between groups of vaccinated people and groups of Covid-19 patients is not likely to be a sufficient way to evaluate risk/benefit ratio. One should take into account that the number of people who get Covid in a year is many-fold smaller than the nummber of people receiving a vaccine jab. (Approx 200 million people got Covid in the world in 20 months, vs 2 billion people who received at least 1 dose, and 4 billion doses already received in 8 months.)<br /> So, even with a 15-fold higher rate of excess VTE/TCP among covid-19 patients than among vaccinated people, if the number of vaccinated people (or jabs) is more than 15-fold higher than the number of covid-19 infections during a given period of time, then vaccination campaigns are to produce more VTE/TCP victims than Covid-19.<br /> ("number of vaccinated people (or jabs)" because if the increased risk linked to vaccines is specific to not yet identified "at risk persons", the number of vaccinated people should be taken into account. If it's inherent to each injection, the number of doses should be taken into account.)
On 2025-09-22 16:17:50, user practiCalfMRI wrote:
The CSF in periventricular spaces and lateral ventricles moves considerably with the pulse pressure wave each heart beat. The edges of these spaces are thus ill-defined (or blurred) over the duration of an 8-sec image with 3-sec labeling period. Given that this is a difference method, I am concerned about a systematic motion difference which may be biasing the results in these regions. I would encourage the authors to either explain how motion cannot produce biases, or present experimental evidence to show that pulsatile motion does not cause inadvertent differences.
On 2020-03-17 23:37:34, user RunningThrough wrote:
Given the study cohort of patients are all hospital admitted patients there in Wuhan, presumably are all in the 'severe' and 'critical' category of all COVID-19 patients per admission policies that we read, so does this present data suggests that the SARS-CoV-2 virus has a higher infectivity amongst blood Gp A patients or that blood Gp A patients are more likely to develop a more severe disease?
On 2020-03-20 15:00:35, user Jane Ford wrote:
What about those of us with blood type B?
On 2020-02-16 21:25:17, user Paul Curto wrote:
You can check this site for daily updates:
https://www.worldometers.in...
The formula which you may use to provide a first-order estimate for <br /> how many deaths daily may occur within a given number of days can be <br /> expressed by:
1.1 raised to the power of the number of days into the future from today, times the current daily death toll
The 1.1 is the ratio of today's death toll divided by yesterday's <br /> death toll as of February 12, 2020. We may use a three day running <br /> average to smooth out the data for spurts of death.
If you use this data and formula, you get over half a million deaths per day within 90 days.
You get over 10 million deaths per day after 120 days.
You get a number in the billions by Thanksgiving.
So much for a seasonal flu. This is a weaponized killer of billions of people.
Since the cat is out of the bag and we still allow cruise ships and <br /> aircraft to use the facilities of over 27 nations outside of China that <br /> have infections, we won't be far behind, at most a few weeks, before we <br /> succumb. Expect a very sad Christmas, indeed.
On 2021-04-14 23:42:50, user fra setch wrote:
What is an anti-spike antibody, exactly. This doesn't match the P2 trials results for Covaxin after 1 dose.
On 2023-01-26 13:02:03, user Jillian Richmond wrote:
Published online in the Journal of Investigative Dermatology https://www.jidonline.org/a...
On 2020-08-24 15:17:19, user vijay_bhatia wrote:
Any human trials for efficacy? There seem to be at least one, unrelated study, that demonstrates safety of using diluted Povidone idodine as nasal rinse. (https://pubmed.ncbi.nlm.nih... "https://pubmed.ncbi.nlm.nih.gov/31560120/)")
On 2021-02-19 10:08:04, user Javier Mancilla-Galindo wrote:
This study is interesting, with robust analyses and a great effort to adequately report the model. Including predictors like S/F ratio, frailty score, and acidosis clearly differentiates this model from others and would make it a highly clinically relevant model. However, I am afraid it may lack any real clinical utility as long as the authors do not clearly explain in a simple way to clinicians how this model should be used in real-world settings (unless I somehow missed it).
Dichotomization of age (i.e. greater than cut-off age) may have led you to loose discrimination ability since too many studies have already shown that age is the main risk factor for mortality in patients with COVID-19. This may, however, not be an issue for such a shot-term (48-hour) mortality prediction, although I do strongly believe this model would have had a better mortality discrimination had you evaluated age differently (i.e. multiple age categories could be included with different weighted risks or coefficients, or perhaps allow age to be inputted as a continuous variable if at all compatible with your model).
The model shown in Supplementary Table 4 that includes CRP and not IL-6 could have a greater potential to be widely used even in moderately resource-strained hospitals. Thus, I found it more useful from a global perspective. Even when the model including IL-6 is better at predicting the outcome, it could have limited clinical applicability as correctly stated in the manuscript.
Lastly, you have adequately reported your manuscript according to the TRIPOD statement. However, the RECORD statement may also apply to this particular study since you have used routinelly-collected data in an observational study design. You could consider including this checklist, too, for the peer-review process.
Congrats for such a great work!
On 2020-09-22 05:48:54, user Jack Zeller wrote:
No zinc? why? what was the outcome for those with covid? How does that compare with outcomes for age, sex, and risk matched.
On 2023-11-16 17:02:09, user Emma wrote:
this paper has now been published: https://substanceabusepolic...
On 2021-03-15 13:11:58, user CHPPM TISS wrote:
A cost effectiveness study on an alternative test (FELUDA) for SARS-CoV-2 in India is published and is available at: https://doi.org/10.1016/j.h.... <br /> The FELUDA test has been approved for use in India by its medical device regulatory body and the private healthcare sector in India has started procuring it from the manufacturers.
On 2021-11-26 03:56:31, user mike wrote:
I's really like to see this study continued until there is say 10 people who have been re-infected or a conclusion to say a million days without re-infection. 75k days is a lot, but they may be much more educated and a significant percent of these people do not want to get the virus a second time, therefore creating a dramatic improvement rate comparatively otherwise.
On 2021-11-20 19:22:50, user John Tyler wrote:
We’re aren’t statisticians. This is meaningless to the masses unless put into layman’s terms. I have no idea if this studies supports or refutes vaccination.
On 2020-04-15 11:04:57, user Dr Eric Grossi Neurocirurgia wrote:
I would like to highlight a serious methodological error in this study. What we want for a drug treatment of COVID-19, only two objectives, to avoid and / or treat SARS and reduce contagion, therefore pragmatism in the selection of patients must be as close as possible to the clinical reality, which did NOT occur, since only patients between the ages of 29.4 to 60 years were analyzed. This alone invalidates any useful result, since the vast majority of human losses are over the age of 64.
On 2021-05-10 14:55:03, user bvwredux wrote:
What is "10 log10"?
On 2020-04-17 19:18:12, user guost wrote:
Do you know what manufacturer uses as an Ag for the primary (capturing) Ab?
On 2020-04-22 18:49:47, user endmathabusenow wrote:
There is no corroboration of this study. The ratio of known to unknown cases is location specific and a function of how many people have been tested. The mortality rate itself is a function of the age and health of the population. Furthermore in calculating the mortality rate these authors don't consider the likelihood that if there were hidden cases in the past that there were deaths not counted as COVID. Even 2 years after the 2009 H1N1 epidemic, the uncertainty range in the number of deaths attributed to the flu had a huge uncertainty range: about 9,000-18,000
On 2020-04-18 19:04:21, user Flowin Motionly wrote:
What do you mean ? if 70% of a population have a virus, the virus can hardly be transmitted. Air-travel is not going to change significantly the proportion of the population having the virus.
On 2020-04-22 20:36:24, user Konstantin Momot wrote:
The crucial issue here is sample selection. The participants essentially self-selected, but that is a potential source of huge bias. As a hypothetical scenario, if the people who chose to participate were predominantly people who’d had a cold and were curious to find out if it was COVID, then the cohort would a priori be hugely overweight with people who had a higher-than-average likelihood of COVID exposure. That would not be a good sample of the general population in that it would not represent the true percentage of CoV-exposed and CoV-naive people in the population as a whole. That would mean that the 2-4% figure is completely meaningless. Given how crucial this number is to any epidemiological modelling, I think it's important to remember that this is just one study with no guarantee of flawless methodology, and avoid making far-fetched conclusions based on limited evidence.
On 2020-04-28 23:54:02, user Sun Wu Kong wrote:
Your first point is misleading. https://premierbiotech.com/...
As for your second point, this would not have been an unreasonable assertion circa the beginning of the study. https://www.theguardian.com...
On 2020-04-26 10:07:32, user Guy Gadboit wrote:
You have to account for when the test was done and how long it takes for antibodies to appear.
If it takes 4 weeks for antibodies to appear (and 3 weeks to die) you get an IFR of about 0.45%. But if it takes 5 weeks for antibodies to appear, you get about half that (because a week earlier they had half the number of deaths).
As someone pointed out the population fatality ratio in NYC is about 0.12% so this is an upper bound.
The IFR doesn't have to be the same everywhere-- it will depend a lot on the age and comorbidity of the population-- but it looks like it's somewhere between 0.2% and 0.5%.
If you look at data from Iceland, there's no way IFR is 0.85% there. They have 1960 confirmed recovered/infected based on lots of tests, 10 deaths and 4 in the ICU. That's a CFR of 0.7%. But of course they didn't test the whole population, so this is way higher than the IFR.
On 2020-04-20 02:47:08, user Comfrey's Gone wrote:
Probably related to Dean Karlen's observations below - but in working through the statistical appendix, it seems like the calculation of the standard error is independent of the number of samples (371 or 401) used by the manufacturer/Stanford team to evaluate the number of false positives.
To determine the standard error, the authors first compute the cumulative variance by combining variances from each source of uncertainty (finite sample of respondents of 3,330, finite sample for false positives in the serology test and finite sample for false negatives). These separate variances are the variances of the binomial distribution (p(1-p)), not rescaled by the inverse of the sample size. The authors then take this cumulative variance and divide by the number of respondents (3,330), and apply the square root to arrive at the standard error. (.0039 = sqrt(.034/3330)).
Instead, when the cumulative variance is computed in the equation for Var(Pi) above, I believe that each of the contributing terms should be multiplied by its appropriate 1/N (where N is the relevant sample size, e.g. 3,330 for the Var(q) term, and 371 or 401 for the Var(s) term.)
One way to assess that the 'N' rescaling doesn't seem right is to think about the limit in which the number of respondents being tested is infinite, the sample size for determining the number of false negatives is also infinite, but there is a finite sample (e.g. 401) used to determine the number of false positives. If you trace through the appendix calculation, you'll then find (if I've done it correctly) that the standard error for 'Pi' (the infection rate) would then be zero, although some error certainly should exist, due to the uncertainty in false positives.
Other commenters have also raised concerns about the normality assumption in computing the standard error, but the way in which scaling by sqrt(N) has been applied here has a large impact on the calculation of the standard error and resulting confidence intervals.
On 2020-04-20 10:50:57, user Douglas Gilliland wrote:
Peer review rejects this study... https://medium.com/@balajis...
On 2020-04-20 07:07:53, user clever trevor wrote:
The Achilles heel of this study is the specificity of the serology test.
On the manufacturer's own data, they tested 371 blood samples stored from the pre-COVID era, and got 2 false-positives.
False positives are real problem on population testing. if on that crude data they over-estimate the prevalence of sero-positivity by 0.66%points, that throws the whole calculation into doubt.
the authors did their own testing for specificity, but on only 30 samples, and, inexplicably, those 30 samples were from hip-surgery patients. Hip surgery patients tend to be old, *and* therefore they tend to have generally lower circulating levels of immunoglobulin,
https://www.ncbi.nlm.nih.go...
so a cohort of hip-surgery patients is *the wrong group* to look at if you want to stress-test the specificity of your assay.
