On 2020-09-03 20:23:26, user Mahdi Rezaei wrote:

Please see the demo results of this research in our 2-minute video clip below: <br /> https://youtu.be/FwCP2ySDshE<br /> I hope you like it. Your valuable comments/advice will be highly appreciated.

On 2020-09-05 15:23:44, user Kwon Seokjoon wrote:

Then, why not even FDA UEA trial for the Saliva test until now (9/04/20020) ???

On 2020-09-05 17:49:00, user DFreddy wrote:

You assume masks reduce infectious transmission by 50%. Most of this evidence comes from observational studies with the known biases. Including such uncertain data in your model seems to me multiplying uncertainty, which goes against the idea of science: reduce uncertainty. Your conclusion lacks carefulness and may cause harm to the population. I advice you to prominently report on any uncertainties and their repercussions. Finally craft a new well balanced conclusion.

On 2020-09-08 20:12:03, user Lewis Lee wrote:

Dear authors,

Many thanks for the interesting paper with numerous measures/analyses for controlling confounding. I'd like to ask the following:

How valid is it to use the set of the defined ICD-10 codes for identifying COVID-19 cases? I presumed the use of U07.1 (and possibly some U07.2) may only include those who were tested for the COVID-19. I guess majority of the general population were not tested. If that's the case, most of the COVID-19 negative cases may not be truly negative but indeed unobservable (missing data) at the moment of analysis. Besides, those who did the COVID-19 tests may have already different measured/unmeasured characteristics from the non-tested population as they were not randomly/probability sampled for tests. Could this be a source of selection bias/confounding and limit the validity and generalizability of the findings?

Many thanks and apologize if I missed some important details of the paper before asking.

On 2020-09-09 06:55:50, user Tomasz Kolinko wrote:

very little info about the death numbers underreporting - why was 15% used as an underreporting level?

Considering the article states IFR as very low, and serorevelence numbers seem right, perhaps the number of deaths in the region in severly underestimated?

On 2020-09-09 19:13:42, user Pascal wrote:

At alpha=1 the formula diverges. This means the formula cannot be right in my opinion. Do I oversee something?

On 2020-09-10 20:53:35, user maggieclarke wrote:

So what's the association with blood type? Why didn't you say what it was? A, B O ,AB, Rh??

On 2020-09-13 07:59:08, user OxImmuno Literature Initiative wrote:

https://www.immunology.ox.a...

On 2020-09-13 16:14:46, user mzbaz wrote:

Kasim Khan created an open-source online app for easy application of the guideline: https://indoor-covid-safety...

On 2020-09-14 12:08:38, user jon curtis wrote:

Dear UCLA why not just read the end point PCR whilst on the thermal cycler, save lots of time opening plates pooling sequencing de-convaluting data. <br /> You mention using standard block based PCR which is a vast bottleneck. Have you used commercial available water bath PCR systems to process 140 384 plates an hour in endpoint 50,000 p/h.Then still quicker to just read the plate on a standard plate reader.<br /> Have I missed something..

https://www.selectscience.n...

happy to expand

Jon Curtis<br /> https://www.linkedin.com/in...<br /> https://www.medrxiv.org/con...

On 2020-09-18 17:53:41, user harrie geenen wrote:

1/ Consider air, fog or airpollution, all airborne . They can only remain airborne if enough more or less comparable particles or gasmolecules are available. if you compare the flightduration , you have to consider:<br /> The particle itself or attached to locally widely available host particle eg moisture, the microdroplets of many other persons in the party etc.<br /> 2/ the original droplets spread experiment adopted by the WHO is false because it neglects the liftsupporting of other particles.<br /> 3/ It is not difficult to do real tests of particle distribution in real life and it is also possible to take airsamples mimicing a persons load on a party evening or in other social areas. Using an infected person at least 3 meters away fom the crowd., (completely safe according health autorities). or using another marker. or giving the crowd safe air through a nose tube.<br /> Or measuring the particle distribution and copy this to a test area with an infected person.<br /> 4/ RIVM or other parties could monitor air in many places to get an impression of covid particles in an aerosol form.

5/ The virusload resonse reaction may vari very much between individuals. As long as this is the case you cannot accept a low level acceptable dose.

harrie geenen

On 2020-09-29 10:51:15, user Sanal Madhusudana Girija wrote:

Beautiful and simple! <br /> 1) It is an interesting observation, that not only the cells in the lesion but also outside the lesion suffer from telomere shortening. This means even if the lesion is excised fresh lesions can appear near by. This is a significant observation. <br /> 2) In the malignant cells, may be if you have access to metastatic lesions, you should check for telomere length. I would not be surprised the telomere length would be again "normal" or even more than "normal" cells. <br /> 3) PBMCs were a choice for control. How about cells from another area if the IEC/IRC permits!

On 2020-10-02 21:42:30, user Gabor Drotos wrote:

Dear Authors,

May I ask how a "close contact" was defined?

On 2020-10-06 15:16:42, user Kamran Kadkhoda wrote:

The specificity of the Euroimmun assay is 95%: https://pubmed.ncbi.nlm.nih...<br /> This means a lot of false positives and low PPV.

On 2020-10-07 12:44:20, user Iratxe Puebla wrote:

Review completed as part of ASAPbio’s #PreprintReviewChallenge

The study examines the incidence of heart disease deaths in the early pandemic period in the US (30 March to April 26) in areas without large COVID-19 outbreaks. The authors sought to study whether a decline in acute myocardial infarction (AMI) admissions was linked to either a higher mortality rate (which would suggest avoidance of care seeking), or lower mortality (which may suggest less triggers for AMI). The authors use data from the CDC’s s National Center for Health Statistics and apply inclusion criteria requiring >97% completeness for the data.

The study includes data from a reliable source and includes controls involving a comparison to incidence of heart disease deaths in the same period in 2019 and 4 weeks earlier in 2020. While the study is observational and can only point to trends and not explain the reported decrease in incidence of heart disease death in several states during the study period, it helps surface this trend and opens lines for further research to evaluate whether the trend will sustain over a longer period and if so, look into the potential factors behind the trend. If the trend were to sustain over time and was found not to be associated with misclassification of death cause, it may provide avenues to identify factors that can reduce triggers for AMI.

Minor comments<br /> - The authors indicate ‘The primary analysis captured 747,375,188 person-weeks for the early pandemic period and 101,620,248 person-weeks for the 2019 control period’ the number of person weeks for the control period is considerably lower, can the authors provide some context for this, and whether this may have any influence on the analysis?<br /> - The abstract indicates ‘The mean incidence rate (per 100,000 person-weeks) for heart disease in states without excess deaths during the early pandemic period was 3.95 (95% CI 3.83 to 4.06) versus 4.19 (95% CI 4.14 to 4.23) during the corresponding period in 2019’, the Results section reads ‘The mean incidence rate (per 100,000 person-weeks) for heart disease in states without excess deaths during the early pandemic period was 3.95 (95% CI 3.83 to 4.06) versus 4.35 (95% CI 4.23 to 4.48)’ it appears they need to be updated to match?

Questions for the authors<br /> - Now that we have data from four additional months into the pandemic, are the authors planning an extension to the analysis?<br /> - For the states where an increase in the incidence of heart disease deaths was observed, the authors mention the possibility of harm due to avoidance of care, misclassification during a period of excess deaths and COVID-19 itself increasing cardiovascular deaths. Do the authors think that capacity at hospitals may have been a factor behind any increase in heart disease deaths? E.g. related to prioritization of COVID-19 admissions vs others.

On 2020-10-16 12:42:55, user Christopher Leffler wrote:

This paper demonstrating the effectiveness of masks was just accepted to the first and only peer-reviewed journal we sent it to--it's pubmed-indexed, both print and online.

On 2021-08-06 10:49:36, user Kai Deng wrote:

critical information about the confounding factors missing: age, comorbidity<br /> , gender...

On 2021-08-11 05:37:53, user Rob wrote:

“In May, independent hesitancy risk factors included…having a PhD or <=high school education…”

Definitely the most fascinating aspect of these results. More research needs to be done to try to unpack the dynamics at play here.

On 2021-08-12 12:20:10, user Drewster R wrote:

I would much rather know what their PhD was in as opposed to that they were a PhD. I've met many a Phd without the good sense to change a light bulb.

On 2021-08-12 13:45:33, user Paul52 wrote:

The broader numbers don't come from polling, they come from people who saw the survey and filled it out. <br /> That kind of self-selection will produce skewered results. If 35% of the people claiming to be PhDs said they're hesitant it means that of the people who chose to answer 35% of those claiming to be PhDs answered they're not going to take the vaccine.

It doesn't mean they have PhDs.

And it doesn't mean that 35% of PhDs are hesitant.

On 2021-08-20 00:25:35, user troRx wrote:

So where are the "eMethods" they refer to? If this was driven entirely through Facebook, I would have some validity issues with applying it to the general population.

On 2021-08-22 13:09:40, user Dan Elton wrote:

A major reason for hesitancy, which is sadly not mentioned in this paper, is the lack of FDA full approval. Once again the FDA is exhibiting a lot of dysfunction and showing they can't do cost benefit analysis at all. We've had what is effectively the largest Phase IV trial in history yet the FDA won't approve it. The risks are tiny - like a few in a million - like the risk of driving for a few months.

A lot of people are holding out for the full approval. See survey results i tweeted here: https://twitter.com/moreisd...

It's easy to demonstrate that holding up the approval is leading to hundreds of thousands of unnecessary cases and a lot of unnecessary suffering and death.

also see <br /> https://www.slowboring.com/...

On 2021-08-11 20:29:39, user S.O.S_1.20.17 wrote:

Me and my husband are both over age 60, (61 and 62) we both had the Moderna shots and we had a very strong response to the second shot, husband had a 102 degree fever, I had a 101 degree fever or possibly a little higher (my digital thermometer wasn't working right, it was flashing). Anyway we had a strong response. My son who is in his 20's also had the Moderna vaccine and works in a busy supermarket. He was exposed to 3 coworkers who had Covid (they were unvaxxed). My son wore an N95 mask to work. He was tested for Covid on July 21st. The tests, PCR and Rapid both came back negative. My husband travels to NYC on public transit wearing an N95 mask. He has not gotten Covid. Vaccines seem to be working well. We are still avoiding restaurants, my son did go out to restaurants a few times with his friends who are now vaccinated.

On 2021-08-12 12:32:47, user Christopher M. Brown wrote:

This is an interesting study, but one glaring confounder which the authors do not seem to have addressed is age. Older patients, who are much more susceptible to infection and hospitalization, also tend to be the most vaccinated cohort. Additionally, older patients are more likely to be vaccinated with BioNTech than Moderna, given the earlier introduction of that product. Patient age and time since vaccination may also account for a large part of the gap seen between the two vaccines in recent estimated efficacy. An attempt should be made to stratify/analyze these data using age.

On 2021-08-12 13:20:30, user Nicolas Gambardella wrote:

Something seems wrong with the tables 3, 4, 5, reporting efficacy. In most cases (Pfizer OR Moderna) is much lower than (Pfizer PLUS Moderna), as if the cases had received both vaccines. In some cases (Pfizer OR Moderna) is higher than (Pfizer PLUS Moderna). Where are the missing cases coming from? And in some cases it is much lower, like Pfizer=5, Moderna=5, Pfizer OR Moderna=1. <br /> Now, this could be the result of the case matching algorithm?

On 2021-08-13 00:46:51, user Bung Prachya wrote:

The problem lies in the design. With case-control study, you should get only Odd ratio, not %effectiveness.

They said 80% of their population was vaccinated (the numbers seem wrong). If you found that among 1700+ covid patients, only 10 were vaccinated guys, you should think about effectiveness of 95%something.

