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HCQ for COVID-19: real-time meta analysis of 298 studies
https://hcqmeta.com/
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ All studies 25% 298 413,756 Improvement, Studies, Patients Relative Risk, 95% CI With exclusions 39% 187 221,765 Mortality 22% 184 291,871 Hospitalization 21% 42 82,333 RCTs 21% 46 21,623 Prophylaxis 32% 57 142,795 Early 64% 33 54,693 Late 19% 201 213,581 HCQ for COVID-19 hcqmeta.com Dec 1, 2021 Favors HCQ Favors control
97% of the 33 early treatment studies report a positive effect (14 statistically significant in isolation).
Meta analysis using the most serious outcome reported shows 64% [54‑72%] improvement for the 33 early treatment studies. Results are similar after exclusion based sensitivity analysis and after restriction to peer-reviewed studies. Restricting to the 8 RCTs shows 46% [16‑65%] improvement, and restricting to the 13 mortality results shows 75% [60‑84%] lower mortality.
Late treatment is less successful, with only 68% of the 201 studies reporting a positive effect. Very late stage treatment is not effective and may be harmful, especially when using excessive dosages.
83% of Randomized Controlled Trials (RCTs) for early, PrEP, or PEP treatment report positive effects, the probability of this happening for an ineffective treatment is 0.0038.
There is evidence of bias towards publishing negative results. 76% of prospective studies report positive effects, compared to 72% of retrospective studies. Studies from North America are 2.8 times more likely to report negative results than studies from the rest of the world combined, p = 0.0000000277. The probability that an ineffective treatment generated results as positive as the 298 studies is estimated to be 1 in 1 quadrillion.
Negative meta analyses of HCQ generally choose a subset of trials, focusing on late treatment, especially trials with very late treatment and excessive dosages.
While many treatments have some level of efficacy, they do not replace vaccines and other measures to avoid infection. Only 5% of HCQ studies show zero events in the treatment arm.
Elimination of COVID-19 is a race against viral evolution. No treatment, vaccine, or intervention is 100% available and effective for all current and future variants. All practical, effective, and safe means should be used. Not doing so increases the risk of COVID-19 becoming endemic; and increases mortality, morbidity, and collateral damage.
All data to reproduce this paper and the sources are in the appendix. See [Ladapo, Prodromos, Risch, Risch (B)] for other meta analyses showing efficacy when HCQ is used early.
Total298 studies4,772 authors413,756 patients
Positive effects217 studies3,380 authors291,466 patients
Early treatment 64% improvement RR 0.36 [0.28-0.46]
Late treatment 19% improvement RR 0.81 [0.76-0.86]
    
  
A
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Gautret 66% 0.34 [0.17-0.68] 2.4g viral+ 6/20 14/16 Improvement, RR [CI] Dose (4d) Treatment Control Huang (RCT) 92% 0.08 [0.01-1.32] 4g (c) no recov. 0/10 6/12 Esper 64% 0.36 [0.15-0.87] 2g hosp. 8/412 12/224 Ashraf 68% 0.32 [0.10-1.10] 1.6g death 10/77 2/5 Huang (ES) 59% 0.41 [0.26-0.64] 2g (c) viral time 32 (n) 37 (n) Guérin 61% 0.39 [0.02-9.06] 2.4g death 0/20 1/34 Chen (RCT) 72% 0.28 [0.11-0.74] 1.6g viral time 18 (n) 12 (n) Derwand 79% 0.21 [0.03-1.47] 1.6g death 1/141 13/377 Mitjà (RCT) 16% 0.84 [0.35-2.03] 2g hosp. 8/136 11/157 Skipper (RCT) 37% 0.63 [0.21-1.91] 3.2g hosp./death 5/231 8/234 Hong 65% 0.35 [0.13-0.72] n/a viral+ 42 (n) 48 (n) Bernabeu-Wittel 59% 0.41 [0.36-0.95] 2g death 189 (n) 83 (n) Yu (ES) 85% 0.15 [0.02-1.05] 1.6g death 1/73 238/2,604 Ly 56% 0.44 [0.26-0.75] 2.4g death 18/116 29/110 Ip 55% 0.45 [0.11-1.85] n/a death 2/97 44/970 Heras 96% 0.04 [0.02-0.09] n/a death 8/70 16/30 Kirenga 26% 0.74 [0.47-1.17] n/a recov. time 29 (n) 27 (n) Sulaiman 64% 0.36 [0.17-0.80] 2g death 7/1,817 54/3,724 Guisado-Vasco (ES) 67% 0.33 [0.05-1.55] n/a death 2/65 139/542 Szente Fonseca 64% 0.36 [0.20-0.67] 2g hosp. 25/175 89/542 Cadegiani 81% 0.19 [0.01-3.88] 1.6g death 0/159 2/137 Simova 94% 0.06 [0.00-1.13] 2.4g hosp. 0/33 2/5 Omrani (RCT) 12% 0.88 [0.26-2.94] 2.4g hosp. 7/304 4/152 Agusti 68% 0.32 [0.06-1.67] 2g progression 2/87 4/55 Su 85% 0.15 [0.04-0.57] 1.6g progression 261 (n) 355 (n) Amaravadi (RCT) 60% 0.40 [0.13-1.28] 3.2g no recov. 3/15 6/12 Roy 2% 0.98 [0.45-2.20] n/a recov. time 14 (n) 15 (n) Mokhtari 70% 0.30 [0.20-0.45] 2g death 27/7,295 287/21,464 Million 83% 0.17 [0.06-0.48] 2.4g death 5/8,315 11/2,114 Sobngwi (RCT) 52% 0.48 [0.09-2.58] 1.6g no recov. 2/95 4/92 Rodrigues (RCT) -200% 3.00 [0.13-71.6] 3.2g hosp. 1/42 0/42 Sawanpanyalert 42% 0.58 [0.18-1.91] varies progression n/a n/a Chechter 95% 0.05 [0.00-0.96] 2g hosp. 0/60 3/12 Early treatment 64% 0.36 [0.28-0.46] 148/20,450 999/34,243 64% improvement All 33 hydroxychloroquine COVID-19 early treatment studies hcqmeta.com Dec 1, 2021 Tau​2 = 0.20; I​2 = 52.7%; Z = 8.29 Effect extraction pre-specified, see appendix Favors HCQ Favors control
    