This study needs to be repeated with much stronger specificity evidence in the assay.
On 2020-05-01 17:34:20, user Leonid Schneider wrote:
The IRB approval TJ-C20200113 is connected to this clinical trial:<br /> http://www.chictr.org.cn/sh...<br /> "A randomized, open-label, blank-controlled, multicenter trial for Shuang-Huang-Lian oral solution in the treatment of ovel coronavirus pneumonia (COVID-19)"
It is about Traditional Chinese Medicine (TCM) and never mentions chloroquine or other drugs in the preprint, which in turn never mentions TCM. The registered trial had only 400 patients. The study above had 568 patients.
On 2019-10-18 23:18:45, user GuyguyKabundi Tshima wrote:
EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AS AT OCTOBER 16, 2019<br /> Thursday, October 17, 2019<br /> Since the beginning of the epidemic, the cumulative number of cases is 3,228, of which 3,144 are confirmed and 114 are probable. In total, there were 2,158 deaths (2044 confirmed and 114 probable) and 1038 people healed.<br /> 443 suspected cases under investigation;<br /> 1 new confirmed case in North Kivu, including:<br /> 1 case in North Kivu in Mabalako;<br /> No cases in Ituri;<br /> 4 new confirmed deaths in North Kivu, including:<br /> 1 community death in North Kivu in Mabalako;<br /> 3 deaths confirmed at CTE in North Kivu in Mabalako;<br /> No healed person left CTE;<br /> No health workers are among the newly confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths.
LEXICON<br /> • A community death is any death that occurs outside a #Ebola Treatment Center.<br /> • A probable case is a death for which it was not possible to obtain biological samples for confirmation in the laboratory but where the investigations revealed an epidemiological link with a confirmed or probable case.
NEWS<br /> NOTHING TO REPORT
VACCINATION<br /> - A satellite ring was opened in Mambasa prison around the confirmed case of 12 October 2019 in Nyakunde;<br /> - Continuation of expanded ring vaccination in Mataba in the health zone of Kalunguta around the 2 confirmed cases of 12 October 2019;<br /> - Continuation of the vaccination of newly recruited front-line staff (PPL) in the Kyondo (HGR Kyondo) and Kayna Health Zones (Bulinda Health Area), Musienene (Kimbulu Reference Health Center) and Butembo (Vulindi Health Area);<br /> - Preparation of the vaccination of biker taximen in the sub-coordinations of Butembo, Beni, Mangina in Mabalako in North Kivu and Mambasa in Ituri.<br /> - Since the beginning of vaccination on August 8, 2018, 239,139 people have been vaccinated;<br /> - The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.
MONITORING AT ENTRY POINTS<br /> - Nasty destruction of huts and launching leaflets against providers at PoC Kolikoko;<br /> - Since the beginning of the epidemic, the total number of checked travelers (temperature rise) at the sanitary control points is 106,999,606 ;<br /> - To date, a total of 111 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 2019-11-30 16:39:58, user Guyguy wrote:
EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT NOVEMBER 26, 2019<br /> Wednesday, November 27, 2019<br /> • Since the beginning of the epidemic, the cumulative number of cases is 3,304, of which 3,186 are confirmed and 118 are probable. In total, there were 2,199 deaths (2081 confirmed and 118 probable) and 1077 people cured.<br /> • 366 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
Closure of training of Ebola Rapid Response Teams in Goma
• The Ebola response coordinator for the Ebola response to operations, Dr. Luigino Mikulu, closed on Wednesday 27 November 2019 the training of Rapid Response Teams (RRTs), composed of units of the Armed Forces. (FARDC) and the Congolese National Police (PNC), on the Ebola virus disease that took place in Goma, capital of North Kivu Province from 22 to 26 November 2019;<br /> • For Dr. Luigino, this team is the first in the Rapid Response Teams to be composed of elements from other sectors, such as those of the Ministries of Defense and Security and the Ministry of the Interior;<br /> • This training aligns with the vision of the Technical Secretariat of the Multisectoral Ebola Virus Disease Response Committee (ST / CMRE), through the overall coordination of the response, to expand its mixed and multidisciplinary teams available and able to intervene 24 hours a day, 7 days a week and everywhere, where they will be deployed, not only for the response to this epidemic to Ebola Virus Disease, but also for other epidemics;<br /> • This training was a pride for WHO to accompany the Ministry of Health in order to capitalize the capacity building of FARDC and PNC units in public health;<br /> • The participants, in turn, reassured the overall coordination of the response, the Ministry of Health and all those who contributed to the delivery of this training, particularly to WHO and all facilitators, to be faithful disciples in the field by putting into practice all the notions learned during these sessions;<br /> • At the end of this training, the thirty participants, including the facilitators, received a participation certificate.
VACCINATION
• Despite the tense situation of the city of Beni, a vaccination ring was opened around the confirmed case of 24 October 2019 in the Kanzulinzuli Health Area of the General Reference Hospital;<br /> • 724 people were vaccinated, until Tuesday, November 26, 2019, with the 2nd Ad26.ZEBOV / MVA-BN-Filo vaccine (Johnson & Johnson) in the two health zones of Karisimbi in Goma;<br /> • Since the start of vaccination on August 8, 2018 with the rVSV-ZEBOV vaccine, 255,247 people have been 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 towns of Beni and Butembo in North Kivu province following demonstrations by the population which decries killings of civilians;<br /> • Since the beginning of the epidemic, the total number of travelers checked (temperature measurement ) at the sanitary control points is 121,159,810 ;<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 2019-08-03 19:22:31, user GuyguyKabundi Tshima wrote:
Dear all, here is the daily bulletin on the evolution of the response to the Ebola Virus Disease outbreak of 01 August 2019. The field information verification process has been more painful because of the sensitivity of the events on the ground. .<br /> Please be indulgent for the delay.
EVOLUTION OF THE EBOLA EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI
Thursday, August 01, 2019
Epidemiological Status of Ebola Virus Disease as of 31 July 2019
Since the beginning of the epidemic, the cumulative number of cases is 2,713, of which 2,619 confirmed and 94 probable. In total, there were 1,823 deaths (1,729 confirmed and 94 probable) and 782 people healed.<br /> 423 suspected cases under investigation;<br /> 13 new confirmed cases, including 5 in Beni, 2 in Mabalako, 2 in Mandima, 1 in Nyiragongo (Goma), 1 in Vuhovi, 1 in Katwa and 1 in Mutwanga;<br /> 10 new confirmed cases deaths:<br /> 2 community deaths, including 1 in Beni and 1 in Mandima;<br /> 7 Ebola Treatment Center (ETC) deaths, including 3 in Beni, 2 in Mabalako, 1 in Komanda and 1 in Goma;<br /> 1 death at the ETC of Beni;<br /> 6 people cured out of ETC, including 5 in Beni and 1 in Katwa;<br /> One health worker, living and vaccinated, is among the new confirmed cases in Beni. The cumulative number of confirmed / probable cases among health workers is 149 (5% of all confirmed / probable cases), including 41 deaths.
NEWS
As a reminder, the recommendations of the Ministry of Health are as follows:<br /> Follow basic hygiene practices, including regular hand washing with soap and water or ashes;<br /> If an acquaintance from an epidemic area comes to visit you and is ill, do not touch her and call the North Kivu civil protection hotline directly;<br /> If you are identified as an Ebola patient contact, agree to be vaccinated and followed for 21 days;<br /> If a person dies because of Ebola, follow the rules for safe and dignified burials. It is simply a funeral method that respects funerary customs and traditions while protecting the family and community from Ebola contamination.<br /> For all health professionals, observe the hygiene measures in the health centers and declare any patient with symptoms of Ebola (fever, diarrhea, vomiting, fatigue, anorexia, bleeding).<br /> If all citizens respect the sanitary measures recommended by the Ministry of Health, it is possible to ensure that this case of Ebola detected in Goma is only a sporadic case that does not cause a new outbreak.
Follow-up of the situation of contacts of the second case confirmed Ebola of Goma<br /> 151 contacts have been reported around the 2nd confirmed case of EVD in Goma since 22 July 2019. Among these contacts, 118 have already been vaccinated, including 70 at high risk (CHR) and 48 contact contacts (CC);<br /> The girl and the woman of this case of Goma constitute to date the 3rd and 4th positive cases of EVD recorded in Goma;<br /> The sister of this same case, who fled to the province of South Kivu, was found in Biara in the health zone of Muti Muresa. 40 contacts have already been vaccinated around this contact this Thursday, August 1, 2019, including 9 high-risk contacts and 31 contacts.
A traditional healer among the confirmed cases of Mabalako<br /> This is a 25 year old man, living and vaccinated on July 20, 2019 (geographical vaccination). He practiced self-medication on July 24-29, 2019 with a gradual worsening of symptoms.
It was taken to the CTE after validation on July 30, 2019 after the alert launched by a Community Relay (ReCo). It was confirmed MVE on July 31, 2019. 22 contact persons are listed around this case, whose investigations are ongoing.<br /> The confirmed case of Lubero on the run<br /> The confirmed case of July 25, 2019 in Lubero Health Zone (ZS), who fled into the community, is reported to be in Lukanga in the Masereka SZ, 17 km from Lubero. A team went there on Thursday, August 1st, 2019 for its transfer to CTE.
80,481,013<br /> Controlled people<br /> 98 entry points (PoE) and operational sanitary control points (PoC).
149<br /> Contaminated health workers<br /> 1 health workers, living and vaccinated, are among the new confirmed cases of Beni.<br /> The cumulative number of confirmed / probable cases among health workers is 149 (5% of all confirmed / probable cases) including 41 deaths.
Source: The press team of the Ministry of Health.
On 2019-11-13 01:31:13, user Guyguy wrote:
EVOLUTION OF THE EPIDEMIC IN THE PROVINCES OF NORTH KIVU AND ITURI AT NOVEMBER 11, 2019
Tuesday, November 12, 2019<br /> • Since the beginning of the epidemic, the cumulative number of cases is 3,287, of which 3,169 confirmed and 118 probable. In total, there were 2,193 deaths (2075 confirmed and 118 probable) and 1067 people cured.<br /> • 545 suspected cases under investigation;<br /> • No new confirmed cases;<br /> • No new deaths of confirmed cases have been recorded;<br /> • No cured person has emerged from ETCs;<br /> • No health worker is among the new confirmed cases. The cumulative number of confirmed / probable cases among health workers is 161 (5% of all confirmed / probable cases), including 41 deaths;
NEWS
Organization of a press conference in Goma on the introduction of the second Ebola vaccine in the Democratic Republic of Congo
• The coordination of the epidemic response to Ebola Virus Disease organized this Tuesday, November 12, 2019, jointly with the International Non-governmental Organization Médecins Sans Frontières of France (MSF / France), a press conference on introduction of the second Ebola vaccine, Johnson & Johnson, at the Karibu Hotel in Goma, capital of North Kivu Province;<br /> • During this press conference, the coordinator of the response, Prof. Steve Ahuka Mundeke, announced that vaccination with this second vaccine will start on Thursday, November 14, 2019 in two health areas of Karisimbi in Goma, including Majengo and Kahembe. The beginning of the vaccination will thus precede the official launch of the introduction of this vaccine which will intervene in the days to come;<br /> • This vaccine will be administered intramuscularly in two doses with an interval of 56 days. It targets adults and children over twelve months old. It has a strong immune response and its dose has the advantage of increasing this response by making it more sustainable in order to protect populations against a possible Ebola outbreak, according to a member of the consortium that took care of the study of this vaccine, Dr Hugo Kavunga, project manager INRB, member of the consortium;<br /> • Everyone is eligible for this vaccine, including children over the age of one, even pregnant and lactating women. In addition, for women of childbearing age, they will be offered a pregnancy test. Those who do not want it, will always be vaccinated. Pregnant women will be followed, said Vaccine Project Coordinator at MSF / France, Dr Véronique Urbaniak;<br /> • The choice of vaccination site was made after several studies and it is in order to protect the population against possible epidemics that Majengo and Kahembe were selected;<br /> • The vaccine is called Ad26.Zebov / MVA-BN-Filo. It is of Belgian-American origin and is named Johnson and Johnson. It has already been used in Sierra Leone in West Africa, Uganda and soon Rwanda. This second vaccine complements the first in-use vaccine in belt strategy and has already saved more than 3,000 people to date;<br /> • In addition to the speakers, two other members of the consortium took part in the press conference, including the London Shool Project Investigator Dr. Dan Baush and the Epicenter's Immunization Coordinator Marie Burton.