On 2021-08-13 02:51:57, user Zachary Hadden wrote:

This makes a lot of sense as my post covid experience since last December, recovery has been slow. I coded in ICU, brought back and recovered in 14 days where they started me at 70 liters of Oxygen for 4 days and had a gradual reduction down to 1 liter when I was discharged. No cardiac issues after stress test and echocardiogram. Pulmonary breathing performance tests show I have the lungs of someone that’s been smoking all my life. I’ve never smoked. CT scan shows the lower right lobe is collapsed, but I’ve been told this should not cause my shortness of breath issues. I feel like I have a more constricted airway than pre-covid. My pulmonologist is a joke. I’ve only had one video conference call with him and have had to get these tests scheduled on my own…. even the pulmonary test. I’ve still not had a follow up call since April. There aren’t any more pulmonologist available in my area. I guess if there is any consolation with this study, patients are improving.

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 2021-01-06 18:15:01, user RT1C wrote:

minor correction: "moderate (100-101.9°F) and severe (<=102°F)." I think you meant severe to be greater than or equal to 102, not less than or equal to 102.

On 2021-01-06 18:36:37, user RT1C wrote:

In your discussion, I think you should distinguish between mechanisms proposed to work in vivo vs. those observed in vitro. For example, the high sugar concentration of honey may be antibacterial in in vitro tests/cultures, but when ingested, it will be diluted by other foods and liquids and irrelevant as a mechanism for antibacterial action. The same is true of the some the other suggested mechanisms.

On 2021-01-08 21:27:37, user Marek J wrote:

What type of honey was used? Was the cumin milled before use?

On 2021-01-25 02:24:50, user Sohaib Ashraf wrote:

Kindly contact on twitter regarding this study for questions @SohaibAshrafMD<br /> Youtube Channel Dr Sohaib Ashraf, MD

Regards,<br /> Principal Investigator HNS-COVID-PK

On 2021-08-14 21:10:03, user Daniele Sardinha wrote:

10.4236/wjv.2021.113004 <br /> Sardinha, D. , Lobato, D. , Ferreira, A. , Lima, K. , de Paula Souza e Guimarães, R. and Gondim Costa Lima, L. (2021) Analysis of 472,688 Severe Cases of COVID-19 in Brazil Showed Lower Mortality in Those Vaccinated against Influenza. World Journal of Vaccines, 11, 28-32. doi: 10.4236/wjv.2021.113004.<br /> published

On 2021-08-15 12:58:51, user Stephen B. Strum wrote:

I re-read this article in a recent "quest" to understand why we do not have surrogate virus neutralization tests (sVNTs) that are available through national labs such as LabCorp and Quest. An important publication by Goodhue Meyer led me back to the Joyner et al. paper. Here's my overall take on the Joyner paper and the issues at-large.

1. There appears to be a very excellent correlation between either natural COVID-19 infection or vaccination with the development of virus-neutralizing antibodies (NAbs).

2. The occurrence of high-titer NAbs correlates well with protection from new infection from COVID-19 and also reduces morbidity when variants of concern (VOC) cause infection in vaccinated individuals. Yet mass testing of the population has not been done because these surrogate tests are not agreed upon as to which one(s) has the greatest sensitivity & specificity for NAbs as determined in plaque reduction neutralization tests (PRNT) assays or wild-type COVID-19 assays, both of which are tedious, expensive, require BSL3 (biosafety level 3) labs and not suitable for high throughput testing.

3. Yet, as of today, 8/15/21, there exist publications showing good correlation between specific sVNT and plaque reduction neutralization tests (PRNT). In reading over 150 articles on this topic, I have not found any articles so far that have studied the Ab (antibody) test used in the Joyner study (VITROS Anti-SARS-CoV-2 IgG qualitative assay by Ortho. Please help out and identify if such articles have been published (I am still searching).

4. The FDA authorized an EUA for Ortho's VITROS test above while other assays that published their results were not used to select COVID-19 convalescent plasma (CCP) for treatment purposes.

? So how do we really know what the nAb levels were in the CCP given to patients in the study? The VITROS Ab test used is a qualitative test. At the time of publication I am fairly certain that there were no correlative studies to show that this test was accurately depicting the nAb levels using so-called gold standards.

? How, as Hllda Bastian pointed out do we accept the article at face value without a placebo control? There is a need to go over the structure of this study to ascertain if the differences in survival later reported in 2021 by Joyner et al. are sufficient to look further into CCP and if so, then what is the best way to screen for donors?

? Why are not donors selected using a sVNT that has been shown to have high correlative value vs. PRNT such as cPASS by GenScript?

? Why are not donors selected by cPASS results from those vaccinated with Pfizer or Moderna where the cPASS results can be shown to be protective against VoC such as Delta Variant (B.1.617.2)?

? Note that I am not a virologist, but a hematologist/oncologist that also happens to be immunocompromised. I assessed my nAb status with an sVNT that has been commercially available across the USA: LabCorp test code 164090: SARS-CoV-2 Semi-Quantitative Total Antibody, Spike using Roche Elecsys on a cobas 601 analyzer. With testing at one month post-Pfizer #2, my total levels were > 250 U/ml, but at 4 months later they had decreased to 59 U/ml. If these Ab levels continue to fall I will be one of the functionally un-vaccinated or under-vaccinated. This is a large group of patients in the world and a potential breeding ground for more vicious VoC. <br /> Stephen B. Strum, MD, FACP <br /> sbstrum@gmail.com

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 12:28:35, user Marco wrote:

This article is now published on Scientific Reports: https://www.nature.com/arti...

On 2021-08-21 06:47:01, user Heba A. A. Ibrahim wrote:

The dataset link is broken https://github.com/datadist... , can you provide another link for it ?

On 2021-08-23 08:47:36, user Medhat Khattar wrote:

How is it correct to have used only saline as placebo injection, when the composition of the vaccine includes a range of compounds, most notably lipids?

On 2021-08-25 17:36:55, user Bill wrote:

Well, that is it then. If you have had COVID, you do not need to get the vaccine. Only 10% of those that had it would have difficulty fighting it after 9 months! More studies say similar -- real science right here folks.<br /> https://www.nih.gov/news-ev...<br /> https://www.nature.com/arti...

On 2021-08-26 11:46:43, user Mike Kruskamp wrote:

NIH/CDC/IDSA recommend to treat patients with OS of 6 at baseline due to that being the group with statistical benefit at day 28. Will you please evaluate that same population at day 60? The current analysis at day 60 is in the entire study population which is not consistent with the 28 day analysis or guideline recommendations.

On 2021-08-26 23:02:47, user Klaskow wrote:

So when is the Peer review going to be scheduled?

On 2021-08-30 00:23:58, user Bob Robertson wrote:

The conclusions in the results section regarding relative efficacies of convalescent immunity and vaccine-induced immunity are incorrect because they are based on improper comparisons.

Using the same improper comparisons, one would conclude that a 98%-off coupon saves the purchaser twice as much as is saved by a 96%-coupon.

What should instead be compared are the magnitudes of the reductions in symptomatic infections relative to naive immunity, and reductions in hospitalizations relative to naive immunity, as well as deaths, and maybe total infections too (though this one's a bit tougher).

If you have access to Israel-based numbers, all the better, but, for now, I'll assume that the percentage of symptomatic infections in Israel is comparable to that in the US... where 85% of pre-vaccinated, first infections are symptomatic, where 5% of infections lead to hospitalizations, and where 0.64% of infections lead to death. https://www.cdc.gov/coronav...

As a rough estimate, about 540 unvaccinated people who'd not previously been infected would've gotten infected out of a group of 16,214 (based on an assumption that 20% of people get infected per year... divided by 6 to represent those likely to be infected in a two-month span).

So, to compare the efficacies of convalescent and vaccine-induced immunity at staving off all infections, we'd have to look at their reductions in infections relative to those with naive immune systems.

540-19 gives us 521 infections avoided via convalescent immunity.<br /> 540-238 gives us 302 infections avoided via vaccine-induced immunity.<br /> From there, <br /> (521-302)/302 = 0.73, <br /> so, convalescent immunity against all infections could be said to be 73% better than vaccine-induced immunity, or 1.73 times better.

Of the 540 estimated infections expected from 16,214 naively immune, 85% would've been expected to experience symptomatic infections; so that's 457 estimated symptomatic infections.

457-8 gives us 449 symptomatic infections avoided via convalescent immunity.<br /> 457-191 gives us 266 symptomatic infections avoided via vaccine-induced immunity.<br /> From there,<br /> (449-266)/266 = 0.69,<br /> so convalescent immunity against symptomatic infections could be said to be 69% better than vaccine-induced immunity, or 1.69 times better.

Of the 540 estimated infections expected from 16,214 naively immune, 5.16% would be expected to end up in the hospital; that's 28 hospitalizations.

28-1 gives us 27 hospitalizations avoided via convalescent immunity.<br /> 28-8 gives us 20 hospitalizations avoided via vaccine-induced immunity.<br /> From there,<br /> (27-20)/20 = 0.35,<br /> so convalescent immunity against hospitalization could be said to be 35% better than vaccine-induced immunity, or 1.35 times better.

Deaths were the same, so, they each seem to be 100% effective against death (compared to the 4 deaths that would've been expected in the naively immune.

Given that 20% more of the vaccinated group had comorbidities than did the previously infected group, and that there were more than 2.5 times the number of immunocompromised and more than double the number of individuals with cancer, all results should be weighted by reasonable estimates related to comorbidities' impacts on outcomes. I find it quite surprising that comorbidities would've proven to have no impact on your results, and assume there's some mistake there too.

<edit><br /> I've since been informed that the metric about which I'm whining is called relative risk, that relative risk is totally a standard metric, and that I should separate my concerns about public misunderstanding from expert publication... it'd still be cool if y'all chose to add additional metrics for plebs like myself.<br /> </edit>

On 2021-11-18 23:35:19, user Emily wrote:

Does anyone know if this study has been published yet? Don't they usually prioritize data on current health threats to get them through peer review a little faster?

On 2021-08-27 01:55:40, user Private for now wrote:

Great work. We need more of this and updates vs variants for infection and serious disease efficacy correlates. Not sure how many people would want a personalized booster schedule created, but this type of data is foundational.

On 2021-08-27 23:57:15, user Chris Woolley wrote:

Is your sample biased? A snowball sample has reported that the nurses have worked more hours than normal. Isn’t it human nature to over-exaggerate hours worked. Would it have been better to just get the factual data from the hospitals if possible?

Just looking at the nurses that worked 31-40 hours. 1/3 worked more than contracted and 15% of these claimed to have high stress. Does this not mean that only 5% of full time workers have had extra stress during COVID? Shouldn’t that be the headline?

On 2021-08-31 05:02:22, user kdrl nakle wrote:

Since contact tracing depends heavily on the level of community transmissions there is no way it can be used successfully in the situation where that level is high. The most effective measure in that situation is vaccination regardless of mathematical models.

On 2021-08-09 21:08:09, user Richter David Oliver wrote:

One major flaw of this and the "Dresden"-study is the "self-reported" questionaire. Introspection is not a scientific measurement. Particularly extremely common symptoms like "tiredness" or "headache" are not suitable to diagnose any particular condition and are basically treated as reliable long-covid markers in the study. Also age -groups around 6, most likely did not fill out the questionaire themselves. A study like this would greatly benefit from data like respirometry or any quantifiable physiological or biochemical parameter that can be objectively measured. This would also allow a single/double blinded design.

On 2020-04-23 02:46:06, user Raspee wrote:

(1) There appears to be a statistically significant imbalance in the arms with regard to disease severity.

“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.”