  
B
    
  
C
    
  
D
Figure 1. A. Random effects meta-analysis of all early treatment studies. This plot shows pooled effects, analysis for individual outcomes is below, and more details on pooled effects can be found in the heterogeneity section. Effect extraction is pre-specified, using the most serious outcome reported. Simplified dosages are shown for comparison, these are the total dose in the first four days. Chloroquine is indicated with (c). For details of effect extraction and full dosage information see the appendix. B. Scatter plot of the effects reported in early treatment studies and in all studies. Early treatment is more effective. C and D. Chronological history of all reported effects, with the probability that the observed frequency of positive effects occurred due to random chance from an ineffective treatment.
Introduction
We analyze all significant studies concerning the use of HCQ (or CQ) for COVID-19. Search methods, inclusion criteria, effect extraction criteria (more serious outcomes have priority), all individual study data, PRISMA answers, and statistical methods are detailed in Appendix 1. We present random-effects meta-analysis results for all studies, for studies within each treatment stage, for mortality results only, after exclusion of studies with critical bias, and for Randomized Controlled Trials (RCTs) only. Typical meta analyses involve subjective selection criteria and bias evaluation, requiring an understanding of the criteria and the accuracy of the evaluations. However, the volume of studies presents an opportunity for an additional simple and transparent analysis aimed at detecting efficacy.
If treatment was not effective, the observed effects would be randomly distributed (or more likely to be negative if treatment is harmful). We can compute the probability that the observed percentage of positive results (or higher) could occur due to chance with an ineffective treatment (the probability of >= k heads in n coin tosses, or the one-sided sign test / binomial test). Analysis of publication bias is important and adjustments may be needed if there is a bias toward publishing positive results. For HCQ, we find evidence of a bias toward publishing negative results.
Figure 2 shows stages of possible treatment for COVID-19. Pre-Exposure Prophylaxis (PrEP) refers to regularly taking medication before being infected, in order to prevent or minimize infection. In Post-Exposure Prophylaxis (PEP), medication is taken after exposure but before symptoms appear. Early Treatment refers to treatment immediately or soon after symptoms appear, while Late Treatment refers to more delayed treatment.
    