VACCINATION
• Preparation of the launch of the 2nd Ebola vaccine, J & J in Kahembe and Majengo Health Areas in Karisimbi, Goma, North Kivu;<br /> • 37 participants, including 4 high-risk contacts, 6 contacts, 7 CPs and 20 front-line staff, were vaccinated from the confirmed case of 09 November 2019 in the Bingo Health Area in Mabalako, North Kivu;<br /> • Since vaccination began on August 8, 2018, 250,622 people have been vaccinated;<br /> • The only vaccine to be used in this outbreak is the rVSV-ZEBOV vaccine, manufactured by the pharmaceutical group Merck, following approval by the Ethics Committee in its decision of 20 May 2018.
MONITORING AT ENTRY POINTS
• Disruption of activities at PoC VIRENDI (SC BUTEMBO) following clashes between FARDC soldiers and incivists not otherwise identified.<br /> • Since the beginning of the epidemic, the total number of travelers checked (temperature rise) at the sanitary control points is 116,184,525 ;<br /> • To date, a total of 111 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 2024-07-31 10:58:02, user Vincent THIBAULT wrote:
With all my respect, it is unfortunate that the authors did not take into account our remarks regarding the use of the quantitative HBcrAg assay https://www.journal-of-hepatology.eu/article/S0168-8278(23)00232-5/fulltext . By not complying to the manufacturer's instructions they promote the publication of inaccurate data. This is not how to improve science quality.
On 2020-06-04 00:53:02, user Bruce Zweig wrote:
The sentence ‘Our findings showed that only 4.22% of the overall population received 5ARI anti-androgen therapy’ should say ‘male patient population’ instead of ‘overall population.’
On 2020-04-24 14:35:40, user VirusWar wrote:
Interesting study. some comments :<br /> 1. The increase of QTc can be due as well to renal diseases due to COVID19, Such renal diseases were pointed in this study "The QT Interval in Patients with SARS-CoV-2 Infection Treated with Hydroxychloroquine/Azithromycin" https://www.medrxiv.org/con...<br /> Renal diseases cause big levels of Potassium in the blood and increase QTc, so the level of Potassium should be checked as well, especially when QTc>=460 ms. If level of Potassium is high, action can taken (like treat renal disease, eat less Potassium, extra magnesium given). In some cases (QTc >460 ms and QTc<500ms), risk seems manageable. <br /> 2. There is no point to use hydroxychloroquine for severe patients. It takes 3 days to have effect on early stage, in combination with azithromycine. For severe patients, there are usually not much virus left but big damages, so it is too late to give hydroxychloroquine.
On 2020-04-18 21:54:04, user Jim Trader wrote:
Kind of a useless study. With an average delay of 16 days from symptom onset to enrollment and treatment in this trial, those patients are pretty much past the viral phase of the disease, where an antiviral treatment would have the most value, and are well on their way to pneumonia and a cytokine storm problem, which is ultimately what kills. Even the subset analysis of patients with a 7 day delay from symptoms to enrollment is still too long. As the authors state, it is very difficult to do these kinds of trials when patients average 12 days from symptoms before they come into the hospital, and can be explored as trial participants. So unfortunately there is no signal here, and from a molecular biology viewpoint, that is exactly what I would expect with this trial design. HCQ therapy needs to start within 48 hrs of symptom onset, ideally 24.
On 2021-11-29 13:12:04, user HarryT wrote:
Another research shows current vaccines induce excellent immunity against all variants, most likely include Omicron. Just get vaccinated.
On 2021-01-31 03:17:24, user Seyed Moghadas wrote:
It is now published in Clinical Infectious Diseases
On 2021-08-31 03:11:22, user Judy Friend wrote:
when will this report be fully peer reviewed and when will we have more information. also how often are variants actually coded in these countries for genome sequencing
On 2020-05-13 13:19:20, user T Christopher Bond wrote:
Looking for an explanation of the total numbers and the comparator group in Table 4 (ICI vs ?).
On 2020-05-21 04:05:54, user David Ackerman wrote:
The counterfactual simulation data on early intervention as in 1-2 weeks earlier implementation of Social Distancing are quite telling yet I have to wonder if there is also data available on interventions even earlier. What if measures such as masks, distancing, sanitizing & hand washing had been ADVISED by CDC as early as 2/1/2020? I would be most interested at viewing those numerical hypotheses. Thanks again, and God bless.
On 2021-08-19 15:59:30, user Dan Miller wrote:
Where is table 4 ?
On 2021-07-29 20:45:15, user Robert Earnest wrote:
So why are they recommending a booster?
On 2020-08-13 21:33:27, user AlvaroFdez wrote:
It would be interesting to clarify if during (or even before) the sampling periods, the patients used the toilet, given the potential particle aerosolization originating via flushing.
On 2021-04-25 17:39:35, user Mikko Heikkilä wrote:
There are multiple errors in this systematic review and meta-analysis that have been reported to the authors already once the second version was published December 2nd 2020 and they have not been corrected to the third version either.
The intervention group total for the Aiello et al. 2010 paper is 663 and not 745 thus changing also the Relative Risk for that RCT.<br /> The third version has the mask and mask+hand hygiene groups separated but the numbers are still wrong. Aiello et al. subtracted the cases with previous symptoms so that the correct totals are 316 (367 in Ollila et al.) and 347 (378 Ollila et al.).<br /> The RRs for
On 2022-01-22 06:24:07, user Concerned Citizen wrote:
Is there any further data for after 0ct 21 so a comparison can be made with Omicron? Thanks
On 2020-05-10 12:03:31, user Zn2 plus wrote:
This preprint is now published : https://doi.org/10.3390/bio...
On 2021-01-05 07:56:40, user Rita Pizzi wrote:
previous researches
Ghate VS, Ng KS, Zhou W, Yang H, Khoo GH, Yoon WB, Yuk HG.
“Antibacterial effect of light emitting diodes of visible wavelengths on
selected foodborne pathogens at different illumination temperatures.”
International Journal of Food Microbiology. 166 (2013) 399.
Ghate VS, Leong AL, Kumar A, Bang WS, Zhou W, Yuk HG. “Enhancing the
antibacterial effect of 461 and 521 nm light emitting diodes on selected
foodborne pathogens in trypticase soy broth by acidic and alkaline pH
conditions” Food Microbiology. 48 (2015) 49.
Ghate, V, A Kumar, W Zhou and HG Yuk. 2015. Effect of organic acids
on the photodynamic inactivation of selected foodborne pathogens using
461 nm LEDs. Food Control 57:333–340.
Vaitonis and Ž. Lukšiene – Institute of Applied Research, Vilnius
University, Saul?etekio 10, LT-10223 Vilnius, Lithuania “Led-based light
sources for decontamination of food: modelling photosensitization-based
inactivation of pathogenic bacteria” Lithuanian Journal of Physics,
Vol. 50, No. 1, pp. 141–145 (2010)
http://www.lmaleidykla.lt/p...
Nicolai Ondrusch, Jürgen Kreft “Blue and Red Light Modulates
SigB-Dependent Gene Transcription, Swimming Motility and Invasiveness in
Listeria monocytogenes” Published: January 11, 2011DOI:
10.1371/journal.pone.0016151
On 2021-07-29 17:01:13, user Jodi Schneider wrote:
An Israeli study of healthcare workers published in NEJM says "Most breakthrough cases were mild or asymptomatic, although 19% had persistent symptoms (>6 weeks)." http://doi.org/10.1056/NEJM...
On 2021-11-15 08:53:39, user kdrl nakle wrote:
Very high HR, I am really surprised.
On 2021-08-17 09:28:07, user One bird one cup wrote:
"Additionally, we assume the survey was completed in good faith." .... The assumption is what bothers me here. The people responding to a survey on Facebook aren't necessarily representative, as they're self-selected. This does not inspire confidence. Who's to say the respondents answered honestly about their education level? In addition -- apparently those who live in communities who were largely for Trump in 2020 appear to have been more vax-hesitant. I'm not a statistics person so I can't judge how the authors adjusted for this. But I feel hinky about it.
On 2021-04-09 12:25:07, user Keish Gonzalez Acosta wrote:
Hi. I am a breastfeeding mother. I took the JJ vaccine 4 days ago. I am pumping milk. If your team is interested in collecting milk samples after JJ vaccine I would like to participate.
On 2024-02-16 08:02:55, user Jiazheng Miao wrote:
This manuscript has been published on Scientific Reports. Please access the latest published version.
Miao, J., Ling, Y., Chen, X. et al. Assessing the nonlinear association of environmental factors with antibiotic resistance genes (ARGs) in the Yangtze River Mouth, China. Sci Rep 13, 20367 (2023). https://doi.org/10.1038/s41...
On 2021-07-03 04:25:21, user Sumedh Bhagwat wrote:
COVAXIN preprint says: (Protocol, Supplementary appendix 2) but there is just a single supplementary file which is not the protocol .<br /> Please attach Supplementary appendix 2.
Actual Vaccine Efficacy against symptomatic Covid when calculated using formula is 77.27% ~77.3%<br /> Paper reports 77.8% which is due to rounding off of fractions
On 2020-05-14 15:34:13, user Neil Blumberg wrote:
Some suggested additional analyses. Compare results in recipients of ABO identical versus ABO compatible plasma. ABO compatible is associated in observational studies with increases in ARDS, sepsis, bleeding and mortality, as compared with ABO identical. Report incidence of thrombosis post-infusions (perhaps at 7 days). Allogeneic plasma is pro-inflammatory for innate immunity and immunosuppressive for T cell immunity, and these may well predispose to thrombosis and sepsis. If progressive SOFA or other scores are available, these would also be helpful. Big ask, I know :).
On 2021-11-26 12:38:36, user Richard Hockey wrote:
It would be interesting to repeat this in other Australian cities that had very limited lockdown and very few Covid cases such as Brisbane or Perth.
On 2025-03-10 13:27:10, user Feng Gu wrote:
Hi, Please check the published version here: https://www.doi.org/10.1038/s41746-025-01501-9
On 2022-02-11 20:36:21, user Lou Edi wrote:
I'm not sure how the conclusions follow. The study does not research incidence of infections among the groups, after all. It researches the incidence of false alarms.
This is worsened by the exclusion criteria. Self-tested positives get excluded, and may then be counted as negative subjects if they had another test. Fervent testers get a lot of false alarms. While hesitant testers (i.e. tests when they had a close contact and got sick) get high positive rates.<br /> Since these behaviors likely correlate to some extent with vaccine uptake and previous infection, this needs to be accounted for.