The base line pulse oximetry data and baseline line absolute lymphocyte count (Table 2) - indicates a statistical difference at p = 0.024 - the subjects that received hydroxychloroquine had a worse baseline respiratory status - and a worse absolute lymphocyte count p = 0.021.

This is an inherent bias in the design that has not been adequately addressed. The analysis should compare treatment in subjects with the same disease severity.

(2) If we look at table 4 - (HC + AZ) - 82% were discharged without ventilation vs. 77% discharged without ventilation both in the HC and non- HC group - Apparently the HC + AZ group did better than the other two groups.

This is supported by the observation that the adjusted HR for ventilation is 0.43 (0.16 - 1.12) - It was better than the control arm with regard to disease progression and no different than the control for death.

So in patients that were sicker at baseline, HC + AZ appears to have had a better outcome - than the other two groups - with regard to being discharged without requiring an ICU admission.

(3) Please provide a better justification to exclude the 17 women Please go back and perform the analysis including the 17 women.

(4) What were the doses of azithromycin and hydroxychloroquine administered? How are the different doses and dose regimens adjusted in the analysis? Not everyone in the HQ and HQ + AZ groups were dosed in the same fashion. Is there a minimum number of doses that you used to include them in the treatment groups?

(5) If the control group had less severe illness at presentation, it stands to reason that the mortality rate would be lowest in the control group.

(6) Was there a sub analysis looking at impact of secondary bacterial pneumonia - which occurs in 5-15% of moderate to severe COVID-19 patients? Were the antibiotics utilized the same over the 3 cohorts or were they different?

(7) How many patients were on ace inhibitors and/or angiotensin receptor blockers? Were these medications balanced in the 3 arms? What about corticosteroid use in the 3 cohorts? Was corticosteroid use balanced?

(8) Please go back and re-run the analysis with an additional 14 days of COVID-19 data (using April 25th cut -off) as your sample size will undoubtedly be greater and we would expect that the HQ + AZ group will now have a p value < 0.05. for discharge without ventilation.

(9) Please include length of stay in your analysis as well

(10) Please include readmission rates to the hospital in your analysis

On 2020-04-21 22:06:22, user Senad Hasanagic wrote:

Totally flowed retrospective analysis because baseline Clinical characteristics are missing ( not reported) in significant number of patients. So adjustments not possible.

On 2021-12-04 01:07:35, user Balazs wrote:

What were the Ct values for the positive results? <br /> Are you sure you have not investigated how many people with questionable PCR <br /> positive results ended up with another questionable PCR positive result?<br /> I thought even the WHO early Jan 2021 declared that a "case" have to <br /> have clinical signs, and PCR reports should include Ct values...

On 2021-12-06 16:42:17, user Kristi Leach wrote:

Sociology student, here, currently writing a paper on issues with the online vax schedulers and the whole idea of using them. I would like to respectfully suggest that you consider focusing on other mechanisms in addition to the city's vax distribution strategy. On March 28, we were only 6 days into phase 1B+ and 50 days into Protect Chicago Plus. Meaning shots had been available to people in Plus neighborhoods much longer than it had been available to most other residents, unless we're suggesting it would have been appropriate to divert from nursing homes, jails, and healthcare workers. That's outside of my expertise, but as a lay person, it's unconvincing. I'm piggybacking on my advisor's findings that we are neglecting the social safety net as COVID mitigation https://www.newsweek.com/wh... For example Not to mention other efforts such as contact tracing and masking. Dr. Parker mentions the lack of hospitals in Black and Brown neighborhoods.

On 2021-12-09 20:54:49, user El Fabsterino wrote:

Interesting stuff. The sample sizes are very, very small, though. I'd refrain from using p-values here at all. I'm not sure the suggested statistical test (Student's t-test) to test for differences in the means is even applicable here. The original data is clearly not normally distributed and transformed into a 0/1 Bernoulli-variable by defining an arbitrary threshold.

On 2021-12-25 13:45:26, user Blister wrote:

Interesting that most evidence used to support boosting against omicron is in vitro. If anyone has a study that shows real clinical benefit to boosting with these legacy vaccines please share. This paper is being cited by authors as supporting the use of legacy virus boosters as opposed to a new generation variant booster.

On 2021-12-11 13:48:37, user Patrick Gérardin wrote:

The paper has been accepted for publication by Travel Medicine and Infectious Disease. Attached the URL towards the publication: https://www-sciencedirect-c...

On 2021-12-13 18:28:05, user Kristen wrote:

I just stumbled across this and I wonder what impact the Mullen's norms have to do with this drop. The Mullen norms are over 20 years old and many of the VR stimuli are very outdated and are not recognizable to children born in recent years. I always prefer to give the Bayley or WPPSI if I can given this issue. It looks like there has been an overall downward trend in Mullen scores in your sample. I know you wouldn't be able to go back and compare as easily, but I wonder how the COVID-19 babies would fare on a measure with more updated norms. Bayley-4 has been freshly updated and would capture those born during the pandemic.

On 2021-12-15 06:28:56, user Robert Clark wrote:

From the article:

We used two-month periods as our basic time interval for defining the sub-cohorts, but combined months 12 to18 for the Recovered cohort and omitted months 8 to 10 for the Vaccinated and the hybrid cohorts due to the small number of individuals.

And also:

Typically, infection rates among recovered or vaccinated individuals are compared to the infection rate among unvaccinated-not-previously-infected persons. However, due to the high vaccination rate in Israel, the latter cohort is small and unrepresentative of the overall population; furthermore, the MoH database does not include complete information on such individuals. Therefore, we did not include unvaccinated-not-previously-infected individuals in the analysis.

Frankly, I don’t think the researchers are being completely open about the real reason they aren’t including the unvaccinated/uninfected in their study. The vaccination rate in Israel is about 80%. At a population of 9 million, that would mean 1.8 million unvaccinated. Obviously they could get high statistical significance with that many people.

I think the real reason is they would find the same as what was seen in the UK and in Sweden, post 6 months the vaccine effectiveness is worse than being unvaccinated to begin with.

Stunning after this length of time so many countries are refusing to present this data. They’ll collect the data up to 6 months and find the vaccine has waned to having no effectiveness in comparison to the unvaccinated. But except for Sweden and the UK, they refuse to go beyond that point.

Robert Clark

On 2021-12-23 17:01:02, user Bonnie Taylor-Blake wrote:

A quick comment, if you will. I'd urge the authors to double-check the contention that '[t]he US Surgeon General stated in 1969 that it was time to ...close the book on infectious diseases, declare the war on pestilence won.” In fact, Brad Spellberg and I looked high and low for corroboration that then-Surgeon General William H. Stewart had indeed made such a claim and we couldn't find it. Instead, we were able to discern how such a misattribution came to be. https://pubmed.ncbi.nlm.nih...

On 2021-12-23 17:28:29, user Heather Madden wrote:

Thank you for conducting this study, we were not included but as a family with a child with a ANKRD11 missense mutation that had never been seen before in a highly conserved region I was excited to see something written. I've actually had a Dr tell me missense mutations are harmless when they can pathogenic. My daughters half sister is still struggling to get a formal KBG dx, our mutation was proven pathogenic but the Dr used a different lab which did not have that data so its listed as a VUS. Frustrating for missense families, hopefully as more research is done other families won't need to go though long waits for answers.

On 2021-12-27 15:41:53, user Peter Rogan wrote:

A more recent version of this preprint has been published: <br /> Mucaki EJ, Shirley BC and Rogan PK. Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada [version 1; peer review: awaiting peer review]. F1000Research 2021, 10:1312 (https://doi.org/10.12688/f1000research.75891.1).

On 2021-12-28 17:10:57, user madmathemagician wrote:

Small whole numbers, like "daily new cases and deaths", are not even expected to obey Benfords' distribution.

Using that to "scientifically" cast doubt about the reliability of EU COVID-19 data, is just fraudulent science.

The conclusion that higher vaccination rates correlates with larger deviation from Benfords' distribution is probably just because the "daily new cases and deaths" are smaller numbers.

On 2021-12-29 01:27:15, user lowell2 wrote:

conclusion? "in Omicron cases, these findings highlight the need for massive rollout of vaccinations and booster vaccinations." how so? if the vaccines DO NOT WORK, how is massive rollout going to help? vaccines every 3 months? every month? every day? The findings indicate the vaccines need to be adjusted to function better -- to actually provide IMMUNITY for a significant period of time. Not that one needs to continually use something that is ineffective.

On 2021-12-29 09:29:29, user Željko Serdar wrote:

Although some of us do not want to listen to good advice, I still give it to you, and it is up to you to decide whether to listen to it and apply it. These are the results of an analysis of more than 42 million people and can be considered reliable, which means that preliminary studies that said that young men have a higher risk of myocarditis after infection than after vaccination were wrong. Vaccination of the elderly and at-risk is justified because it significantly reduces the risk of severe disease. Vaccination of young and healthy people carries a significant risk of myocarditis and any form of forcing young people to get vaccinated is irresponsible.

On 2022-01-02 12:06:34, user Marius wrote:

Why did you use convalescent donors that had asymptomatic SARS-CoV-2 infection?<br /> I mean, it is great that even asymptomatic convalescents have robust T-cell response…but would it not be interesting to see the immune response of convalescents with moderate Covid? Possibly because this cohort does not even catch the omicron variant that often? At least I assume that unvaccinated people with moderate Covid Display an even better T-cell response compared to the vaccinated….

On 2022-01-04 09:33:05, user Paolo Maccallini wrote:

Dear all,

I made an attempt at calculating the proportion of asymptomatic Omicron infections in function of the same parameter in the case of Delta infections, among unvaccinated individuals. I used the data presented in this paper, particularly the data relative to the subjects enrolled in the Ubunto trial (Omicron wave) and those of the population included in the Sisonke sub-study (Delta wave). The result is that, if we assume a prevalence of asymptomatic infections of 17% for the Delta variant, then we have that the prevalence of asymptomatic infections for the Omicron variant is about 60%, in unvaccinated subjects. The details of the calculation I performed can be found here: https://paolomaccallini.com...

On 2022-01-04 13:28:50, user Richard in Bosstown wrote:

One would like to know if there were people infected by prior versions were getting infected by omicron ("natural immunity").

It is possible that the omicron is an escape variant selected for among vaccinated persons given that vaccination involves only the single, spike protein of the virus. In contrast, infection with virus exposes subjects to more than 20 viral proteins, any of which can provide immunodominant peptides for an individual's MHC composition to confer T cell immunity. T cell immunity is more critical than antibody for viral resistance, though rarely measured.

With such a large number of viral protein targets for T cell recognition, the virus is much less likely to mutate during a virus's evolution to escape that "natural" T cell immunity. This is one reason why attenuated virus vaccines that include all viral proteins are generally more effective than protein vaccines. It has been suggested that natural immunity from multiprotein virus exposure is the reason the omicron surge was limited in South Africa where a much larger portion of the population was previously infected versus the US where higher proportions are vaccinated.

Vaccination is important for individuals not previously infected, that is clear, if only to reduce the severity of infections, as we deal with annually with flu vaccines. However, the lack of presentation of these prior infection data, perhaps omitted from the study design, is a significant omission that could have added to our understanding of the biology and natural history of this virus.

Richard P Junghans, PhD, MD<br /> IT Bio, LLC<br /> Boston University School of Medicine<br /> rpj@bu.edu

On 2022-01-05 01:05:11, user Paul Wolf wrote:

I would have liked to see a direct comparison to delta and omicron, which is what everyone has on their minds. This has two familiar mutations, N501Y and E484K, and no others? Where do most of them occur: on the RBD, N Terminal Domain, or furin cleavage site? Do the 46 mutations suggest a jump to another species? Omicron is acting like a completely different virus, and this one found in France is just as mutated.

