@SabinehazanMD Ok. I start NOW !
handbook to conduct fraudulent repurposed drug covid-19 clinical research
Protocols
1/ Choose wrong drug dosage, too high (HCQ - recovery, solidarity) or too low (IVM - together) depending of the drug safety and efficacy.
1/n
@SabinehazanMD 2/ Choose wrong treatment duration (IVM - together, etc...),
3/ Choose wrong timing intervention: start late treatment when your trial aim to study an antiviral (HCQ - recovery, solidarity, discovery),
2/n
@SabinehazanMD 4/ Change inclusion criteria regarding delay between symptoms and recruitment (principle: 7 days for all drugs, except for IVM 14 days)
5/ Don't exclude young healthy patients, it'll be hard to see a difference between groups (Lopez-Medina),
3/n
@SabinehazanMD 6/ If it is recommended to take the drug with fat meal, prescribe it on empty stomach (Together), and vice versa
7/ Choose wrong outcome, like 'resolution of all symptoms after 21 days' (Lopez-Medina),
4/n
@SabinehazanMD 8/ Don't measure viral load if you study early treatment (Lopez-Medina), measure viral load only when you start treatment AFTER the viral phase (HCQ - discovery),
8b/ Argue that not seeing difference in viral load is a bad sign indicating drug doesn't work,
5/n
@SabinehazanMD 9/ STOP the trials with good protocols if a blatantly fraud (#lancetgate) is published, but continue trials with bad protocols arguing everything is ok (HCQ-recovery),
6/n
@SabinehazanMD 10/ Argue that your (well-done) study showing non statistically significant 70% death reduction contradicts (poor) meta-analysis showing statistically significant 70% death reduction (Lim),
7/n
@SabinehazanMD 11/ Don't test multi-therapy (don't forget it's forbidden to save lives using more than one drug), only one single drug.
Meta-analysis
12/ All studies satisfying one of the 1-11/ points is a 'low risk of bias' study.
8/n
@SabinehazanMD 13/ Don't include multi-therapy trials (don't forget it's forbidden to save lives using more than one drug),
14/ Download data and conduct a rapid meta-analysis before your registration on prospero (Fiolet), make a youtube video and argue it was only pedagogical,
9/n
@SabinehazanMD 15/ Include observationnal study, until large positive observationnal studies are published, then STOP doing that ! (HCQ)
16/ If results for outpatient and inpatient are different (HCQ), include both in a single meta-analysis to hide positive results,
10/n
@SabinehazanMD 17/ If results for outpatient and inpatient are positive (IVM), separate both in distinct meta-analysis to hide positive results (Popp)
18/ Include trials that don't match your inclustion criteria if they showed negative results, even if outcome doesn't match (Fiolet),
11/n
@SabinehazanMD 19/ Evaluate 'low risk of bias' studies published in a high IF journal, and 'high risk of bias' all preprint. Oops high IF are only interested to publish negative paper on repurposed drug 😇,
12/n
@SabinehazanMD 20/ Trials with positive results are 'high risk of bias', because, you know, we know it's impossible...
21/Choose wrong statistical model, according to what you want to show, don't forget that fixed effect model will produce smaller CI (Shankar-Hari)
13/n
@SabinehazanMD 21b/ Argue it's ok, because you wrote it in the protocol, nananère!!!
22/ If a trial show positive result, JUST REVERSE BOTH GROUPS (Roman preprint) 😉
23/ Create your own imaginary data on a trial's length of hospital stay (Roman)
14/n
@SabinehazanMD 24/ Write an opposite conclusion to what show the data (Hill),
25/ If someone says you did mistakes and if you fix mistakes it changes the result, argue that you find exactly the same results as other published meta-analysis, thus it's ok not to fix them (Fiolet).
15/15
@SabinehazanMD 11b/ Prescribe macrolide to 20% of the control group when your trial is testing azithromycin, a macrolide. Don't speak about it in the study, hide it in the supplementary data (recovery)
@SabinehazanMD People are creative, we have new tactics: 😀
26/ include patients who already recovered in trials whose primary outcome is "symptom duration" (activ6)

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More from @sudokuvariante

Jun 12
2022: Conversation cyclique montrant qu'il est impossible de montrer qu'un produit pharmaceutique n'est pas sûr:⤵️
🧑Ces vaccins sont sûrs. Dans le cas contraire on l'aurait vu après avoir vacciné plusieurs milliards de personnes dans le monde
𝄆🧑‍🦰Justement, les données des bases de pharmacovigilance montrent que ces vaccins ne sont pas sûrs
🧑La pharmacovigilance ne permet pas d'établir l'imputabilité
🧑‍🦰Qu'est-ce qui permettrait d'établir l'imputabilité?🧑Seuls les essais cliniques le peuvent
Read 6 tweets
Jun 10
I wrote a comment in the @JAMANetwork about @AviBittMD et al. study "Comparison of Trials Using Ivermectin for COVID-19 Between Regions With High and Low Prevalence of Strongyloidiasis"
jamanetwork.com/journals/jaman…
1/n
I'm not scientist and the editors of JAMA decided not to publish it. Here is the commenting policy: jamanetwork.com/pages/commenti… I guess my comment was refused "for other reasons", so that's fine. I'll publish it here. ⤵️
2/n
Authors claim they use parasitological methods for the variable of country-level strongyloidiasis prevalence.
This is not true.
3/n
Read 17 tweets
Apr 3
I do not understand the experts who defend the together study on ivermectin.
1/n
I mean, ok, results are not positive, it means that we cannot expect to save many lives by giving 3 days of ivermectin on an empty stomach without co-medication (yet IVM group did better than control group on every outcome). But really, who cares?
2/n
Doctors advocating for early treatment use very different protocols, and it is these protocols that should have been tested or used without delay.
3/n
Read 6 tweets
Mar 31
Together trial on IVM. nejm.org/doi/full/10.10…
Some basic inconsistencies !!!
1/ Lot of missing patients in the subgroups 😱
98 patients lost in the age subgroups 😱
1/n ImageImage
317 patients lost in the "time since onset of symptoms" subgroups 😱
Which crucial informations do they try to hide?
2/n Image
Number of deaths doesn't correspond between table 3 and table S6 😱 (investigators who are not able to count deaths in their trials, this is not a good sign !)
21 vs 24 or 20 vs 25?
Number of events of Grade 1-4 doesn't correspond either.
3/n ImageImage
Read 4 tweets
Feb 20
@DIVIZIO1 L'étude est peut-être bien conduite, mais ne nous apprend pas grand chose, à cause d'un protocole mal ficelé.
1/n
@DIVIZIO1 Mauvais choix du critère principal: si on mesure l'aggravation de la maladie, il faut commencer le traitement précocement, ce qui n'est pas le cas ici (5j après le début des symptômes en moyenne),
2/n
@DIVIZIO1 l'aggravation arrivant peu après le début du traitement (3j en moyenne).
3/n
Read 8 tweets
Jan 10
.@Cyrilhanouna "C'est le monde entier qui s'est trompé?" Non, les experts indépendants n'ont jamais soutenu une vaccination de masse.
1/n
Cette idée ne vient pas de la science, elle vient d'organismes comme le WEF, GAVI, BMGF, le cabinet McKinsey, reprise en masse par les politiciens, les médias et les lobbyistes en tout genre (👋Laurent Alexandre).
2/n
Les experts n'étaient pas unanimes sur la meilleure stratégie à adopter, surtout au début de la campagne vaccinale, mais au fil du temps est tout de même venu un consensus sur le fait que ces vaccins présentent un mauvais profil de sécurité.
3/n
Read 11 tweets

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