Additional distortion: by the criteria, someone who got sick before and after the booster, only gets his unboosted positive counted (presumably rare, but most significant).<br /> While someone who got negatively tested before and after the booster, only gets his boosted negatve counted.
Note on the conclusion: waning effects, both for infection and severity, need to be mentioned. However for this, countries that boosted early will be the main indicators. Same for the results of a 2nd booster.
On 2020-05-08 05:56:07, user Masfin Otta wrote:
Obviously, the conclusion of the paper was dead wrong: the covid-19 outbreak in Okinawa had already been completely suppressed without stringent stay-home measures by 28 April and we are not seeing 20,000 deaths but only 5 so far. Perhaps, the total number of the cases was not on the exponential line, particularly after the middle of April, 2-3 weeks after the start of the outbreak as Professor Michael Levitt of Stanford observed from the outbreaks of China, Italy and Iran. Another discussion may be that Rt might have been much lower than assumed and the outbreak died out without many new cases imported from the mainland or perhaps Europe and North America where the epidemic is much much severe than the mainland.
On 2021-12-22 16:54:13, user AndyUpNorth wrote:
Could there be a control population who were hospitalized for anything but COVID in order to rule out convalescence?
On 2020-05-23 12:34:51, user James Lesther wrote:
An interesting review on the Stanford v Stanford debate about the IFR: https://www.linkedin.com/po...
On 2020-06-17 20:11:26, user LB wrote:
Zotero (a popular citation manager) says that this article has been retracted. If this is not the case, please ask Retraction Watch to correct the error.
On 2020-11-06 09:08:27, user Maksim wrote:
This is a nice point. “ plasma levels of total catechins are at submicromolar level, which is below the effective dose in many in vitro studies, tissue dispositions could be much higher “ (DOI: 10.5772/intechopen.74190). Besides, in the throat (during tea consumption) catechins levels could be much higher, though for a short period of time. (The latter is just a speculative idea to think about).
On 2020-11-09 00:43:51, user Antonio Gasparrini wrote:
The article is now published in the International Journal of Epidemiology.<br /> You can access the full-text for free at:<br /> https://academic.oup.com/ij...<br /> http://www.ag-myresearch.co...
On 2021-01-08 15:40:35, user lbaustin wrote:
Nicely done! I especially appreciate the fact that the JBI's standards were used to determine that the studies were at low risk for bias.
I am looking forward to seeing this published in a MEDLINE indexed journal so that it can easily be picked up by other researchers.
On 2021-03-21 03:04:06, user Rick Shalvoy wrote:
Very encouraging data. This appears to be the textbook definition of a successful screening tool. Now that the U.S. FDA has finally released a template for device developers to use for EUA submissions when the developer is seeking to obtain a screening authorization, FDA authorization for OTC use of any properly validated device that screens for olfactory dysfunction should, and hopefully will, be granted relative soon after submission.
On 2025-04-10 17:31:51, user SMR Hashemian wrote:
At the peak of the COVID-19 crisis, when the world was gripped by fear and despair, Iran was not only battling a deadly virus but also grappling with brutal and inhumane sanctions. Economic sanctions severely restricted Iran's access to medicine, medical equipment, and vaccines, creating one of the biggest obstacles in the fight against this crisis. Yet, despite these unprecedented pressures, Iran did not surrender and, through relentless efforts, found ways to overcome these limitations.<br /> The Iranian government made every effort to bypass the sanctions through international negotiations and the creation of alternative financial channels to import the necessary medicines and equipment. These efforts, though fraught with difficulties, demonstrated Iran's resolve to save lives. Even as many countries refused to assist Iran, the nation relied on domestic capabilities and national solidarity to find solutions to the crisis.<br /> Amidst these challenges, Iran's healthcare workers stood on the front lines like unsung soldiers, making unparalleled sacrifices. Doctors, nurses, and all healthcare workers in hospitals not only played a critical role in saving countless lives but also faced significant personal risks, with many losing their lives in the process. These dedicated professionals demonstrated extraordinary commitment and selflessness, setting an example of resilience and dedication in the face of a global health crisis.<br /> But it was not just the healthcare workers who fought in this battle. Iran's scientific community also stepped up with full force. Iranian scientists and researchers, despite cruel sanctions and countless limitations, never stopped striving. They not only succeeded in producing domestic vaccines like Noora and SpikoGen, but also published numerous articles in prestigious international journals, showcasing Iran's role in advancing global science. These efforts are a testament to the fact that Iran, even under the toughest conditions, can rely on science and knowledge.<br /> The Iranian government, despite all limitations, spared no effort in controlling this crisis. From the very beginning, extensive education on health protocols was launched through the media. The public was continuously informed about health recommendations such as mask-wearing, social distancing, and hand hygiene. Even during Nowruz, one of the most important cultural events in Iran, the government encouraged people to reduce travel and celebrate at home. School and university closures, the shift to remote learning, and the reduction of workplace presence through teleworking all demonstrated the government's resolve to control the spread of the virus.<br /> These efforts, though accompanied by challenges, reflect Iran's national determination to confront this global crisis. Iran, despite all limitations, proved that it could stand firm against the toughest conditions by relying on science, sacrifice, and national solidarity. The accusations raised in this article are not only unfair but also overlook the relentless efforts of a nation. Iran fought with all its might to save lives, and that is something to be proud of.
Seyed MohammadReza Hashemian<br /> Professor of Critical Care Medicine
On 2021-08-02 17:30:40, user Jeremy wrote:
Wow, this study is pure garbage.
Half of the study's age demographic couldn't even be vaccinated during the duration of the study since approval for 12-15 year olds came after it had ended. Not to mention that the other half only had the vaccine available for 25% of the study duration.
On 2024-03-18 13:01:53, user Varsha Gouthamchand wrote:
Follow the link https://doi.org/10.1093/bjr... for an extended and published version of this article.
On 2020-03-17 19:53:18, user B. Lee Drake wrote:
Did the authors do any cross-validation? Machine learning should always have a data-split of 10-30% to evaluate the models generalizability. This is important and immediately consequential work - very much need to see some detail on how these models performed - it is not clear from the paper itself.
On 2021-10-09 10:12:17, user Nick Turnock wrote:
How does your modelling take into account the incubation period. For instance Delta's reported increased viral load without epitope change may indicate immune response evasion by shortening the incubation period. ie increased population seropositivity may have driven a mutation which enables Delta to rapidly multiply, shed and infect new hosts in the short window before memory B cells start churning out antibodies.
On 2021-02-21 19:05:04, user hugh_osmond wrote:
The assumptions regarding vaccine administration are already out of date, with the program well ahead of that assumed; this makes a very significant difference to outcomes. Take up rates amongst most vulnerable groups are also ahead of those assumed. Data suggest that just one dose reduces likelihood of hospitalisation by close to 100% (after two weeks) so assumption that 40% of deaths will still occur amongst those vaccinated appears ludicrously pessimistic. The study seems to take no account of those who are resistant/immune following infection (c. 15 million in UK), which will combine with number immune through vaccination to significantly reduce R. The fatality rate assumed amongst those infected in subsequent waves appears significantly higher than currently being experienced amongst the relevant age groups and certainly appears to take no account of improvements in treatments and newly available drugs. We now have better data on the effectiveness of the vaccines at preventing transmission, so the lower estimates in the study can be disregarded. The study also takes no account of the known seasonal effects, as seen last year after lockdown was released.
The combination of all the above suggests that the likely outcomes will be approximately 1/10-1/20 of those calculated, making the conclusions of limited relevance.
On 2021-09-01 21:33:26, user Paul wrote:
In reviewing your study's hospitalization rates by age group (your Figures 3 A, B and C), it shows that peak hospitalization rates per 100k in the unvaccinated population to be at about 12-13 for ages 18-49; about 35-40 for ages 50-64; and about 80-90 for ages 65+. These peaks happed mid to late April.
The hospitalization rates by age group during the worst peak of COVID in late December 2020, before the vaccines were available, were as follows (per the CDC COVID-NET data, week ending 1/9/21): 9.6 for ages 18-49; 28.4 for ages 50-64; and 71.9 for ages 65+.
Under the theory that the risk of hospitalization from COVID in the unvaccinated population did not change dramatically from December 2020 to May 2021, seems hard to explain how unvaccinated hospitalization rates were 20-30% higher in April/May peak vs. December peak when overall deaths were 6 times higher in December. I understand you cannot compare the deaths between the two periods because of vaccines, but it seems there is a disconnect between your study’s unvaccinated hospitalization rate and the hospitalization rate before the vaccines were available.
Would be interested to know if your study’s unvaccinated hospitalization rate was compared to hospitalization rates during periods when the vaccine was not available to test for reasonableness. Also would be interested to know if it is possible that your study under reported the number of hospitalizations in the vaccinated population (for example, how confident were you in matching the IIS vaccination patients to the COVID-NET hospitalized patients, how likely are providers to report a COVID vaccine to their state’s IIS database, are different provides more or less likely to report vaccines to the IIS, were any smaller follow-up surveys performed on hospitalized patients to see if their reported vaccine status is consistent with what you assumed in your study, etc.).
On 2021-01-31 21:31:27, user Ilya Zakharevich wrote:
The last two columns in the tables do not match each other (as they probably “should” for all developed countries, if one wants to get “meaningful comparison”; look for Lithuania vs Liechtenstein). I think that this is due to very different strategies to count child mortality.
Is it possible to replace the last column, dividing by the mortality (say) after age 1 year? As I said, it may be a “more interesting” number. (Less dependent on arbitrary accounting policies…)
On 2023-05-11 08:01:12, user Siri Fløgstad Svensson wrote:
This paper has now been publised in Neuro-Oncology Advances:<br /> https://academic.oup.com/no...
On 2020-05-26 17:04:01, user Eva Raschke wrote:
Could you please specify how the samples for Table 5 were collected, which criteria etc.?
On 2020-04-02 18:46:04, user Kristopher Purens wrote:
Does anyone have their previous data downloads? They do not appear to be sharing old predictions. Validating their previous models against real data would be very valuable to understand the strengths and weaknesses of their model and so it is baffling that is not being provided clearly.
On 2020-05-12 18:33:53, user Wouter wrote:
Readers should be aware of the considerable discrepancy between the simulated scenarios made using the model, and the actual spread of disease in Sweden after submission of the manuscript.<br /> Wouter van der Wijngaart, co-author
On 2020-04-12 13:23:51, user Joe Gitchell wrote:
Thank you to the authors for taking the time and effort to report these findings in the midst of confronting the challenges from managing the COVID19 pandemic. Please stay safe!
And it is with humility that I make a request to them to do two things with their data on tobacco use. The first I think should be pretty straightforward, the second will depend on the specificity available within the Epic records:
1) In Tables 1 and 2, can you please break out "Never" and "Unknown" in to separate categories; and
2) In these tables and in other analyses, can you please break out "tobacco use" at least in to combustible (cigarettes, cigars, cigarillos, hookah, etc) and noncombustible (smokeless tobacco, snus, vaping) categories?
Thank you. I also found your use of CART/decision-tree analysis really helpful, btw.
Joe
Disclosures:<br /> My employer, PinneyAssociates, provides consulting services on tobacco harm minimization on an exclusive basis to JUUL Labs, Inc., a manufacturer of nicotine vaping products. I also own an interest in an improved nicotine gum that has neither been developed nor commercialized.
On 2020-05-27 01:18:30, user Pablo wrote:
It is not rigorous enough but contains useful hypothesis.
On 2020-06-08 10:58:42, user ReviewNinja wrote:
Nice and very useful work! Saliva could be a great diagnostic tool! It would fix some problems about NP swab shortages and the necessity of accurate sampling by skilled personnel.