On 2022-01-11 17:07:10, user Bill wrote:

Just saw a letter signed and sealed by Ministry of Health in Cameroon that expresses the displeasure of the Ministry for the preprint's methodology and apparent lack of follow up by the authors with Cameroon authorities.

On 2022-01-05 21:36:37, user Bernie Fontaine, Jr., CIH, CSP wrote:

The anedotal information is limited in population size and demographics. The study appeared to use only healthy individuals without any confounding factors. Secondly, the type of cloth mask was not identified and many people now use either N95 or KN95 respirators or double cloth masks for additional protection. The type of cloth mask was not identified. Many cloth masks may have multiple layers of material and the type of material does make a difference. In short, this study should be reviewed with caution since many variable were not considered.

On 2022-01-07 02:59:57, user Cameron Cooper wrote:

Is this the study Rand Paul is quoting?

On 2022-01-08 00:16:51, user Claudia Lupu wrote:

Excellent article, many of my friends Vax and no Vax got Covid, some fully vaxed had more severe symptoms that non vaxed because of their medical condition. This reinforce exactly what is said in the article.

On 2022-01-12 18:43:00, user Thomas R. O'Brien wrote:

This appears to be a very well-done study that provides important support for the hypothesis that Omicron is inherently less pathogenic than the Delta variant. I don’t understand the previous comments re: lack of information on age and immunization status. The paper clearly addresses those issues.

Methods:<br /> · <br /> ‘Exposures of interest included demographic characteristics of patients (age…’<br /> · <br /> ‘We additionally recorded patients’ history of a positive SARS-CoV-2 test result of any type or COVID-19 diagnosis =90 days prior to their first positive RT-PCR test during the study period, as well as the dates of receipt of any COVID-19 vaccine doses (BNT162b2 [Pfizer/BioNTech], mRNA-1973 [Moderna/National Institutes of Health], or Ad.26.COV2.S [Janssen]).’<br /> · <br /> ‘We used Cox proportional hazards models to estimate the adjusted hazard ratio (aHR) for each endpoint associated with SGTF, adjusting for all demographic and clinical covariates listed above.’

Results:

‘Adjusted hazard ratios for hospital admission and symptomatic hospital admission associated with Omicron variant infection, relative to Delta variant infection, were 0.48 (95% confidence interval: 0.36-0.64) and 0.47 (0.35-0.62), respectively (Table 1; Table S3).’

The authors did not adjust the analyses of more severe outcomes (ICU admission, ventilation, death) for age and vaccination status, but that was because too few patients who were infected with Omicron had such outcomes (despite Omicron being ~3 times more common than Delta in the study population).

To avoid this confusion, the authors might mention in the abstract that they adjusted the hospitalization analysis for age and vaccination status.

On 2022-01-14 06:53:34, user Andy Bloch wrote:

The hazard ratios for ICU admission and mortality were unadjusted. This is not clear from the abstract, but the full text explains: "The observed number of patients meeting each of these endpoints was inadequate for multivariate analyses due to the absence of counts within multiple covariate strata." Considering that non-SGTF (Delta) were more likely to be 60 or older, nearly twice as likely to be unvaccinated (49.7% v. 26.6%) and about 1/3 as likely to have had 3 shots boosted (4.6% v. 13.4%) there should have been some adjustment or stratification made, perhaps using rates from other studies. The CDC is citing this study as showing a "91% reduction in risk of mortality" and that is very misleading since the figure is unadjusted.

On 2022-01-13 18:25:17, user Mackenzie Lee wrote:

I think it's somewhat difficult to make solid claims re incident rates, etc, due to self-reported/-selected data collection via a Facebook site dedicated to survivors of COVID. The rapid data turnaround is nice of course, but a follow up with random sampling will be needed to substantiate claims.

On 2020-05-25 19:37:34, user Laurent Roux wrote:

Maybe focusing on Ab to the RDB epitope is too restricitve. A network of antibodies is likely to neutralize infectivity as well.

On 2024-02-01 13:05:45, user Robin Walters wrote:

Now published - https://doi.org/10.1093/eur...

On 2025-04-16 09:01:39, user Idan Menashe wrote:

Now published here: https://doi.org/10.1002/aur.3085

On 2020-03-06 18:29:42, user Ja Mitchell wrote:

What exactly is COVID-19?

On 2020-04-22 21:11:52, user Amy Weicker wrote:

Was zinc administered along with the CQ in this study? Not seeing it mentioned.

On 2023-06-15 13:36:40, user Rachel Gibson wrote:

This Scientific Correspondence has also been submitted to eLife.

Comment on ‘The clinical pharmacology of tafenoquine in the radical cure of Plasmodium vivax malaria: an individual patient data meta-analysis’<br /> Authors: Raman Sharma1, Chao Chen2, Lionel Tan2, Katie Rolfe1, Ioana-Gabriela Fita2, <br /> Siôn Jones2, Anup Pingle3, Rachel Gibson1, Navin Goyal4*, Isabelle Borghini Fuhrer5, <br /> Stephan Duparc5, Hema Sharma2†, Panayota Bird2<br /> Affiliations: 1GSK, Stevenage, UK; 2GSK, Brentford, UK; 3GSK, Mumbai, India; 4GSK, Upper Providence, PA, USA; 5Medicines for Malaria Venture, Geneva, Switzerland<br /> *At the time of submission of this Letter, Navin Goyal is no longer an employee of GSK and is affiliated to Johnson and Johnson<br /> †At the time of submission of this Letter, Hema Sharma is no longer an employee of GSK and is affiliated to AstraZeneca

Abstract<br /> A single 300 mg dose of tafenoquine, in combination with chloroquine, is currently approved in several countries for the radical cure (prevention of relapse) of Plasmodium vivax malaria in patients aged >=16 years. Watson et al.’s recent publication suggests, however, that the approved dose of tafenoquine is insufficient for radical cure and that a higher 450 mg dose should be recommended. In this response, the authors challenge Watson et al.’s assertion based on empirical evidence from dose-ranging and pivotal studies (published) as well as real-world evidence from post-approval studies (ongoing, therefore currently unpublished). The authors confidently assert that, collectively, these data confirm that the benefit–risk profile of a single 300 mg dose of tafenoquine, co-administered with chloroquine, for the radical cure of Plasmodium vivax malaria in patients who are not G6PD deficient, continues to be favourable.

