I am going to ignore Ivermectin for a moment to say that Wikipedia's editors have been a problem for a long time. They are a VERY necessary bullwark against misinformation but are also prone to having known bias problems which, in essence, cause the exact thing they are there to prevent. It isn't nearly as bad as many critics make it seem but it does exist and it is more of a problem than Wikipedia thinks.Originally Posted by dan_bgblue
When it comes to Ivermectin, Wikipedia is not in the wrong here (and even Dr. Hill agrees but I will get to that in a bit). The authors of the article to which you link attempt to use n-values to bolster their argument, n-value is only important when BOTH the input studies and meta-analyses are done properly. Meta-analysis in particular is extremely susceptible to flawed input studies, data massaging, flawed procedures, and outright manipulation.
To quote the British Medical Journal:
For example, two of the largest studies around Ivermectin which showed a benefit have had MAJOR problems: Elgazzar et al. was retracted due to potential scientific fraud and breach of ethical conduct by the researchers while the other study Niaee et al, has been roundly criticized for failing to randomize the cohorts leading to biased results. This lead to Dr. Hill retracting his own meta-analysis . Quite simply, Wikipedia VERY RIGHTLY refuses to accept their data because they not only refuse to comply with the accepted protocol standards which have been developed to prevent bias, data manipulation, and outright fraudulent analysis but their data has multiple known major flaws. As stated before, Dr. Hill (the author of said retracted study) states that Wikipedia is correct in not citing them:Different websites (such as https://ivmmeta.com/, https://c19ivermectin.com/, https://tratamientotemprano.org/estudios-ivermectina/, among others) have conducted meta-analyses with ivermectin studies, showing unpublished colourful forest plots which rapidly gained public acknowledgement and were disseminated via social media, without following any methodological or report guidelines. These websites do not include protocol registration with methods, search strategies, inclusion criteria, quality assessment of the included studies nor the certainty of the evidence of the pooled estimates. Prospective registration of systematic reviews with or without meta-analysis protocols is a key feature for providing transparency in the review process and ensuring protection against reporting biases, by revealing differences between the methods or outcomes reported in the published review and those planned in the registered protocol. These websites show pooled estimates suggesting significant benefits with ivermectin, which has resulted in confusion for clinicians, patients and even decision-makers. This is usually a problem when performing meta-analyses which are not based in rigorous systematic reviews, often leading to spread spurious or fallacious findings.
SourceOur meta-analysis of survival for ivermectin had to be retracted after one of the main studies was suspected of medical fraud. With the revised version, there is no statistically significant survival benefit for ivermectin. So the original version should not be quoted
I have been following these studies pretty intently and most of the well-detailed testing shows AT BEST a very slight improvement in the reduction of outcomes for Ivermectin with most showing no statistically significant difference. This potential slight benefit is offset by the fact that Ivermectin has an extremely notable "toxic shelf". This means it is relatively easy to exceed the toxic threshold for Ivermectin and when that happens the side effects can be extremely severe (nerve damage, sensory damage, etc.).
You missed some other far more likely options:
One, as discussed above, the data in the meta-analysis had multiple problems, was retracted by the author, and subsequent analysis shows no benefit.
Two, the data from India is extremely unreliable and inaccurate. Quite simply, parts of India suffer from extreme corruption and a lack of infrastructure. In particular, northern states like Bihar and Uttar Pradesh are EXTREMELY impoverished and lack many basic necessities let alone any sort of reasonable health care. As such, much of the outbreak was not even quantified in these regions. There were no doctors to go to, no testing, and certainly no treatment. People just contracted COVID, died, and were cremated.
If we look at excess deaths during the COVID outbreak, there were somewhere between 3-4 million more deaths than normal but only a bit over 400,000 were ascribed to COVID. At this point, it is pretty well accepted that the death toll in India is in the millions. This is supported by government satellite images showing mass cremations across the country, shortages in medical equipment which far exceeds the official numbers ,etc. Add in the hyper-nationalistic Modi government, which tried to downplay COVID throughout, and you end up with heavily distorted data. The truth is, we will never know how high the death toll was in India but we know that it was FAR FAR higher than the official numbers which were reported.
In conclusion, this misinformation is the most insidious kind, it took a LOT of work on my part to explain why it is wrong and why Wikipedia is right to block this particular info.
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