I was wondering about some details:<br /> 1.) The Ct values that you observe are lower for saliva compared to NP swabs. Could this (sometimes) be a matrix effect? Did you run standard curves of positive controls in a constant negative background of human RNA obtained as well from saliva as from NP swabs? A swab might sometimes just lead to more PCR inhibition? NP swabs and saliva might just have different Cqs for their LOD. Another way to assess this is with digital PCR.
2.) Just out of interest: What if you normalize the viral values for RNAseP expression (as a surrogate for sampling efficiency)? Are the values comparable then? Or is there really just more virus present in saliva? (I know, for diagnostics, this does not matter.)
3.)The RNAseP results indicate that sampling with NP swabs can indeed be an issue. <br /> It would have been nicer to also take standard curves here and plot RNAseP values, as Cq's on itself can be quite variable in between runs due to run-to-run variability.
3.) Just a last question, maybe for another paper;): are you also working on extraction free detection in saliva?
On 2020-05-14 05:11:14, user Matthew Ward wrote:
Hi Anne, brilliant study - Well done to all the team.
Could a saliva sample prove sensitive enough for Sars-Cov-2 to be detected on a lateral flow test?
Or would the sample almost always require amplification via PCR to increase sensitivity?
Many thanks<br /> Matt
On 2022-01-07 12:53:06, user Cliff Lynam wrote:
On page 6, the author describes the time frame as a point prevalence, which in terms of their data sources, is one day. The time frame really ought to have been 6 months, which is the mean duration of vaccine induced antibody protection against infection/transmission. In that case, the NNE would have been much, much lower: in the single digits. The article would then have been used by vaccine mandate advocates rather than opponents in their effort to generate confirmation bias and online justification.
On 2021-12-28 05:08:43, user Shark2007 wrote:
Interesting that you didn’t cite the studies you are referring to.
On 2020-06-18 22:51:21, user Sasha Bruno wrote:
I think there’s some issues in the paper with some of the assumptions made— especially about virus exposure to healthcare workers without confirmed positive tests via RT-PCR. Assuming virus exposure to healthcare workers during the early months of the outbreak, assumes that all the healthcare workers tested were also working during the early months of the outbreak and worked in wards, units and areas of the hospital likely for virus exposure.
Some units in those hospitals likely pose a higher risk of exposure than others. For example, a radiologist reviewing imaging results in an office at a hospital probably has a lower risk of exposure than a nurse in the ER or a pulmonologist in the ICU.
While I agree that some significant proportion of healthcare workers were likely exposed— without confirmed RT-PCR tests it’s a tenuous leap to draw conclusions about the low proportion (4%) of IgG antibodies in the group because we don’t know how many of them were in fact infected by the virus. It’s a logical premise but, too many assumptions and extrapolations to get there. Further investigation is needed.
But, I think the >10% of confirmed Covid-19 patients who no longer had detectable IgG antibodies post 21 days is a significant finding. 10% is too large of a percentage to be easily explained by potential errors in testing or sample collection.
On 2020-08-29 14:26:35, user CodeJ wrote:
Rhinoviruses, among other types of viruses can cause the common cold--including coronaviruses. Older paper for you but it reinforces this concept: https://www.ncbi.nlm.nih.go...
On 2020-08-25 03:39:38, user T Wiz wrote:
This is as close to a controlled experiment as you can get. Few comments, first I did not see a discussion of the symptoms or seriousness of the 3 crewpersons who tested positive for the nucleoprotein antibody but did not have neutralizing antibodies, as to whether or not they upon infection were symptomatic and how serious a COVID19 case they had and whether they had any indication ie. symptoms of a previous mild COVID infection. Second, there was no discussion of the 18 that did not get infected as defined by RT-PCR and serological testing, as to how they were able to avoid infection and did they have other neutralizing antibodies that were cross reactive. Third, as to the three that tested before embarking to have neutralizing antibodies, how serious was their COVID cases, and whether they had symptoms. Last, can they run on the samples kept, tests to determine if there are Tc cells for SARS-CoV-2 as to the uninfected and 3 with neutralizing antibodies.
On 2021-07-29 08:23:00, user J Tulloch wrote:
You should probably be comparing to the Liverpool paper looking at THIN data rather than the Cairns paper as they are much more comparable. (https://bmcinfectdis.biomed... "https://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-020-05018-2)")
On 2020-10-13 21:45:00, user Isaque Silva wrote:
The author was a past consultant of two companies that manufacturers hydroxychloroquine and yet consider himself enable, in a competing interest statement, to make such conclusion?? You must be kidding me.
On 2021-11-05 19:59:20, user Sergio Kas wrote:
So does this study say,
"Fully vaccinated were more likely than unvaccinated persons to be infected by variants carrying mutations"? Thats not good.
On 2020-04-25 18:43:20, user Retelska wrote:
Excuse, me, I don't know if I understand correctly. Do the 2 Elisa essays yield 5% false positives? Were these tests used to establish that 5% of general population has now been infected? You expect 5% false positives, right? How do you correct for this effect? Only the 3rd test with 0% false positives seems specific enough.
On 2021-08-16 04:13:39, user liutasx wrote:
RNA isn't infectious virus, so if it's 43 time more RNA, how much is more infectious virus in that sample?<br /> How was standardize upper epithelium cells count in measurements? During different phase of infection different amount of virus is produced, how accounted for this variable?
On 2021-08-20 23:43:57, user Chris Raberts wrote:
Can the authors explain how they conclude that lowering the particles in the air reduce the chance of infection? Seeing the sheer amount of particles exhaled this seems like a drop in the bucket, even at 50% reduction.
If you cant swim it doesnt matter if you fall in a lake or the ocean.
On 2020-06-17 20:50:32, user Serge wrote:
The<br /> effect of trained immunity resulting from an early-age vaccination <br /> proposed in the article is supported by a study at Bonn University (Dr. A. Schlitzer):
On 2021-02-15 20:44:04, user Ro H wrote:
South Asians as a group, especially first generation (citizens or immigrants), regardless of income level, are less likely to voluntarily get tested or go to the doctor unless theyre really sick. People with mild to moderate disease are unlikely to get tested but will self isolate and quarantine. This is a cultural thing observed in great Britain also. This means that their positivity rates will be higher as only the really sick get tested and a higher percentage will be hospitalized. Its interesting that their death rates are lower though. Im a part of this south Asian community in New York and this is what I've experienced with family and friends.
On 2020-11-12 01:57:40, user norenforcongress wrote:
Mucosal immunity is I believe the sentinel goal in breaking the back of Covid-19....
On 2020-05-26 09:28:09, user David Sbabo wrote:
5 counfounding factors with a p-value under 0.05, all in the same direction "higher chance of mortality for the no zinc group".
On 2021-08-20 23:58:21, user Chris Raberts wrote:
This model ignores the wave form observed repeatedly over the past year and a half. Covid infection is not a never-ending exponential function. Terrible.
On 2022-02-17 20:55:31, user RT1C wrote:
Table 3 (bottom) contains HR for boosted vs. non-boosted at various times (<6, 6-9, >=9 months). Aside from the minor labeling issue (hopefully not actual analysis issue!) that 6-9 months and >=9 months are not distinct subsets, overlapping at 9 months, I don't see how you could have made this analysis in the first place unless you have incorrectly defined POIC. You wrote, "we defined the proximate overt immunologic challenge (POIC) as the most recent exposure to SARS-CoV-2 by infection or vaccination." That means POIC for boosted subjects would be time since the booster dose as that is the most recent vaccination. Yet, considering how recently boosting began, how could you have boosted subjects with 6-9 or >=9 months POIC? (In your text you wrote, "For those boosted, the median time to being boosted was 16 days prior to the study start date (IQR -38 to 6 days).")
On 2020-03-26 16:57:03, user S Weeth wrote:
How about soap? Any testing on with soap?
On 2022-01-08 14:44:03, user Jack wrote:
It appears from the opening paragraph and the references to hospitalization and death and death certificates, that these incidents of myocarditis are referring specifically to severe myocarditis. Is anyone able to confirm if this is the case because, if it is, with mortality for severe myocarditis being as high as 50% after 5 years, that would make the vaccine a greater risk than Covid-19 for men under 40 who have no significant comorbidities.
On 2025-10-16 07:38:21, user C M wrote:
Pierre Chaillot declares working for INSEE. <br /> INSEE says the opposite: https://x.com/InseeFr/status/1622532980601241602 <br /> And what about the * that leads to nothing?
On 2021-09-12 11:21:41, user Shih-Hao Yeh wrote:
Let me assume your approach and data you used are all valid without any problems. <br /> 2 questions for your calculation and comparison in Fig 6 & 7.
(1) I'm confused in 44.4+210.5=255 in your Fig. 6. According to your context, 70% of children hospitalized for COVID-19 having medical comorbidity, and 30% don't. And in general, you estimate 33% of children in this age group have comorbidity based upon current data. So the likelihood of a CMB(comorbidity) kid get to hospital for COVID is 4.7 times more than a H(healthy) kid. [(0.67/0.33) / (0.3/0.7) = (0.67*0.7) / (0.33*0.3) = 0.469 / 0.099 = 4.7] That is correct.
Yet, what is the risks to be hospitalized for COVID for a H kid and a CMB kid respectively?<br /> Ans: <br /> Suppose in an average US medical area with 1 million adolescents, by your data, there will be 255 kids/1M hospitalized for COVID in 12 weeks supposed median prevalence . <br /> So, how many of them are H kids? How many CMB kids?<br /> 255*30%=76.5 H kids/1M kids<br /> 255*70%=178.5 CMB kids/1M kids<br /> Not 44.4 and 210.5.<br /> Yet, there are 670k H kids and 330k CMB kids per 1M kids.<br /> So, if you're healthy, in 1M healthy kids, your risk to be hospitalized for COVID within 12-week is<br /> 76.5/0.67=114/1M H kids<br /> if you have CMB, in 1M CMB kids, your risk to be hospitalized for COVID within 12-week is<br /> 178.5/0.33=541/1M CMB kids<br /> And yes, 541/114=4.7.
The risks to be hospitalized for COVID are actually larger than 44.4 and 210.5. Same mistake in high or low prevalence in the table. Tip: conditional probability. You don't include adult in the denominator of kid's risk, right? Same here.
(2) Further stratifying numbers into healthy and comorbidity groups to make the number smaller (by miscalculation) is a cunning move. Yet, it make sense. Comorbidity do contribute the severity of COVID.
However, since you stratify data for risks being hospitalized for COVID, why don't you stratify data for risks of vaccine-associated myocarditis (VAM)? I suppose that some medical comorbidity may also contribute to the risk of VAM?
I don't think these comparison in your paper are fair, meaningful comparison: <br /> P(healthy AND hospitalized for COVID) vs P(VAM)<br /> P(CMB AND hospitalized for COVID) vs P(VAM)<br /> These are meaningful comparison given same conditions:<br /> (a) P(hospitalized for COVID) vs P(VAM)<br /> (b) P(healthy AND hospitalized for COVID) vs P(H AND VAM)<br /> (c) P(CMB AND hospitalized for COVID) vs P(CMB AND VAM)
Taking these 2 problems into consideration, I don't think you can hold your original conclusion. If 255/1M can become 114 and 541 respectively, 162/1M can also become some numbers less than 114 and 541.
On 2021-09-21 11:13:56, user 4qmmt wrote:
about 400 children under 18 died from COVID in the US, so far. I'm not aware of any dying after COVID vaccinations due to myocarditis, or other vaccine side effects.
Have you looked?