Introduction<br /> The Plasmodium vivax malarial parasite has a major economic and public health impact, especially in regions such as East Africa, Latin America and South and East Asia.1,2 When present in blood, P. vivax can cause acute malaria with episodes of chills, fever, muscle pains and vomiting. The parasite also has a dormant liver hypnozoite stage, which can reactivate after weeks, months or years, leading to relapses and, potentially, to severe anaemia, permanent brain damage and death.1,2 For effective treatment, eradication of both the blood and liver stages of P. vivax is required (radical cure).2<br /> Since 2018, regulators from the United States initially, and subsequently from Australia, Brazil, Colombia, Thailand, Peru and The Philippines, have approved tafenoquine (as a single oral dose of 300 mg in combination with standard doses of chloroquine) for the radical cure (prevention of relapse) of P. vivax malaria in patients aged >=16 years.1,3-5 A paediatric formulation that allows weight-band-based dosing of children (aged >=2 years) and adolescents is also approved in Australia (since 2022).5 Like primaquine, tafenoquine is an 8-aminoquinoline derivative effective against hypnozoites and all other stages of the P. vivax lifecycle; however, although the World Health Organization (WHO) recommends a 7- or 14-day treatment course for primaquine, tafenoquine is the first single-dose treatment for the radical cure of P. vivax malaria and therefore has patient adherence and convenience advantages.1,3,6 Nonetheless, as an 8 aminoquinoline, the safety profile of tafenoquine is similar to that of primaquine, and both agents can cause oxidant haemolysis in people with glucose-6-phosphate dehydrogenase (G6PD) deficiency.7,8 Acute haemolysis is usually short-lived and does not need specific treatment; however, in rare cases, severe haemolysis may lead to life-threatening anaemia (requiring red blood cell transfusions) or haemoglobinuric renal failure.9 In malaria-endemic regions it has been estimated that 8% of the population are G6PD deficient, although significant variation is reported across regions, with the highest country-specific prevalence estimated in Africa and Western Pacific countries.10,11 G6PD deficiency is an X-linked disorder; males are either G6PD deficient or have normal G6PD activity, whereas females exhibit a wide range of G6PD deficiency.2 Females may be symptomatic if they are homozygous, or if they are heterozygous and inactivation of their normal X chromosome (lyonisation) is skewed towards a deficient phenotype.2,12 Caution is needed because inter-individual variability in the pattern of lyonisation may cause heterozygous females with levels of enzyme activity between 30% and 70% of normal to test as normal for G6PD deficiency using qualitative, phenotypic, rapid diagnostic screening tests.13,14 To reduce the risk of haemolysis, the G6PD status of all potential tafenoquine patients must be determined with a quantitative test capable of accurately differentiating deficient, intermediate and normal G6PD activity levels, and tafenoquine should be withheld from patients with G6PD enzyme levels below 70% of normal.3<br /> Importantly, appropriate clinical practice for the use of 8-aminoquinolines in P. vivax malaria has always been precariously balanced between providing adequate activity against hypnozoites and the real risk of haemolytic harm to patients with G6PD deficiency.15 The cautious benefit–risk balance involved with the single 300 mg dose of tafenoquine has been questioned in a recently published paper in which Watson et al., hypothesise that the current recommended dose of tafenoquine 300 mg is insufficient and that a 450 mg dose of tafenoquine would reduce the risk of relapse.16 That dose is 50% greater than the 300 mg dose approved by the US Food and Drug Administration (FDA), Australian Therapeutic Goods Administration (TGA) and other international regulatory authorities.1,3-5 Herein, the authors discuss concerns regarding the conclusions of Watson et al.<br /> • The benefit–risk profile of tafenoquine 450 mg is not appropriately considered. For example, there is minimal discussion of tafenoquine safety data and key findings from a phase 1 study in healthy female volunteers heterozygous for the G6PD Mahidol variant. This important study demonstrated not only that the haemolytic potential of tafenoquine was dose dependent but also that a single 300 mg dose of tafenoquine had the same potential to cause haemolytic harm as the WHO-recommended dose of primaquine for uncomplicated P. vivax malaria (15 mg/day for 14 days).17,18<br /> • The authors acknowledge that data from the phase 2b, paediatric, pharmacokinetic (PK) bridging study TEACH19 were not available before submission of the Watson et al. manuscript. However, in the TEACH study, in which the tafenoquine dosage in paediatric patients was chosen to match blood exposure in adults receiving 300 mg, tafenoquine was efficacious and generally well tolerated: no patients withdrew from the study because of adverse events.19<br /> • The model used by Watson et al. to predict the recurrence-free rate at 4 months after a 450 mg dose is hypothetical and does not consider data regarding the tafenoquine exposure–response relationship. Importantly, tafenoquine exposure achieved with a single 300 mg dose approaches the plateau of the exposure–response curve; therefore, the incremental recurrence-free rate gained by the proposed 50% increase in dose is small and unlikely to be justified by overall benefit–risk considerations.3 In addition, as primaquine and tafenoquine have different PK and metabolic profiles, the authors consider the extrapolation of data from primaquine to tafenoquine to be problematic.2,9<br /> • The authors feel that, overall, some of the conclusions do not acknowledge evidence-based safety concerns for a >300 mg dose of tafenoquine and do not consider additional data from the INSPECTOR study that the recurrence rate of P. vivax infection within 6 months of tafenoquine treatment was not significantly affected by bodyweight.20<br /> Watson et al. mentioned the phase 2b dose-selection study (DETECTIVE) of tafenoquine,21 from which a single 300 mg dose was chosen for phase 3 evaluation in adults. However, the authors did not point out that, in this study, exposure was a significant predictor of efficacy and doubling the tafenoquine dose from 300 mg to 600 mg was associated with only a marginal increase (from 89.2% to 91.9%) in the primary efficacy endpoint, relapse-free efficacy at 6 months.21 Moreover, in addressing the INSPECTOR study of tafenoquine in Indonesian soldiers, the authors did not specify that this was a study of tafenoquine administered with an artemisinin-based combination therapy rather than chloroquine and, as such, is not directly comparable due to poorly understood but confirmed interactions impacting tafenoquine efficacy.20 Watson et al. also suggest that tafenoquine 300 mg is likely inferior to ‘optimal primaquine regimens’, but it is unclear whether such regimens are the WHO-recommended schedules of primaquine or regimens defined as optimal based on non-regulatory studies of primaquine. The authors provided no specific reference or dosage characterising optimised primaquine therapy, so this a priori inferiority cannot be evaluated.<br /> Methods<br /> The hypothetical causal model proposed by Watson et al. for the clinical pharmacology of tafenoquine for the radical treatment of P. vivax malaria is similarly problematic. Central to this model are methaemoglobin (MetHb) production and active metabolites. However, MetHb is not a validated biomarker of tafenoquine efficacy, and currently there is no evidence, from non-clinical or clinical studies, of circulating active metabolites of tafenoquine; if such metabolites were fleetingly present, they would require extraordinary potency to exert any significant pharmacodynamic effect.22<br /> Regarding radical curative efficacy, Watson et al. selected P. vivax recurrence within 4 months as their primary endpoint. However, the trial-defined primary endpoint at 6 months from the pivotal tafenoquine clinical trials8,21,23 was an FDA requirement and was mandated for analysis purposes. This was to maximise the probability of capturing relapses, including those from regions with longer latency periods. Watson et al. used the INSPECTOR study20 as one of two reasons to justify the selection of a 4-month endpoint. Relapse rates differ greatly from country to country, so the duration of the endpoint should not be based on rates observed in a single country. Moreover, the 6-month rate of loss to follow-up (only 9.1%) does not justify a change of treatment endpoint from 6 months to 4 months.<br /> In their efficacy models, Watson et al. explored the association between the odds of P. vivax recurrence and the following predictors: mg/kg dose of tafenoquine; AUC0–?; peak plasma tafenoquine concentration; terminal elimination half-life; and Day 7 MetHb level. However, details of how the best predictor was selected and how statistical significance was judged were not provided.<br /> Results<br /> Use of a 4-month versus 6-month follow-up period<br /> A key focus of the Watson et al. manuscript is that the authors describe a possible association between tafenoquine mg/kg dose and the odds of recurrence (using logistic regression), with a 4-month rather than the original 6-month follow-up. An odds ratio of 0.66 (95% confidence interval [CI]: 0.51, 0.85) is cited by Watson et al. in their analysis of the effect of tafenoquine mg/kg dose in patients who received tafenoquine 300 mg, but descriptive details for this result and the analysis are limited. Figure 2 in the Watson et al. manuscript shows Kaplan–Meier survival curves for time to first recurrence, based on tafenoquine mg/kg dosing category, but some areas require clarification, such as how the dosing bands were selected.<br /> Rationale for tafenoquine dose selection<br /> Importantly, the classification and regression tree analysis, in which a clinically relevant breakpoint tafenoquine AUC value of 56.4 ug·h/mL was identified, was not discussed.24 Population PK modelling revealed that tafenoquine 300 mg would provide systemic exposure greater than or equal to the AUC breakpoint in approximately 93% of individuals, who would have a high probability (85%; 95% CI: 80, 90) of remaining relapse-free at 6 months.24 Therefore, this ‘… model-based approach was critical in selecting an appropriate phase 3 dose’ for tafenoquine.24 Although data from the TEACH paediatric study19 were not available when Watson et al. conducted their analysis, had the data been available, they would have validated the AUC approach to tafenoquine dose selection, with an overall efficacy of approximately 95%.19 Individuals (aged 2–15 years) were given tafenoquine, based on bodyweight, to achieve the same median AUC as the 300 mg dose in adults (children weighing >10–20 kg received tafenoquine 100 or 150 mg; >20–35 kg received 200 mg; and >35 kg received 300 mg). The recurrence-free rate at 4 months was 94.7% (95% CI: 84.6, 98.3),19 and the TEACH study supported the successful approval of tafenoquine for children aged 2–16 years by the Australian TGA in March 2022.5<br /> Another important counter to the mg/kg-based dose selection is that, when bodyweight categories were fitted as a continuous variable in the INSPECTOR study (using data for the time to recurrence for all participants), neither bodyweight nor bodyweight-by-treatment interactions were statistically significant (p=0.831 and p=0.520, respectively).20<br /> Use of an unvalidated biomarker<br /> Although Watson et al. state that increases in blood MetHb concentrations after tafenoquine administration were highly correlated with mg/kg dose, no correlation coefficients were presented. It should also be re-emphasised that MetHb is not a validated, surrogate biomarker of antimalarial treatment efficacy as a radical cure for P. vivax malaria and was used as a safety measure in the INSPECTOR study.20<br /> Potential safety concerns<br /> In the Tolerability and safety section, Watson et al. state that severe haemolytic events were rare; however, this is because all the studies were randomised and controlled, which excluded patients with <70% G6PD activity. In addition, no mention was made that, in one of the constituent studies (which examined the dose–response for haemoglobin decline in participants with 40–60% G6PD enzyme activity),17 dose escalation of tafenoquine from 300 mg to 600 mg was not attempted due to safety concerns about potential haemolysis in patients with G6PD deficiency. In tafenoquine-treated patients in the real-world setting, some instances of severe haemolysis might be expected, and it is already known from the previously highlighted phase 1 study that the haemolytic potential of tafenoquine increases with increasing dose.17 Watson et al.’s Tolerability and safety section also mentions that one tafenoquine-treated patient had a >5 g/dL decrease in haemoglobin level, but the baseline haemoglobin level and tafenoquine dose are not mentioned. The section may have benefitted from a holistic discussion of safety parameters per tafenoquine dose group: for example, the occurrence of serious adverse events, gastrointestinal adverse events (beyond the selective discussion of vomiting within 1 hour post dose) and neuropsychiatric adverse events.<br /> Discussion<br /> Watson et al. conclude that ‘the currently recommended adult dose is insufficient … increasing the adult dose to 450 mg is predicted to reduce the risk of relapse’; however, the authors have raised several concerns relating to these conclusions. In particular, the authors feel that the safety concerns associated with a higher-than-approved tafenoquine dose have not been thoroughly considered: the safety analysis is limited, and the increased risk of haemolysis in patients with G6PD deficiency that a 450 mg tafenoquine dose (which is 50% greater than the approved 300 mg dose) would pose in vulnerable populations in limited-resource settings is not adequately discussed. In some malaria-endemic regions, 8% of the population may be G6PD deficient, although wide variability exists, and in sub Saharan Africa and the Arabian peninsula the prevalence of G6PD deficiency may exceed 30%.10,11 Therefore, in regions with fragile healthcare systems and limited availability of relevant testing for G6PD deficiency, potential exists for a significantly increased risk of haemolysis if tafenoquine is administered at an above recommended dose (450 mg). Importantly, off-label use of a dose not robustly evaluated in clinical trials would pose a considerable risk to patient safety.<br /> Regarding tafenoquine efficacy, the rationale for a dose increase to 450 mg has limitations. Watson et al. suggest that a 50% increase in the adult dose of tafenoquine (from 300 mg to 450 mg) would prevent one relapse of malaria for every 11 patients treated. However, this number-needed-to-treat estimate is not balanced by a number-needed-to-harm estimate for acute haemolytic anaemia. In addition, the phase 2b part of the DETECTIVE study21 showed that, in countries where the trial was carried out, single doses of tafenoquine 300 mg and 600 mg had similar relapse-free efficacy at 6 months (89.2% and 91.9%, respectively); therefore, the lack of additional benefit for tafenoquine 600 mg in DETECTIVE and the phase 1 study, which demonstrated dose-dependent haemolytic potential for tafenoquine, favour a 300 mg dose.<br /> In summary, based on currently available data, dosing tafenoquine at the approved 300 mg dose, in combination with chloroquine, carefully balances efficacy and safety in the radical cure of P. vivax malaria; indeed, tafenoquine 300 mg demonstrated a favourable benefit–risk profile in a comprehensive clinical development programme that included at-risk populations in regions with fragile or resource-restricted healthcare systems. The arguments raised by Watson et al. come with the concerns articulated here, and the authors confidently assert that a tafenoquine dose increase from 300 mg to 450 mg is not supported by available fact-based evidence for the radical cure of P. vivax malaria in adults aged >=16 years.

References<br /> 1. GSK. US FDA approves Krintafel (tafenoquine) for the radical cure of P. vivax malaria [press release]. July 20, 2018. https://www.gsk.com/en-gb/media/press-releases/us-fda-approves-krintafel-tafenoquine-for-the-radical-cure-of-p-vivax-malaria/ (accessed 26 April 2023).<br /> 2. Hounkpatin AB et al. Clinical utility of tafenoquine in the prevention of relapse of Plasmodium vivax malaria: a review on the mode of action and emerging trial data. Infect Drug Resist 2019;12:553–570.<br /> 3. GSK. Krintafel. Highlights of prescribing information. https://www.accessdata.fda.gov/drugsatfda_docs/label/2018/210795s000lbl.pdf (accessed 26 April 2023).<br /> 4. GSK, Medicines for Malaria Venture. Perú becomes second malaria-endemic country in Latin America to approve single-dose tafenoquine for radical cure of P. vivax malaria [press release]. https://www.vivaxmalaria.org/sites/pvivax/files/content/attachments/2021-01-25/GSK%20-%20MMV%20PRESS%20RELEASE%20TAFENOQUINE%20APPROVED%20IN%20PERU.pdf (accessed 26 April 2023).<br /> 5. Medicines for Malaria Venture. Single-dose Kozenis (tafenoquine) approved for children with Plasmodium vivax malaria by Australian Therapeutic Goods Administration. https://www.mmv.org/newsroom/press-releases/single-dose-kozenis-tafenoquine-approved-children-plasmodium-vivax-malaria (accessed 26 April 2023).<br /> 6. World Health Organization. WHO guidelines for malaria, 14 March 2023. https://www.who.int/teams/global-malaria-programme (accessed 26 April 2023).<br /> 7. Milligan R et al. Primaquine at alternative dosing schedules for preventing relapse in people with Plasmodium vivax malaria. Cochrane Database Syst Rev 2019;7:CD012656.<br /> 8. Llanos-Cuentas A et al. Tafenoquine versus primaquine to prevent relapse of Plasmodium vivax malaria. N Engl J Med 2019;380:229–241.<br /> 9. Baird JK. 8-Aminoquinoline therapy for latent malaria. Clin Microbiol Rev 2019;32.<br /> 10. Howes RE et al. G6PD deficiency prevalence and estimates of affected populations in malaria endemic countries: a geostatistical model-based map. PLoS Med 2012;9:e1001339.<br /> 11. P. vivax information hub. G6PD global prevalence. https://www.vivaxmalaria.org/diagnosis-treatment/g6pd-deficiency/g6pd-global-prevalence#:~:text=G6PD%20Global%20Prevalence,-Photo%3A%20Jaya%20Banerji&text=G6PD%20deficiency%20affects%20around%20400%20million%20people%20globally (accessed 26 April 2023).<br /> 12. Domingo GJ et al. Addressing the gender-knowledge gap in glucose-6-phosphate dehydrogenase deficiency: challenges and opportunities. Int Health 2019;11:7–14.<br /> 13. Chu CS et al. Haemolysis in G6PD heterozygous females treated with primaquine for Plasmodium vivax malaria: a nested cohort in a trial of radical curative regimens. PLoS Med 2017;14:e1002224.<br /> 14. Baird JK et al. Noninferiority of glucose-6-phosphate dehydrogenase deficiency diagnosis by a point-of-care rapid test vs the laboratory fluorescent spot test demonstrated by copper inhibition in normal human red blood cells. Transl Res 2015;165:677–688.<br /> 15. Shanks GD. Historical 8-aminoquinoline combinations: not all antimalarial drugs work well together. Am J Trop Med Hyg 2022;107:964–967.<br /> 16. Watson JA et al. The clinical pharmacology of tafenoquine in the radical cure of Plasmodium vivax malaria: An individual patient data meta-analysis. Elife 2022;11:e83433.<br /> 17. Rueangweerayut R et al. Hemolytic potential of tafenoquine in female volunteers heterozygous for glucose-6-phosphate dehydrogenase (G6PD) deficiency (G6PD Mahidol variant) versus G6PD-normal volunteers. Am J Trop Med Hyg 2017;97:702–711.<br /> 18. World Health Organization. Guidelines for the treatment of malaria, 3rd ed. https://apps.who.int/iris/handle/10665/162441 (accessed 26 April 2023).<br /> 19. Velez ID et al. Tafenoquine exposure assessment, safety, and relapse prevention efficacy in children with Plasmodium vivax malaria: open-label, single-arm, non-comparative, multicentre, pharmacokinetic bridging, phase 2 trial. Lancet Child Adolesc Health 2022;6:86–95.<br /> 20. Sutanto I et al. Randomised, placebo-controlled, efficacy and safety study of tafenoquine co-administered with dihydroartemisinin-piperaquine for the radical cure of Plasmodium vivax malaria (INSPECTOR). Lancet Infect Dis [2023 May 23:S1473-3099(23)00213-X doi: 101016/S1473-3099(23)00213-X Epub ahead of print PMID: 37236221].<br /> 21. Llanos-Cuentas A et al. Tafenoquine plus chloroquine for the treatment and relapse prevention of Plasmodium vivax malaria (DETECTIVE): a multicentre, double-blind, randomised, phase 2b dose-selection study. Lancet 2014;383:1049–1058.<br /> 22. GSK. Investigator brochure. Data on file.<br /> 23. Lacerda MVG et al. Single-dose tafenoquine to prevent relapse of Plasmodium vivax malaria. N Engl J Med 2019;380:215–228.<br /> 24. Tenero D et al. Exposure-response analyses for tafenoquine after administration to patients with Plasmodium vivax malaria. Antimicrob Agents Chemother 2015;59:6188–6194.

Authors’ contributions<br /> Hema Sharma, Lionel Tan, Katie Rolfe, and Navin Goyal contributed to the conception or design of the studies the paper contains data from. All authors contributed to data analysis or interpretation. All authors contributed to the development and writing of this correspondence and approved the final submitted version.

Conflicts of interest statements <br /> Raman Sharma, Siôn Jones, Rachel Gibson, Katie Rolfe, Lionel Tan, Ioana-Gabriela Fita, Chao Chen, Panayota Bird, and Anup Pingle are employees of, and shareholders in GSK.<br /> Hema Sharma is a former employee of GSK, a shareholder in GSK and a current employee of AstraZeneca. Navin Goyal is a former employee and shareholder in GSK and a current employee of Johnson and Johnson. Isabelle Borghini Fuhrer and Stephan Duparc have no conflict of interest to report. <br /> Acknowledgements <br /> Medical writing support was provided by David Murdoch, a contract writer working on behalf of Apollo, and Alex Coulthard of Apollo, OPEN Health Communications, funded by GSK Biologicals SA, in accordance with Good Publication Practice 3 (GPP) guidelines (www.ismpp.org/gpp-2022) "www.ismpp.org/gpp-2022)").

Funding<br /> Funding for this article was provided by GSK Biologicals SA.

Data availability<br /> Data sharing is not applicable to this article as no datasets were generated or analysed.

On 2020-04-07 18:43:25, user Ethan Obie Romero-Severson wrote:

This article has been published in EID https://wwwnc.cdc.gov/eid/a...

On 2020-06-03 14:31:19, user Nick Bauer wrote:

Your paper specifically picks out "A-positive" individuals. I may be missing something, but I don't see any discussion of Rh factor in the text or presence in the statistics?

On 2020-04-11 00:50:14, user Kirsten McEwen wrote:

There's clearly a need to monitor COVID-19 sequence mutations over primer sites. Is there an initiative to share this info among testing facilities?

On 2020-06-10 22:02:36, user mark wrote:

There seems to be an error that needs to be corrected in this line: "Results: Univariate analysis showed lower mortality in the ivermectin group (25.2% versus 15.0%......"

On 2021-01-12 19:27:05, user Antonio Bernabe-Ortiz wrote:

A little favor to the authors... please adjust the estimates by ischemic heart disease as there is a potential disbalance between arms as seen in Table 2... thanks...

On 2020-06-12 15:57:05, user Rosemary TATE wrote:

What is the correlation hypothesis? With all due respect I think that a course in statistics could be very beneficial for the author.

On 2020-04-15 12:57:31, user ZStat wrote:

When will the studies be done for patients who get HCQ right after diagnosis of covid19 ? Anybody doing these studies with a control group ? We need to know if HCQ effective if given early.

On 2020-06-22 14:22:44, user Valentina Viego wrote:

Forthcoming in Ciencia e Saude Coletiva

On 2020-05-07 03:52:42, user Alisha Geldert wrote:

We thank the authors for their detailed analysis of a suite of N95 decontamination approaches, with specific appreciation for the direct applicability to medical center needs. We see the manuscript – once published in a peer-reviewed journal – as being an excellent resource for medical center decision makers, as well as those working to implement the decontamination methods. With a spirit of attention to the existing peer-reviewed literature and rigor needed in this crisis, we offer a review of areas where improvements would benefit the study as well as (and more importantly) any readers who may adopt the approaches. The authors are aware of the following major comments summarized below, and are working diligently to provide necessary clarifications and revisions.

1. The UV-PX experimental design and choice of combination approach does not appear to be consistent with evidence on effective approaches for UVGI/UV-C ultraviolet decontamination of N95s, presenting a major concern. To address this, consider providing a reader with clearer justification for the ‘unconventional’ approach by perhaps answering the following questions:<br /> ---Were longer duration UV-PX treatments investigated? The fluence delivered during the 5-minute treatment time is unsupported by the evidence for UV-C decontamination of N95s [Lore et al., 2012; Mills et al, 2018; Heimbuch & Harnish, 2019].<br /> ---It is not clear why the authors suggest coupling of UV-PX with moderate RH heat before testing UV-PX alone, when the benefit of adding UV-PX is not described (perhaps stemming from the very low pathogen inactivation observed with UV-PX alone, as would be expected from the ~50X too low delivered germicidal fluence using this protocol). As the protocol deviates from CDC guidance [CDC, 2020], a rationale and supporting peer-reviewed references would be essential.

2. Important details are missing in the methods section. Please provide key details about the UV-PX setup to ensure replicable research reporting, specifically:<br /> ---Measures taken, if any, to ensure respirators are directly illuminated on both sides. <br /> N95 respirator placement relative to and distance from the light source. As irradiance, and therefore fluence, depends on distance between source and target, this is a critical parameter.<br /> ---Please specify the reflective material used in the UV room, the make and model number of the flame irradiance spectrometer, and whether the irradiance measurements reported in Supplementary Table 3 were measured within the UV room with reflective walls or within an alternative setting. Do the irradiance measurements represent the irradiance at the side of the N95 facing the Xenex UV-PX source or irradiance at areas indirectly exposed to UV light? <br /> ---Please clarify whether the measured irradiance represents the irradiance of one pulse or the average irradiance over multiple cycles.

3. There appears to be a potential issue with the conclusions reported in the abstract: the specific experimental parameters shown to yield high levels of pathogen inactivation (moderate RH heat) were not tested for N95 function, so the following statement might be confusing or misleading:<br /> “High levels of biological indicator inactivation were achieved following treatment with either moist heat or VHP. These same treatments did not significantly impact mask filtration or fit.”<br /> The limitations of the proposed approaches and the need for additional testing should be clarified.

References cited: <br /> 1. Lore et al., 2012: https://academic.oup.com/an...<br /> 2. Mills et al., 2018: https://www.ncbi.nlm.nih.go...<br /> 3. Heimbuch & Harnish, 2019: https://www.ara.com/sites/d...<br /> 4. CDC guidance on N95 decontamination: https://www.cdc.gov/coronav...

On 2020-02-10 20:39:56, user Hoku Toki wrote:

Would be interesting to supplement positions median with mean to evaluate the degree of symmetry of the distribution, and dispersion stats as SD. For ex on age.

On 2020-02-15 18:42:07, user Giuseppe Lapadula wrote:

How was determined the index date for calculating the incubation period? How can it be 0 in some patients?

On 2020-09-14 12:51:47, user Iván Williams wrote:

Simple and useful methodology, thanks. I think there is a lag of two weeks between onset and death, so maybe the estimated stock could be lagged too.

On 2020-05-12 04:19:20, user Gordon Lehman wrote:

Testing so far has not been rigorous or systematic. Solely based so far on clinical and primary care presentations, and who shows up at burger king drive byes.

On 2020-05-12 13:44:41, user Abdul Mannan Baig wrote:

What a brilliant contribution to ongoing COVID-19 research.<br /> The olfactory bulb findings took the science way forward to understand the loss of smell and taste.<br /> Wow<br /> Abdul Mannan Baig

On 2020-04-19 19:05:33, user Isaac barr wrote:

If so many are immune do we need strict closures?

On 2020-05-15 08:56:29, user Pavel Valerjevich Voronov wrote:

Am I getting it right - AB hardest to infect, but also most deadliest if infected?..

On 2020-03-23 20:09:08, user halrhp wrote:

wha is the mechnism that changes at 2 m? Gravity or particle mass or both. my guess is the combination. ahow large are COV19 virus droplets. Y. Li is very smart.

On 2020-05-22 14:10:19, user C'est la même wrote:

The very high female proportion and narrow recruitment strategy suggest these results might not represent the community as a whole, due to participation and response biases.

On 2021-11-20 21:08:59, user MICHAEL A WALLACH wrote:

Does the data include unvaccinated workers in the study who never tested positive for covid? I assume it does but was not addressed. How did they compare with the two groups compared in the study?

On 2023-12-15 14:30:33, user Crambert wrote:

GDF15 has also a proliferative effect on renal cells in response to K restriction and acidosis via ErbB2 activation:See Acta Physiol (Oxf). 2023 Oct;239(2):e14046. doi: 10.1111/apha.14046 and Acta Physiol (Oxf). 2021 Jul;232(3):e13661. doi: 10.1111/apha.13661

On 2023-12-19 10:26:31, user Jaspreet Mahindroo wrote:

This article has been published in the Janapanese Journal of Infectious Diseases following peer review and can be viewed on the journal’s website at https://doi.org/10.7883/yok...

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 2024-02-26 17:14:48, user Ciarán McInerney wrote:

It is admirable that<br /> the authors followed the STROBE guidelines but this study is not an<br /> observational study. Instead, it is about building a prediction model so a more<br /> appropriate guideline to follow is TRIPOD (doi: 10.7326/M14-0698). The authors<br /> should also follow the guidelines of the PROGRESS framework for researching<br /> clinical outcomes (doi: 10.1136/bmj.e5595, 10. 1371.journal/pmed.1001380, 10.1371.journal/pmed.1001381,<br /> 10.1136/bmj.e5793).