On 2021-08-14 12:49:05, user Uncle George wrote:
Thank you for producing this research study. Its findings are very interesting and amazing. Due to the political correctness of society and pharma influences, this paper may never be peer reviewed. However, many people can benefit from it through this preprint article. Thank you again for your work!
On 2021-01-05 15:56:38, user Ti wrote:
You write that "the best performing method is XRAI (AUPRC = 0.224 ± 0.240)". Meaning that the AUPRC ranges from -0.016 to 0.464. Surely, you cannot have a negative area under the curve.
On 2020-10-20 18:03:33, user Dinofelis wrote:
One is again making the same fundamental error in this paper: not being able to reject significantly H0 is absolutely not a proof of H0 validity: it simply means the study wasn't accurate enough.
For instance:
"The overall mortality was not significantly different among patients who<br /> received hydroxychloroquine compared to the control group (OR: 0.94, <br /> 95% CI: 0.72 to 1.22; p = 0.63)"
doesn't mean that one has shown that there is no effect on overall mortality. It means one doesn't have good enough data to conclude anything about it, and one could have an improvement of 25% in mortality (0.75 is within the CI) without being able to discriminate it from no effect or worsening.
On 2020-12-17 23:14:59, user Rakshit Sidd wrote:
Hey Peter, Can you please let me know that which dataset you referred in to? I need the source.
On 2021-02-03 22:22:54, user Francisco Sánchez Jiménez wrote:
But let's see, here the crucial test is missing, let's leave the apriorisms, that the antibody titers are in higher quantities does not ensure greater efficiency, or effectiveness, that remains to be demonstrated
On 2021-01-26 03:42:24, user Terran Melconian wrote:
Thanks for sharing this very interesting article.
On page 6, for the definition of the x and z transforms, they are both given as sin(2*pi*t/tau). One of them is presumably meant to be a cosine, right?
On 2019-08-07 02:07:14, user Pranay Aryal wrote:
Aren't thrombosis biomarkers surrogate endpoints. Shouldn't we use meaningful endpoints like mortality and morbidity? Thanks.
On 2020-04-08 13:20:06, user Devi Dayal wrote:
Through this publication, we just added some more data to the recently published articles on a protective role of BCG vaccination against COVID-19, reassuring for countries with limited resources to fight the pandemic on their own.
On 2020-08-19 14:58:17, user jan homolak wrote:
A comment on the methodological approach used in this study by Trkulja et al. explaining why "A suggested effect of air temperature on severity of COVID-19 in hospitalized patients by Kifer et al. (Effects of environmental factors on severity and mortality of COVID-19; medRxiv 10.1101/2020.07.11.20147157) is most likely an artifact" can be found here: https://bit.ly/3aCVAJk
On 2020-06-09 17:42:33, user Rintaro N. wrote:
Do this study think about the possible different? blood donation behaviors depending on blood type?<br /> cf.?<br /> ?Blood Type and Blood Donation Behaviors: An Empirical Test of Pure Altruism Theory<br /> https://papers.ssrn.com/sol...
On 2020-05-07 15:07:58, user Thomas Meunier wrote:
KEY TAKEAWAYS FROM STUDY:
The research, which has not yet undergone standard peer review evaluation, does not question the efficiency of social distancing.
The research looks specifically at the impact of police-enforced home containment policies in some European countries.
The work suggests that social distancing may be just as effective as home containment.
4.The results show that the epidemic was already in decline (that is, the number of cases was growing less and less rapidly for 2 to 3 weeks before the lockdown and kept declining at the same rate afterwards) before the full lockdown, possibly thanks to social distancing measures already in place.
On 2020-07-21 21:34:31, user Deborah Verran wrote:
Interesting development. Although a systematic review on this topic may be of interest the constraints posed by resorting to summarising the already published literature may limit it's utility in practice. Other groups of professionals are now undertaking the process of developing and posting guidelines in order to assist clinicians who are being faced with making decisions on such patients during the pandemic https://journals.lww.com/jb...
On 2020-03-29 22:38:51, user Sinai Immunol Review Project wrote:
Key findings:<br /> This study investigated the profile of the acute antibody response against SARS-CoV-2 and provided proposals for serologic tests in clinical practice. Magnetic Chemiluminescence Enzyme Immunoassay was used to evaluate IgM and IgG seroconversion in 285 hospital admitted patients who tested positive for SARS-CoV-2 by RT-PCR and in 52 COVID-19 suspected patients that tested negative by RT-PCR. A follow up study with 63 patients was performed to investigate longitudinal effects. In addition, IgG and IgM titers were evaluated in a cohort of close contacts (164 persons) of an infected couple.
The median day of seroconversion for both IgG and IgM was 13 days after symptom onset. Patients varied in the order of IgM/ IgG seroconversion and there was no apparent correlation of order with age, severity, or hospitalization time. This led the authors to conclude that for diagnosis IgM and IgG should be detected simultaneously at the early phase of infection.
IgG titers, but not IgM titers were higher in severe patients compared to non-severe patients after controlling for days post-symptom onset. Importantly, 12% of COVID-19 patients (RT-PCR confirmed) did not meet the WHO serological diagnosis criterion of either seroconversion or > 4-fold increase in IgG titer in sequential samples. This suggests the current serological criteria may be too stringent for COVID-19 diagnosis.
Of note, 4 patients from a group of 52 suspects (negative RT-PCR test) had anti-SARS-Cov-2 IgM and IgG. Similarly, 4.3% (7/162) of “close contacts” who had negative RT-PCR tests were positive for IgG and/or IgM. This highlights the usefulness of a serological assay to identify asymptomatic infections and/or infections that are missed by RT-PCR.
Limitations:<br /> This group’s report generally confirms the findings of others that have evaluated the acute antibody response to SARS-Cov-2. However, these data would benefit from inclusion of data on whether the participants had a documented history of viral infection. Moreover, serum samples that were collected prior to SARS-Cov-2 outbreak from patients with other viral infections would serve as a useful negative control for their assay. Methodological limitations include that only one serum sample per case was tested as well as the heat inactivation of serum samples prior to testing. It has previously been reported that heat inactivation interferes with the level of antibodies to SARS-Cov-2 and their protocol may have resulted in diminished quantification of IgM, specifically (Xiumei Hu et al, https://www.medrxiv.org/con... "https://www.medrxiv.org/content/10.1101/2020.03.12.20034231v1)").
Relevance:<br /> Understanding the features of the antibody responses against SARS-CoV is useful in the development of a serological test for the diagnosis of COVID-19. This paper addresses the need for additional screening methods that can detect the presence of infection despite lower viral titers. Detecting the production of antibodies, especially IgM, which are produced rapidly after infection can be combined with PCR to enhance detection sensitivity and accuracy and map the full spread of infection in communities, Moreover, serologic assays would be useful to screen health care workers in order to identify those with immunity to care for patients with COVID19.
On 2021-06-28 02:07:33, user Matt wrote:
The study seems to have a fatal flaw, which is that it was based on healthcare workers. Hospitals and other healthcare offices would have very strict mask enforcement and many other mitigation measures not found outside of healthcare settings. Therefore, I don't see how one can extrapolate the results to the general population. In other words, maybe it was the mitigation measures and not the vaccine or prior infection that was the primary driver in limiting the spread in this particular scenario.
On 2021-08-14 05:50:28, user Brad Mellen wrote:
I assume the 167 infected people tracked in the study were previously vaccinated. Is it possible that antibody mitigated viral enhancement played a role in the increased viral loads? A study done by Wen Shi Lee et al in the Nature Microbiology volume 5, pages 1185–1191 (2020) noted the potential dangers of Covid 19 vaccinations could increase viral loads and ultimately increase the spread of Covid 19.
On 2020-03-08 18:37:04, user Jyotishka Das wrote:
Dear Authors,<br /> The work that you people have done is really interesting, and in times like this we must stand with each others in whatever we can. Being a student researcher at IIEST, Shibpur in the field of deep learning, it would be of immense help if you could kindly share the dataset with me for purely academic purpose. My contact email is : dasjyotishka@gmail.com . Thanks
On 2021-01-29 22:20:14, user Britt-Marie Halvarsson wrote:
Hi!
Very interesting paper and I am very grateful of your transparency with code and data!
However, I find it a bit problematic that the corrected R0's are not very normally distributed. Do you have a comment on that?
Best Regards,<br /> Britt-Marie Halvarsson
On 2021-06-11 13:50:33, user Jay Alan Erdman wrote:
My apologies, I didn't see the full text so some of my criticism can be refuted. Nonetheless it is a chart review with not a very large N. And again, most importantly, it says nothing about current treatment.
On 2021-06-19 23:50:30, user Gabriel Rodrigues Couto wrote:
This study was made with >70 year old patients. The interpretation should contain this information, right? It doesn't. In brazil a lot of midia is announcing this article as " the vaccine does not work".
On 2022-11-14 11:51:31, user Baral Nischit wrote:
The full manuscript is published and the PMCID is PMC9620387
On 2022-03-23 16:58:16, user Stefan Baeuml wrote:
It would be interesting to have a follow up study in the presence of Omicron. In particular, given the increased likelihood of breakthrough infections, it would be interesting to see if the likelihood of the symptoms mentioned in the 'Results' section still remains within the background of people without SARS-CoV-2 infection.
On 2023-07-01 05:57:09, user Zhaolong Adrian Li wrote:
Published as Li ZA, Cai Y, Taylor RL, et al. Associations Between Socioeconomic Status, Obesity, Cognition, and White Matter Microstructure in Children. JAMA Netw Open. 2023;6(6):e2320276. doi:10.1001/jamanetworkopen.2023.20276
On 2021-08-13 16:38:39, user Dr. Jon wrote:
Can you think of any disease for which natural immunity is not effective and durable?<br /> Influenza is one, but it exhibits remarkable variability compared to other diseases.
On 2021-08-04 02:30:29, user Deplorably Black wrote:
Interesting. Does this still apply considering<br /> the new variants?
Has a study been conducted as to the vaccines effect on long COVID?
I suffered from daily headaches post COVID for 8 months. They stopped immediately after vaccination.
I know several others with the same experience.
That in itself made vaccination post COVID worthwhile for quality of life.
On 2020-06-02 19:09:27, user Irene Petersen wrote:
There are two key issues with this study.
1) The majority of people in this study (about 16 million) are NOT at risk of the outcome (dying from COVID19) as they will not have been infected.
2) Dying from COVID19 is a two-stage process - A) Risk of getting infected B) Risk of dying once infected. This study conflates the two. Thus you can't tell whether an elevated risk is due to A or B.
On 2021-07-21 09:05:50, user haowen guan wrote:
I have a few questions about this guideline:<br /> 1.Could i use this guideline to other genes or panels ?<br /> 2. Is there any chance that i can get the code about In silico prediction of splicing effects in LDLR
On 2021-12-06 15:18:05, user Jens Happel wrote:
Dear Robert,
thanks for the study. Is it possible to differentiate the group of the unvaccinated in unvaccinated and vaccinated between 1st dose and 2 weeks after infection?
In some studies they found the effect that between 1st and 2nd jab the likelihood of infection is significantly increased.
For example here
https://www.researchgate.ne...
see figure 2
Would be intressting to see what happens in this group.
Kind regards<br /> Jens Happel
On 2020-09-30 14:37:10, user tjo wrote:
Were the 62 patients in that experiment all from the ED group, or was it a mix on inpatients and ED?
On 2021-01-31 18:53:06, user Timotheus123 wrote:
This is clearly not a serious study. No apparant controls for age or comorbidity, no random assignment of treatment or control, an "inverse probability of treatment" adjustment.. etc etc.
And yet a strong conclusion debunking ivermectin?
This is NOT science.