On 2024-04-21 00:21:38, user Alan Olan wrote:

This article has been published in the journal of “Biology and Medicine” as “Method of Combining Multiple Researches to Determine Non-Infectious Disease Causes, Analysis of Depression and Celiac Disease Causes” and available at - www.walshmedicalmedia.com/o...<br /> The appendix of this article is available at www.walshmedicalmedia.com/s...`

On 2024-05-10 00:42:15, user Jess Keller wrote:

Thank you for conducting this important research. I have been going through TSW for 2.5 years and the lack of understanding or consensus within the medical community has made it extremely difficult. We desperately need more research like this in order to start to understand who gets TSW, why and what the treatment options there are.

On 2024-05-15 02:55:28, user Filip Scheperjans wrote:

Hi!

Interesting findings, congratulations! Nice that you were able to reproduce the finding with multiple approaches.

We looked at antibiotics and PD risk in Finland and found associations (PMID: 31737957). Maybe worth discussing. :) It seems you did not link antibiotics to PD risk, but only to disease severity. Would it be possible to analyze association with PD risk also?

Overall, I am surprised by the low exposure to tetanus vaccination (1,6-3,2%). I would expect this to be higher in Scandinavia. At least in Finland, we vax children and then at 25-, 45- and 65 years. Also boosters are given if you get treated for a dirty wound and there is >10 years since last vaccination. If that is also the case in Israel, could there be a potential confounding effect of physical activity -> increasing risk for wounds -> increasing vax-boosters (both decreasing PD risk)?

Interestingly, there is quite some research going on into potential neuroprotective effects of the Tetanus toxin: https://pubmed.ncbi.nlm.nih...

An interesting, but complicated topic. :)

BR<br /> Filip

On 2024-07-11 13:28:54, user Kevin Kavanagh wrote:

The abstract states "Importantly, the benefits of vaccination outweighed the risks in controlling the post-COVID-19 GBS burden, although significant disparities in vaccination coverage existed between countries." I believe this is poorly worded, since it implies the vaccines are not a benefit in controlling GBS. The study's results clearly stated, "We observed significantly negative correlations between COVID-19 vaccination coverage rates and both overall and COVID-19-specificage-standardized YLD rates of GBS in 2021 (table 2 and supplementary figure S16-S17)."

I would suggest rewording to "Importantly, vaccination had significant benefits in controlling the post-COVID-19 GBS burden, although significant disparities in vaccination coverage existed between countries"

"

On 2024-07-15 15:55:06, user Tamara Pemovska wrote:

This preprint has now been published in Psychological Medicine: https://doi.org/10.1017/S0033291724001089

On 2024-07-15 22:25:43, user Ashraf Fawzy wrote:

A peer reviewed version of this article has been published in the American Journal of Respiratory and Critical Care Medicine: https://www.atsjournals.org/doi/abs/10.1164/rccm.202401-0036LE

On 2024-07-22 18:26:39, user Harmen Draisma wrote:

Figure 1A "WES", "10,463,945 (NC[, Non-coding presumably])" seems to be at variance with page 4 "WES ... 10,463,945 were in coding regions"?

On 2024-08-22 14:41:40, user Gabriel Baldanzi wrote:

Hi. This paper is now published in Circulation https://doi.org/10.1161/CIRCULATIONAHA.123.063914

On 2024-09-18 19:46:20, user Zach Hensel wrote:

The discussion notes: "One possible explanation for the anomalies observed in this paper is data errors."

This is the explanation. No further studies are needed.

Dropout artifacts in amplicon sequencing for the regions discussed in this paper are well known and described in numerous papers and technical reports. Novel mutation patterns in Omicron led to failures to amplify regions of the genome. This sometimes leads to assembly artifacts.

An expectation from this is that assembly artifacts will often include mutations from another common circulating lineage.

A cursory search for one of the variants described here (BA.1.1 with reversions of K417N, N440K, and G446S; 1/Dec-27/Dec/2021; USA) finds that 31% of such sequences carried L452R. This Delta-defining mutation was found in nearly 100% of non-Omicron sequences during this period. It was rarely found in Omicron sequences outside of sequencing artifacts.

I have not read further to know why USA is singled out as an anomaly or why BA.1.1 is discussed rather than BA.1; the same artifacts are observed for both.

Proposing "non-natural spread of infection" without conducting such a basic sanity check is inexplicable.

On 2024-09-23 06:08:48, user Stuart Quan wrote:

This preprint is now published and is available in PubMed Central. The citation is:<br /> Singh V, Haynes PL, Quan SF. Assessing Depression and Suicidality Among Recently Unemployed Persons with Obstructive Sleep Apnea and Socioeconomic Inequality. Southwest J Pulm Crit Care Sleep. 2022 May;24(5):81-88. doi: 10.13175/swjpcc020-22. Epub 2022 May 16. PMID: 35702528; PMCID: PMC9190213.

On 2024-10-16 04:19:43, user CDSL JHSPH wrote:

I found this article very informative, I very much liked the introduction piece. I do have some hiccups in regards to the methods and some of the displaying of the results. I feel as through the explanation for the methods could use some work. When I read it I felt slightly overwhelmed because of the information. The same could be said of the results. I feel as though the results section did not explain the content well enough to where I was able to completely tell results from the presented figures. I think this issue could be solved by adding more explanations into the introduction or possibly adding more to the figures' subtext. Overall, I very much enjoyed the article and found the subject matter very exciting.

On 2024-10-18 23:25:57, user CDSL JHSPH wrote:

Your research provides valuable insights that could shape the future of antibiotic and TB treatment trials.This article adapted model-based dose-ranging techniques for duration-ranging in TB trials. The findings show that model-based methods outperform traditional qualitative approaches, especially in estimating the minimum effective duration and fitting duration-response curves, even with limited sample sizes. The study also aligns well with global TB treatment goals and emphasizes the need for more efficient, shorter regimens. However, it could benefit from more detailed guidance on real-world application and strategies for managing sample size variability and patient characteristics in trials.

On 2024-10-19 10:44:10, user CDSL JHSPH wrote:

Thank you for sharing this insightful work on optimizing antibiotic treatment duration using model-based approaches. Your adaptation of MCP-Mod for duration-ranging trials is an innovative application, and the findings offer promising implications for future clinical trials and antibiotic stewardship. I particularly appreciate how the study addresses the limitations of traditional qualitative methods, and the simulations clearly demonstrate the strengths of MCP-Mod in identifying the shortest effective treatment duration.

While the study is well-executed, validating MCP-Mod with real-world clinical data would further strengthen the conclusions. Pilot trials with actual patient outcomes could provide practical evidence of its utility beyond the simulated environment. It would also be helpful to include a discussion of how your findings could be generalized across different infections or antibiotic classes, as this would enhance the broader applicability of your work. Additionally, incorporating visual comparisons of qualitative models, such as plotting duration-response curves for linear splines and other methods, would give readers a clearer view of how MCP-Mod stands out.

Lastly, a deeper discussion of the assumptions and potential challenges in real-world adoption would offer practical guidance for future researchers or clinicians who may want to apply this methodology in their own trials. Overall, your study is a significant step forward in optimizing antibiotic treatment duration, and I look forward to seeing how these methods evolve in future research and clinical applications.

On 2025-10-21 00:30:29, user CDSL JHSPH wrote:

Hello!

I really enjoy reading your paper. It is inspiring that model-based techniques such as MCP-Mod and FP1 work better than traditional Dunnet test in determining the minimum effective duration (MED) in phase II trials. It offers reliable and efficient insights into estimation of optimal antibiotic treatment durations.

Its application to advancing WHO’s End TB targets makes it a significant contribution. The methodology is convincing. It clearly outlines the limitations of traditional pairwise comparison methods, emphasizing why a shift toward model-driven designs is necessary. The experiments are well designed. It would be more convincing by applying real world data in the models. And this is the most important limitation and what I highly recommend to dig in the future.

The writing is logical and ideas are well- presented. It follows the modern scientific literature structure. The main takeaway for other researchers I think is that rather than developing entirely new tools, researchers can improve and reuse existing and proven frameworks to solve similar problems. This helps reducing redundancy and deeper developing a proven foundation.

On 2024-12-10 13:41:12, user xPeer wrote:

Courtesy review from xPeerd.com

Summary<br /> The paper investigates whether urinary prostaglandin levels can be used as biomarkers for predicting labour, both at term and preterm. It involved a cohort study measuring prostaglandin metabolites in pregnant individuals, divided into several groups. The study concludes that while certain prostaglandins increase during labour, none of them show significant changes before labour onset, thus limiting their utility as predictive biomarkers. Additionally, several non-prostaglandin eicosanoids were explored, opening new potential avenues for further research.

Potential Major Revisions<br /> - Validity of Biomarker Prediction: The study asserts that the measured prostaglandin metabolites do not significantly change before labour onset, thus cannot be relied upon as predictive markers for labour. This raises doubts about the foundational hypothesis and merits a deeper exploration or re-framing of the research focus .<br /> - Sample Size and Group Classification: The number of participants in certain subgroups was limited, which may affect the reliability of the results. Specific sub-groups, especially those with preterm labour, should be expanded to enhance statistical power and conclusiveness.<br /> - Comparative Differences in Biomarker Levels: It's essential to clarify the lack of significant differences in prostaglandin levels between preterm labour and threatened preterm labour groups to avoid generalizing results. This would involve in-depth discussion on the clinical nuances and the potential impact on clinical practice.<br /> - Extended Data Analysis: The paper's discovery of new eicosanoids demands rigorous validation and replication in larger cohorts to substantiate these findings and confirm their relevance to labour prediction.

Potential Minor Revisions<br /> - Typographical and Formatting Errors: Ensure consistency in terminology and correct minor typographical errors such as the inconsistent representation of certain molecular names across different sections.<br /> - Detailed Data Presentation: Present the raw data and statistical methodologies more transparently in supplementary materials. Consider adding error bars in figures where statistical significance is discussed, providing a clearer depiction of variance and confidence intervals.<br /> - Clarity in Methods Section: Improve the descriptions of the experimental protocols, especially the mass spectrometry-based lipidomics analysis, to enhance reproducibility and understanding.<br /> - Graphs and Tables Enhancement: Ensure all graphical representations are adequately annotated, and employ color-coding where necessary to distinctly identify the different study groups and highlight significant differences.

AI Content Analysis for Post-2021 Works:<br /> - Estimated AI-Generated Content: Approximately 10% of the text, especially the repeated summarizations and some data interpretations, exhibit patterns that could be characteristic of AI-generated content.<br /> - Assessed Epistemic Impact: Given the AI content detected, the fundamental arguments and conclusions of the work remain sound. However, reliance on AI for section summarizations could introduce bias toward over-simplification and generality in explanations.<br /> - Recommendations: Review and potentially rephrase sections suspected of AI generation to ensure academic rigor and depth are maintained.

Recommendations<br /> - Focus Future Research: Redirect the focus towards the newly identified eicosanoids, ensuring their potential as labour biomarkers. Validate these findings with larger and more diverse cohorts to overcome sample size and variability issues observed in the current study.<br /> - Engage in Collaborative Studies: Collaborate with other research institutions to compare findings and standardize methodologies, thus enhancing the robustness of the research outcomes.<br /> - Integration with Clinical Practice: Develop a framework to integrate novel biomarker research into clinical trials progressively, ensuring findings translate into practical tools for predicting and managing labour, especially preterm labour conditions.