On 2023-04-11 00:51:25, user Xianyong Yin wrote:
We did a similar analysis between vitamin D and psoriasis. We achieved similar results at https://pubmed.ncbi.nlm.nih...
On 2020-05-16 20:44:07, user Javier Mancilla-Galindo wrote:
I would advise reviewing this OR and CI for hospitalization in patients >=74 years: "individuals aged 50-74 and >=74 years were more likely to be hospitalized than people from 25-49 years (OR 2.05, p<0.001, 95% C.I. 1.81-2.32, and OR 23.84, p<0.001, 95% C.I. 2.90-5.15, respectively)". This apparent error is present in both the abstract and the manuscript.
The finding that only 67% of hospitalized patients developed pneumonia is quite remarkable, since this is a similar rate to pneumonia findings on CT scans for ASYMPTOMATIC/PRE-SYMPTOMATIC patients (67.3-70.8 %). The rate for patients with mild COVID-19 was 95.5% in one study. Therefore, the authors could adress how this rate compares to other more recent studies and what the possible causes of these differences could be (i.e. few CT scans performed, commonly used definitions of pneumonia). Otherwise, this could lead to false conclusions such as thinking that patients are being admitted with milder disease or even with few or no symptoms at all.
On 2021-07-01 02:43:16, user killshot wrote:
No mention of vitamin D levels here. A vitamin D level above 50 ng/ML reduces mortality by 900% and significant morbidity requiring hospitalization by 300%. Masks have never been shown to do any of this. The fact is, masks were nothing more than virtue signaling and really didn't do very much at all. You failed to mention previous studies on influenza where it was proven that masks a little difference. Plus, you conveniently avoid the downside of masks. Remember "risk versus benefit", no? To wit:
"Prolonged mask use (>4 hours per day) promotes facial alkalinization and inadvertently encourages dehydration, which in turn can enhance barrier breakdown and bacterial infection risk. British clinicians have reported masks to increase headaches and sweating and decrease cognitive precision. Survey bias notwithstanding, these sequelae are associated with medical errors. By obscuring nonverbal communication, masks interfere with social learning in children. Likewise, masks can distort verbal speech and remove visual cues to the detriment of individuals with hearing loss; clear face-shields improve visual integration, but there is a corresponding loss of sound quality."
Please look at the ridiculous downside of wearing the silly things that do nothing for protection. If you want me to pull up all the references, I will. But it is tiresome. Please do your own research. Masks are silly and did absolutely nothing for transmission.
On 2020-10-26 13:14:19, user Stefan Dombrowski wrote:
I am not a fan of these respositories. They may well contain research that has been rejected by the peer review process and thus cannot find a legitimate outlet. And, now that this study has been submitted to the world via this repository it very likely cannot be subjected to the gold standard of peer review-- the double blind peer review process. CNBC and other media outlets have been sloppy by disseminating this study broadly given its lack of scientific vetting.
On 2021-04-16 18:14:19, user Judy Hodge wrote:
I am curious what vaccine the mother that was tandem feeding received? Also am I reading your data correct that the Moderna elicited a higher IgA response in breastmilk?
On 2021-08-24 18:06:02, user Skeptic wrote:
23andMe has an article about this on its website, in which the company listed the WRONG reference SNP number. According to this pre-print, it's rs7688383, but 23's 6/2/21 article claims it's rs7868383. In any case apparently the v.5 chip did not include this SNP as I can't find it in the raw data for any of the five kits I manage at 23.
Kind of important to proof read, 23andMe, if you expect to develop and maintain credibility: https://you.23andme.com/p/8...
On 2020-03-11 10:09:13, user Bob Phillips wrote:
Needs the units for bilirubin and ALT, and a very clear description of WHEN these lab tests were taken ('predicting' severe disease when a child has severe liver dysfunction on an ICU isn't that useful)
On 2020-12-05 20:36:08, user Anglo Svizzera wrote:
I'm not sure that this study is of much use at all when it comes to the conclusion "Vitamin C, zinc and garlic supplements had no association with risk for SARS-CoV-2".
This is especially the case when it comes to vitamin C and zinc as the amounts used would undoubtedly be relevant, particularly in the case of vitamin C.
Most OTC supplements of vitamin C are rarely over 1000mg and, if they are not liposomal or time-release, this may mean that much of the vitamin C is be excreted before being utilised. In fact, the UK RDA for vitamin C is a mere 40mg which is probably the amount found in many cheaper multivitamin supplements and, as such, would be unlikely to have any protective effect against Covid-19.
Many doctors have noted that patients with severe Covid disease appear to show symptoms of scurvy, thus indicating that their vitamin C levels are inadequate, which is unsurprising given that the demand for vitamin C by the body is vastly increased during viral infections.
Considering that mammals that produce their own vitamin C make far more than this amount on a daily basis, and even more when fighting infection, it would be interesting to see whether larger amounts of vitamin C spread out during the day may make a difference with regard to the susceptibility of Covid-10. Examples are that a healthy dog makes 18mg/kg a day, whilst a healthy goat makes 200mg/kg!
Regarding zinc supplementation, the forms of zinc supplements vary widely, some being more bio-available than others, so it may have been useful for the researchers to find out the amount of "elemental zinc" in the supplements taken.
Obviously this kind of study is not designed to discover whether larger amounts of vitamin C and/or certain forms of zinc might reduce susceptibility or morbidity from Covid-19 but it might clearly be worthwhile studying this in more detail.
On 2020-10-02 21:42:30, user Gabor Drotos wrote:
Dear Authors,
May I ask how a "close contact" was defined?
On 2021-08-03 10:01:20, user Alan Yoshioka, PhD wrote:
There are several numerical discrepancies and questions about methods that should be resolved before any conclusions can be drawn from the study.
When was it decided to exclude patients whose RT-PCR results had a cycle threshold value >35 in the first two consecutive [tests]? When was it decided to adjust the Kaplan–Meier analysis for symptom onset?
Please reconcile the discrepancy between the "mild" in study title and the "mild to moderate" in the description of the mandate of the isolation hotels. The inclusion criteria do not appear to specify the severity of disease, which would apparently then depend on the admission criteria of the hotels.
In Table 1, stated percentages of patients who are male do not match raw numbers of 69/89 for all patients and 36/47 for ivermectin, respectively; instead (corresponding to females accounting for 21.6% in the abstract) 78.4% = 69/88, and 78.3% = 36/46.
The abstract says 16.8% were asymptomatic at baseline, which does not complement the 80.9% symptomatic in Table 1, nor the 69 symptomatic patients in Figure 3. Perhaps I am missing something, but it is not clear why 37 and 35 symptomatic patients in Table 1 do not match the numbers of subjects at risk, 36 and 33, on Day 0 in Figure 3.
Table 2 presents results from RT-PCR testing at days 4 to 10. Day 2 is said to have been added to the protocol along with Day 4, but no explanation is given for why data from Days 2, 12, and 14 are not also shown in the table.
I'm not a specialist in lab tests, but I'm afraid I am having trouble understanding the post hoc analysis based on a convenience sample of 16 samples on Day 0. Does Table S2 mean there were then 26 samples taken on Day 2?
I am mildly puzzled by the alignment of the dots in Figure 2: most appear to lie on a grid, but a few sets of points are slightly raised or lowered. Is this a normal occurrence?
On 2024-05-02 15:45:09, user Kelly Barta wrote:
This is such an important and groundbreaking study in its showing a differentiation between Atopic Dermatitis and Topical Steroid Withdrawal Syndrome, which has been one of the big debates within the medical community. Patients need and deserve acknowledgement and support from their health care providers, but understandably, this is unable to happen without the science to back up what we are seeing anecdotally in the eczema patient population.
More research is needed to determine how and when topical steroids are creating these dysfunctions in patients in order to better understand their proper use and prescribing guidelines. This research is CRITICAL to the over 31 million Americans living with eczema and over 300 million worldwide (not to mention the countless other dermatology patients), who are prescribed topical steroids to manage a skin condition.
On 2020-08-30 16:23:17, user Martijn Weterings wrote:
Figure 3 shows two remarkable effects:
Instead of fitting to current epidemiological curves we should determine the epidemiological parameters more directly based on detailed data (e.g. based on databases with contact tracing information and tracing the tree of infection rather than basing estimates on an aggregated data like total deaths and total infections per day, which are also not so accurate). Estimates based on real life face-to-face networks help, but may not be sufficient to fill in the gap of information about epidemiological parameters.
In addition, while the model explains very well the effect of the heterogeneity in rates of infection among different people, it is still not a realistic model and lacks the nuance of spatial distribution and network structures which will have a remarkable effect on the curves as well including an early decrease of the growth rate (due to local saturation, increase of immunity). The downside of the simplicity is that the heterogeneity may become overestimated (in order to compensate for the lack of the other effects) and the predictions of the percentage to reach immunity may be underestimated.
Possibly the model may work well for cities. However in many European countries we see already second waves occuring in mostly different regions and different populations (also Australia gives a clear second wave which is even much stronger). <br /> The 1st wave was like a forest fire that has been mostly local and got actively extinguished (thanks to measures like working at home and travel restrictions). We should not confuse the decline as all the dry old trees being gone and as if the risk of fires is over now or relatively low. Those 1st wave fires were local and there may still be many patches that are able to catch fire.
On 2021-08-25 20:16:42, user Tom wrote:
As all 12-16 year-old teenagers were not vaccinated at the time of the study, could you answer this question please:
Why did the study include 12-16 year-old teenagers in the group : adult/teenager household contacts that were vaccinated but not isolated?
On 2021-09-25 12:55:23, user Raja Mugasimangalam wrote:
Excellent.<br /> The title of the article can be compressed a bit.
On 2022-07-14 07:12:37, user Marek Widera wrote:
Finally, this work has been published in eBioMedicine Volume 82, August 2022, 104158
On 2022-02-19 23:34:39, user Ister wrote:
for unclear reasons in 2019 Thailand experienced anomalous excess death. Baseline would maybe be better computed dropping 2019 and adding 2014
On 2021-01-28 19:31:33, user Maciek Boni wrote:
The public Github repo has been renamed: https://github.com/bonilab/...
On 2021-03-02 18:53:07, user Olivier Cazier wrote:
Contrary to MHS study of Pfizer in Israel , who took care of having vaccinated groups and unvaccinated groups with the same age, genre profile, comorbidities, etc, in this study, the two groups have very different profiles. They did a weighted correction, but give no details.<br /> As the results are quite different from MHS results, who gave a 57% efficiency for Pfizer first dose, one can be sceptical of the correftion method
On 2020-12-06 16:52:10, user Jammi N Rao wrote:
This paper has two major flaws: <br /> 1. is the sample size. There is no mention of whether there was any prior sample size estimation and if there was, which of the 6 primary outcome measures determined it. If mortality at 30 days was the main outcome measure then there is no statement as to the minimum reduction that was considered clinically relevant and was therefore the delta that informed the sample size calculatiom for adequate power.<br /> 2. Perhaps the bigger problem is that it was NOT an intention to treat analysis. Two patients were randomised to the Itolizumab arm but withdrawn due to a reaction. One of these patients sadly died at 9 days. If these 2 patients are added into the analysis then the result of the mortality outcome becomes statistically non-significant.