On 2024-12-13 11:22:11, user Antoni P.A. Hendrickx wrote:

This article has been published in Genome Medicine:<br /> https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-024-01412-6

On 2024-12-19 23:00:26, user pietje puk wrote:

This paper is based on a corrupted vaccine registration dataset.<br /> Details about this can be found in the following link:

https://virusvaria.nl/en/is-dit-de-smoking-gun/

In summary: vaccinees were registered in CIMS, but there often was a time lag of a few weeks between vaccination and registration in CIMS. Because of a ministerial decree from 19 November 2020, the following happened:<br /> If vaccinees died after vaccination, but before registration, they were not registered as vaccinated. In addition, for a period of time, registered vaccinees that died were actively removed from CIMS.<br /> This makes the data in CIMS not suitable for analyses.<br /> The authors should retract this paper.

On 2024-12-23 21:30:17, user Alistair Pagnamenta wrote:

Lovely work. Wondering are any of haplotype informative SNVs rare enough to be used for tagging this SVA insertion? That could make it easier to pick up in other datasets...

On 2024-12-28 04:44:14, user xPeer wrote:

Courtesy review from xPeerd.com

The paper, "Machine Learning Approaches to Predict Alcohol Consumption from Biomarkers in the UK Biobank," evaluates five machine learning (ML) models to predict alcohol consumption (DPW) using biomarkers. The study leverages biomarkers and covariates from the UK Biobank to enhance prediction accuracy. The highest-performing model, XGBOOST, achieved an r² of 0.356. The research findings indicate that using biomarkers significantly improves the prediction of heavy drinking and other related phenotypes.

Potential Major Revisions:

1. Biomarker Selection Justification: While the paper discusses known biomarkers, it does not provide a detailed rationale for selecting the specific 338 predictors used. The study should offer more context or references explaining why these particular biomarkers were chosen and how they relate to alcohol consumption prediction comprehensively (pg. 4).

2. Ethical Considerations and Limitations: Although the study briefly mentions the ethical limitations concerning the UK's demographics, it could expound on this point, addressing how the findings might translate to diverse populations not represented in the UK Biobank dataset (pg. 16).

3. Model Generalizability: The study should provide more details on the applicability and generalizability of the model findings to different populations with genetic diversity and varying socio-economic backgrounds (pg. 17). It must address how the model could adapt or fail in non-European cohorts as the generalizability might vary.

Potential Minor Revisions:

1. Typographical and Minor Errors:
2. Consistency in the abbreviation of DPW (Drinks Per Week) is essential. There are minor inconsistencies throughout the manuscript that could be formatted uniformly (pg. 7, 14).

3. Clarity and readability can be enhanced by eliminating repeated phrases (e.g., "Alcohol Consumption prediction using biomarkers" is repeated frequently which might be condensed or varied).

4. Formatting Issues:

5. Figures and Tables: Ensure all figures and tables are referenced correctly in the text and positioned to avoid disrupting reading flow (p.13, Figures 3, 4, 8).

6. Supplementary Information: Cross-reference supplementary information more clearly within the text to aid readers in locating relevant data (e.g., Supplementary Table T3 and Figures S2).

7. AI Content Analysis:

8. There is no explicit indication of AI-generated content in this paper. However, the paper exhibits some areas of redundancy which can be indicative of AI-aided writing:
9. Assessed AI content reflects about 5% of the total document. These are sections that repeat information about statistical measures and known biological impacts without much nuanced discussion (e.g., discussion of model performances and the role of biomarkers) (pg. 10-11).
10. The epistemic impact of this AI-generated content is minimal and does not undermine the scientific integrity of the paper. It would benefit from a more nuanced discussion of the statistical results and implications.

Recommendations:

1. Improving Rationale and Discussion:
2. Strengthen the section discussing the selection of specific biomarkers with comprehensive explanations or references.

3. Expand on the implications of the model predictions, especially in clinical and public health contexts, to enhance readability and relevance.

4. Enhancing Generalizability:

5. Discuss in more detail how these predictive models could be adjusted or re-calibrated for non-European populations.

6. Provide more comprehensive demographic benefits and limitations to reinforce the findings' applicability and reliability.

7. Visual and Supplementary Data Clarity:

8. Organize figures and tables to enhance their impact without disrupting the flow.
9. Ensure all supplementary materials are accurately referenced and easy to locate within the text.

By addressing these major and minor revisions, the manuscript will achieve higher clarity, ethical robustness, and academic integrity while broadening its impacts across diverse populations and further grounding its findings within the literature.

On 2025-02-21 05:07:22, user Evan Stanbury wrote:

This paper has a noble goal: To identify patients who have suffered long-term vaccine injury (ie iatrogenic, and potentially eligible for vaccine compensation schemes). It is important to distinguish these patients from from Long COVID, since they have very similar symptoms.

On 2025-02-21 05:13:29, user Evan Stanbury wrote:

Re "the individuals with PVS exhibited elevated levels of circulating full-length S compared to healthy controls". "full-length S" means that this Spike protein was from COVID virus, not COVID vaccine (which has a shorter version). This contradicts the hypothesis that the sick cohort were caused by the vaccine.

On 2025-03-03 05:11:41, user Eli Dumitru wrote:

The Summary says: <br /> "...a small fraction of the population reports a chronic debilitating condition after COVID-19 vaccination..." <br /> However, the paper says: <br /> "The most frequent symptoms reported by participants were excessive fatigue (85%), tingling and numbness (80%), exercise intolerance (80%), brain fog (77.5%), difficulty concentrating or focusing (72.5%), trouble falling or staying asleep (70%), neuropathy (70%), muscle aches (70%), anxiety (65%), tinnitus (60%) and burning sensations (57.5%)." <br /> and<br /> "A high proportion of participants with PVS developed any symptoms (70%) or severe symptoms (52.2%) within 10 days of vaccination (Figure 1G)."<br /> Please explain how these percentages can be described as small fractions.

On 2025-03-07 06:35:55, user H Soori wrote:

The manuscript presents a critical examination of science-related populism and its impact on public health during the COVID-19 pandemic in Iran. While the authors aim to illuminate the detrimental effects of political decisions on health outcomes, the framing of Iranian scientists and health workers raises several ethical and factual concerns. First and foremost, the manuscript appears to overlook the immense efforts made by Iranian scientists and healthcare professionals during one of the most challenging public health crises in recent history. Despite facing significant barriers, including sanctions and limited access to resources, Iranian scientists worked diligently to combat the pandemic. Accusing them of contributing to the crisis undermines their hard work and sacrifices, particularly when approximately 400 health staff lost their lives while serving their communities. The analysis seems to simplify a complex situation by attributing adverse health outcomes solely to political resistance and delays in vaccination. It is crucial to consider the broader context, including international dynamics, supply chain disruptions, and the unprecedented nature of the pandemic. Such factors played a vital role in vaccination delays and should not be overlooked in the pursuit of a singular narrative. While the manuscript discusses the dangers of science-related populism, it inadvertently engages in a form of populism itself by painting a one-dimensional picture of Iranian public health responses. This approach risks alienating those who worked tirelessly on the front lines, suggesting that the authors may not fully appreciate the nuances of scientific work in politically charged environments. The findings advocating for a global commitment to uphold scientific integrity are undoubtedly important; however, this message would benefit from a more nuanced discussion that recognizes and honors the contributions of Iranian scientists and health workers. Instead of casting blame, the narrative should focus on collaborative efforts and the need for solidarity in the face of global health challenges. In conclusion, while the manuscript raises valid concerns about the implications of political actions on public health, it fails to adequately recognize the contributions of Iranian scientists and healthcare workers. A more balanced approach that acknowledges their dedication and sacrifices would enhance the manuscript's credibility and foster a more constructive dialogue on public health policy and scientific integrity.

Hamid Soori<br /> Professor of Epidemiology

On 2025-03-07 14:55:26, user Fatima wrote:

I am so shocked that even a preprint could be published without any evidence-based material. How dare you underestimate one of the most influential, trained medical staff of the Middle East region such as Iran so naive to restrict the import of foreign vaccines into our country. Meanwhile, our honored scientists were preparing Iranian vaccines with efficacy and safety from the very beginning.<br /> It is against humanity to forget our successful safe vaccines Noora and Barekat all of them are Iranian.<br /> Let's shed light on the truth

On 2025-03-15 18:00:20, user amin Abdorrashid wrote:

By singling out Iran for its alleged populist actions, the paper ignores the global prevalence of unscientific practices during the COVID-19 crisis, rendering its argument one-sided and lacking in broader contextual insight.

On 2025-03-25 15:51:39, user Kristjan Norland wrote:

This manuscript has now been published in JACC: https://www.jacc.org/doi/10.1016/j.jacc.2024.06.052

On 2025-04-04 07:10:55, user Tiphaine wrote:

Now published in Gut Microbes https://doi.org/10.1080/19490976.2024.2405547

On 2025-04-10 21:33:23, user Will wrote:

line 165: It should be Figure 3 and not Figure 1.

On 2025-10-13 13:10:16, user Don Talenti wrote:

Would like to see a table of baseline characteristics of vaccinated versus unvaccinated. Also would like to see raw case counts with the absolute numbers of infections in vaccinated versus unvaccinated.

On 2025-04-14 13:17:06, user Ammar wrote:

missing supplementary table1

On 2025-05-08 03:05:33, user John Carter wrote:

Missing from Figure 2 is the control... ie. Unvaccinated cohort.

I suspect what this data is really showing is that mRNA 1273 is more effective against covid AND the mortality due to covid is massively under counted.

On 2025-05-20 23:35:08, user Richard Rebello wrote:

Now published online https://www.nature.com/articles/s41467-025-59661-x

On 2025-06-03 17:06:55, user Ruslan Salamatin wrote:

I would like to inform you that the preprint has now been published in a peer-reviewed journal.

Published in: Journal of Clinical Medicine<br /> DOI of the published version: 10.3390/jcm14113928<br /> Date of publication: 3 June 2025

Please update the preprint record accordingly.

On 2025-06-26 07:45:58, user Stephen Jones wrote:

Now fully available as of June 26, 2025 at<br /> https://doi.org/10.1162/IMAG.a.76

On 2025-07-02 20:18:06, user Samreen Jatana wrote:

This article has been peer reviewed and published:<br /> https://pubmed.ncbi.nlm.nih.gov/37026002/

On 2025-07-12 21:55:39, user David C wrote:

Amazing substantive and methodological contribution. Hats off to the authors.

I'm wondering, if however, there might be selection bias in which high-mortality households are underrepresented in the sample. In the extreme, households in which all members have died would, by definition, not be represented in the sample (I think).

If this type of selection bias holds, the counts could be significant underestimates of the true mortality counts. I'd love to hear the authors' and readers' thoughts on this matter.

On 2025-07-21 19:05:55, user Anna Holmes wrote:

This article has been published in Clinical Infectious Diseases, published by Oxford University Press: https://doi.org/10.1093/cid/ciaf265

On 2025-07-25 12:31:33, user Evolutionary Health Group wrote:

We at the Evolutionary Health Group ( http://evoheal.github.io ) really enjoyed this paper.

Here are our highlights:

Evaluating co-occurrence across different surfaces in the built environment led to the identification of 15 pathogens as indicators for elevated SARS-CoV-2 abundance.

Methodology was flexible, including the evaluation of both cellular and viral genomes.

Study potentially lays the groundwork for improved hospital surveillance of antibiotic resistance gene abundance applying the same approach in a different context.

On 2025-07-25 20:28:33, user Baranger, David wrote:

The final published version of this manuscript is available at: https://www.nature.com/articles/s44220-024-00281-7

On 2025-08-07 09:24:06, user Gaurav Bhalerao wrote:

This article is published in Imaging Neuroscience on May 28th, 2025<br /> : https://doi.org/10.1162/IMAG.a.4