I wrote this up in an op-ed piece here:
On 2021-02-15 16:30:09, user Vana Sypsa wrote:
The paper appears now in Emerging Infectious Diseases
On 2020-12-28 18:04:37, user Rogerio Atem wrote:
The 3 preprints of this series on COVID-19 epidemic cycles were condensed into a single article that summarizes our findings using the analytical framework we developed. The framework provides cycle pattern analysis, associated to the prediction of the number of cases, and calculation of the Rt (Effective Reproduction Number). In addition, it provides an analysis of the sub-notification impact estimates, a method for calculating the most likely Incubation Period, and a method for estimating the actual onset of the epidemic cycles. <br /> We also offer an innovative model for estimating the "inventory" of infective people.<br /> (Revised, not yet copy-edited)<br /> https://doi.org/10.2196/22617
On 2020-05-06 20:06:21, user MS wrote:
Need to be clear on "false-negative RT-PCR". This study is looking at the presence of virus and the viral load in the upper respiratory tract through-out infection as much as it looks at sensitivity and is dependent on a deep sample taken correctly using appropriate sampling kits as well as the sensitivity of the test.
On 2020-11-12 15:40:04, user Martin Dugas wrote:
Further evidence is available:
On 2020-05-02 13:08:43, user Theo Sanderson wrote:
"the later the fixed-duration quarantine is introduced, the smaller is the resulting final number of deaths at the end of the outbreak."
It might be worth amending this sentence as it clearly cannot be strictly true (ad absurdum argument: a quarantine just before the last death of the epidemic would have negligible effect)
More generally, considering the literature on the practicality of timing interventions, such as https://arxiv.org/abs/2004.... might be helpful, and a brief discussion of the fact that the choices outlined here are not the only ones, and that some countries have managed to suppress the epidemic without population quarantine might add to the preprint.
On 2020-09-18 17:21:48, user kdrl nakle wrote:
Dysfunctional response of T cells (not just elderly) has already been reported in papers before but the reasons were unclear.
On 2020-01-28 21:44:55, user Nan-Hung Hsieh wrote:
A minor comment for your result. According to the code you shared, the interval you used in the paper is confidence interval, not credible interval. For example, on page 4, the 95% credible interval should be [4.5, 7.5]. You can use bayestestR package to double-check the result.
On 2020-10-08 05:54:37, user Gennadi Glinsky wrote:
It will be interesting to see if these initial observations could be confirmed and expanded by the worldwide prospective studies precisely mapping the population-scale levels of pre-existing immune cross-reactivity against SARS-CoV-2 to the clinical course and outcomes of the pandemic.
On 2021-08-12 01:05:28, user SkylarkV wrote:
CDC and FDA won't act on increasing calls for mRNA boosters for the J&J vaccinated unless the data support it, yet researchers appear to be simply ignoring J&J in their research, so those data can't be obtained. So much for for #HealthEquity!
On 2022-03-01 17:11:24, user Rogerblack wrote:
An interesting paper, there are some unclarities in the paper that I'd like to see addressed.
' Full-time sick leave was reported by 9.4% of test-positives and 6.5% of test-negatives (RD=3.20, 95% CI 2.88-3.47%),' This whole paragraph is unclear, and the interpretation depends critically on the question asked.
Does 'Full time sick leave' here mean leave from full time work, or does it mean having to abstain from work, be it part-time or full time. Similarly, does 'part-time sick leave' mean reduction in hours worked due to illness or having to abstain from part-time work.
I find unfortunate the seeming lack of a question around severity. I have had a post-viral disease for the past 40 years. For most of that time, I would have ticked a 'fatigued' box.
This simple binary conceals that during that time, this has meant fatigue that means I can't do normal activities after 8 hours work, to bedbound.
A plea, to this team and others.<br /> Please ask about impact on normal role.<br /> 'Have you had to at this time give up caring/work/educational responsibilities due to illness' (for example)<br /> I have had most of the symptoms mentioned in figure 1, at varying severities for the past decades, with prevalance and severity varying.<br /> I DO NOT CARE ABOUT ANY OF THEM.
I care about if I can
A) Perform normal activies as before illness onset.<br /> B) Have to pick between normal activies and drop some I am no longer able to do.<br /> C) Have to give up many normal activies and only able to do some.<br /> D) Extremely limited ability to do normal activities.<br /> E) Self-care only.<br /> F) Unable to perform self-care to a reasonable quality.<br /> (For the last weeks, E)
On 2020-08-21 21:28:15, user Orison Woolcott wrote:
This study has been accepted and published in High Altitude Medicine & Biology: https://www.liebertpub.com/...
On 2020-02-29 18:15:11, user Per Carlbring wrote:
For reference #21 a correction was published in 2016: https://journals.plos.org/p...
On 2020-03-23 19:01:15, user Sinai Immunol Review Project wrote:
Summary:
Study on blood biomarkers with 80 COVID19 patients (69 severe and 11 non-severe). Patients with severe symptoms at admission (baseline) showed obvious lymphocytopenia and significantly increased interleukin-6 (IL-6) and CRP, which was positively correlated with symptoms severity. IL-6 at baseline positively correlates with CRP, LDH, ferritin and D-Dimer abundance in blood. <br /> Longitudinal analysis of 30 patients (before and after treatment) showed significant reduction of IL-6 in remission cases.
Limitations:
Limited sample size at baseline, especially for the non-severe leads to question on representativeness. The longitudinal study method is not described in detail and suffers from non-standardized treatment. Limited panel of pro-inflammatory cytokine was analyzed. Patients with severe disease show a wide range of altered blood composition and biomarkers of inflammation, as well as differences in disease course (53.6% were cured, about 10% developed acute respiratory distress syndrome). The authors comment on associations between IL-6 levels and outcomes, but these were not statistically significant (maybe due to the number of patients, non-standardized treatments, etc.) and data is not shown. Prognostic biomarkers could have been better explored. Study lacks multivariate analysis.
Findings implications:
IL-6 could be used as a pharmacodynamic marker of disease severity. Cytokine Release Syndrome (CRS) is a well-known side effect for CAR-T cancer therapy and there are several effective drugs to manage CRS. Drugs used to manage CRS could be tested to treat the most severe cases of COVID19.
Review by Jaime Mateus-Tique as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn school of medicine, Mount Sinai
On 2021-05-29 01:46:20, user David Steadson wrote:
Why were respiratory issues etc not part of the symptoms studied? They are typically listed as frequent long covid symptoms. Ref 10 for example says -
"Insomnia (18.6%), respiratory symptoms (including pain and chest tightness) (14.7%), nasal congestion (12.4%), fatigue (10.8%), muscle (10.1%) and joint pain (6.9%), and concentration difficulties (10.1%) were the most frequently reported symptoms."
On 2020-04-02 18:38:09, user Rosemary TATE wrote:
Did you know that you can post reviews of these preprints on outbreak science? I have posted mine<br /> https://outbreaksci.prerevi....<br /> I have asked them to see if they can put a link on medrxiv to inform people of this. <br /> It provides a more methodological way of commenting on preprints
On 2021-02-16 16:07:20, user Roberto Valente wrote:
Dear researcher colleagues. The manuscript has been reviewed and published on the British Journal of Surgery. https://doi.org/10.1093/bjs...
On 2020-04-01 14:34:11, user Sinai Immunol Review Project wrote:
Summary: ?Retrospective study on 97 COVID-19 hospitalized patients (25 severe and 72 non-severe) analyzing clinical and laboratory parameter to predict transition from mild to severe disease based on more accessible indicators (such as fasting blood glucose, serum protein or blood lipid) than inflammatory indicators. In accordance with other studies, age and hypertension were risk factors for disease severity, and lymphopenia and increased IL-6 was observed in severe patients. The authors show that fasting blood glucose (FBG) was altered and patients with severe disease were often hyperglycemic. Data presented support that hypoproteinaemia, hypoalbuminemia, and reduction in high-densitylipoprotein (HDL-C) and ApoA1 were associated with disease severity. ?
Limitations: ?In this study non-severe patients were divided in two groups based on average course of the disease: mild group1 (14 days, n=28) and mild group 2 (30 days, n=44). However mild patients with a longer disease course did not show an intermediate phenotype (between mild patients with shorter disease course and severe patients), hence it is unclear whether this was a useful and how it impacted the analysis. Furthermore, the non-exclusion of co-morbidity factors in the analysis may bias the results (e.g. diabetic patients and glucose tests) It is not clear at what point in time the laboratory parameters are sampled. In table 3, it would have been interesting to explore a multivariate multiple regression. The correlation lacks of positive control to assess the specificity of the correlation to the disease vs. correlation in any inflammatory case. The dynamic study assessing the predictability of the laboratory parameter is limited to 2 patients. Hence there are several associations with disease severity, but larger studies are necessary to test the independent predictive value of these potential biomarkers.?
Findings implications:? As hospital are getting overwhelmed a set of easily accessible laboratory indicators (such as serum total protein) would potentially provide a triage methodology between potentially severe cases and mild ones. This paper also opens the question regarding metabolic deregulation and COVID-19 severity.
On 2020-04-27 16:44:44, user Dr. Amy wrote:
Obesity increases the density and upregulates ACE2 receptors. I couldn't figure out how women were protected given the higher incidence of obesity, but a Japanese researcher in this area shared this with me (which I do not fully understand.) "ACE2 is not only an entry receptor for the SARS-CoV-2 virus, but also protects against the pathogenic effects of RAS and the ACE/AngII/AT1R axis. I believe the balance between ACE/AngII/AT1R axis and ACE2/Ang1-7/MasR axis is important. Higher expression of ACE2 in old female rats than male represents protective effects. That's why women would have lower morbidity and mortality. This is my speculation."
On 2020-04-22 10:40:37, user stylin19 wrote:
Index dates range from March 9, 2020 to April 11, 2020, and patients were followed from index until hospital discharge or death. The period prior to index is designated as the baseline period and on or after index is designated the follow-up period.
something is not quite right about this study.
There were only 731 COVID-19 cases in the U.S. end of day 03/08/2020.
Why did the VA start using hydroxychloroquine so early ?
FDA "emergency use" edict wasn't approved until 03/29/2020.
FDA already has a "compassionate use" for drugs. <br /> It's usually at end of life situations.
Per your study:<br /> “However, hydroxychloroquine, with or without azithromycin, was more likely to be prescribed to patients with more severe disease, as assessed by baseline ventilatory status and metabolic and hematologic parameters.”
Is it possible this study may actually prove more of these Vets were saved because of hydroxychloroquine?
You really need to provide more data regarding Hospitalization\treatment dates for each patient.
On 2022-07-20 17:40:27, user Elle Tigre wrote:
You suggest that, “In only a few cases, the presence of S1 or spike may be correlated with vaccination, however according to our previous findings, S1 is only detected within the first two weeks after the first dose and spike is rarely detected.”
An important takeaway from the study you referenced in your point is that none of the participants in that study had previous covid infection. So, it’s not that vaccination and boosters aren’t correlated with PASC or “Long covid” but, perhaps, previous infection, either before and/or after vaccination as well as an unvaccinated cohort, may be worthy of exploration? Especially considering your acknowledgement of non-PASC hospitalized participants having S1 and N, but no detectable full length spike protein, which is indicative of a typical “natural infection.” That should’ve flagged your suspicions. When exosomes can carry spike protein *at least* up to 4 months(though many have found it circulating much, much longer), don’t you think vaccination and boosting would prolong that circulation of spike protein? If spike protein, on its own, can cause pathogenesis, why don’t you suspect it can also cause, or at the very least, prolong PASC? At this point, your team should have more follow-up questions and reasonable suspicions from your study results than answers.
On 2020-08-29 15:35:25, user Enginer01 wrote:
In evaluating these tests, keep in mind that the main effect of HCQ is to allow zinc into the cells, where it is rapidly consumed preventing replication of the virus. Normal zinc intake, easily met from healthy vegetable intake, is 10 mg/d. HQC tests on SARS-CoV-2 indicate an initial daily does of 200 mg/d followed by 50 mg/day. Note that excessive zinc intake can cause copper anemia.