  
Figure 2. Treatment stages.
Results
Figure 3, Figure 4, and Table 1 show results by treatment stage, and Figure 5 shows a forest plot for a random effects meta-analysis of all studies. Figure 6 and Figure 7 show forest plots restricted to mortality and hospitalization results only.
Early treatment.
97% of early treatment studies report a positive effect, with an estimated reduction of 64% in the effect measured (death, hospitalization, etc.) from the random effects meta-analysis, RR 0.36 [0.28-0.46].
Late treatment.
Late treatment studies are mixed, with 68% showing positive effects, and an estimated reduction of 19% in the random effects meta-analysis. Negative studies mostly fall into the following categories: they show evidence of significant unadjusted confounding, including confounding by indication; usage is extremely late; or they use an excessively high dosage.
Pre-Exposure Prophylaxis.
76% of PrEP studies show positive effects, with an estimated reduction of 32% in the random effects meta-analysis. Negative studies are all studies of systemic autoimmune disease patients which either do not adjust for the different baseline risk of these patients at all, or do not adjust for the highly variable risk within these patients.
Post-Exposure Prophylaxis.
88% of PEP studies report positive effects, with an estimated reduction of 33% in the random effects meta-analysis.
Treatment timeNumber of studies reporting positive results Total number of studiesPercentage of studies reporting positive results Probability of an equal or greater percentage of positive results from an ineffective treatmentRandom effects meta-analysis results
Early treatment 32 33 97.0% 1 in 253 million 64% improvement
RR 0.36 [0.28‑0.46]
p < 0.0001
Late treatment 137 202 67.8% 1 in 4 million 19% improvement
RR 0.81 [0.76‑0.86]
p < 0.0001
Pre‑Exposure Prophylaxis 44 58 75.9% 1 in 20 thousand 32% improvement
RR 0.68 [0.57‑0.82]
p < 0.0001
Post‑Exposure Prophylaxis 7 8 87.5% 1 in 28 33% improvement
RR 0.67 [0.53‑0.83]
p = 0.00043
All studies 217 298 72.8% 1 in 1 quadrillion 25% improvement
RR 0.75 [0.70‑0.79]
p < 0.0001
Table 1. Results by treatment stage. 3 studies report results for a subset with early treatment, these are not included in the overall results.
    
  
Figure 3. Results by treatment stage.
    
  
    
  
    
  
    
  
Figure 4. Chronological history of results by treatment stage, with the probability that the observed frequency of positive results occurred due to random chance from an ineffective treatment.
    
  
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Gautret 66% 0.34 [0.17-0.68] viral+ 6/20 14/16 Improvement, RR [CI] Treatment Control Huang (RCT) 92% 0.08 [0.01-1.32] no recov. 0/10 6/12 Esper 64% 0.36 [0.15-0.87] hosp. 8/412 12/224 Ashraf 68% 0.32 [0.10-1.10] death 10/77 2/5 Huang (ES) 59% 0.41 [0.26-0.64] viral time 32 (n) 37 (n) Guérin 61% 0.39 [0.02-9.06] death 0/20 1/34 Chen (RCT) 72% 0.28 [0.11-0.74] viral time 18 (n) 12 (n) Derwand 79% 0.21 [0.03-1.47] death 1/141 13/377 Mitjà (RCT) 16% 0.84 [0.35-2.03] hosp. 8/136 11/157 Skipper (RCT) 37% 0.63 [0.21-1.91] hosp./death 5/231 8/234 Hong 65% 0.35 [0.13-0.72] viral+ 42 (n) 48 (n) Bernabeu-Wittel 59% 0.41 [0.36-0.95] death 189 (n) 83 (n) Yu (ES) 85% 0.15 [0.02-1.05] death 1/73 238/2,604 Ly 56% 0.44 [0.26-0.75] death 18/116 29/110 Ip 55% 0.45 [0.11-1.85] death 2/97 44/970 Heras 96% 0.04 [0.02-0.09] death 8/70 16/30 Kirenga 26% 0.74 [0.47-1.17] recov. time 29 (n) 27 (n) Sulaiman 64% 0.36 [0.17-0.80] death 7/1,817 54/3,724 Guisado-Vasco (ES) 67% 0.33 [0.05-1.55] death 2/65 139/542 Szente Fonseca 64% 0.36 [0.20-0.67] hosp. 25/175 89/542 Cadegiani 81% 0.19 [0.01-3.88] death 0/159 2/137 Simova 94% 0.06 [0.00-1.13] hosp. 0/33 2/5 Omrani (RCT) 12% 0.88 [0.26-2.94] hosp. 7/304 4/152 Agusti 68% 0.32 [0.06-1.67] progression 2/87 4/55 Su 85% 0.15 [0.04-0.57] progression 261 (n) 355 (n) Amaravadi (RCT) 60% 0.40 [0.13-1.28] no recov. 3/15 6/12 Roy 2% 0.98 [0.45-2.20] recov. time 14 (n) 15 (n) Mokhtari 70% 0.30 [0.20-0.45] death 27/7,295 287/21,464 Million 83% 0.17 [0.06-0.48] death 5/8,315 11/2,114 Sobngwi (RCT) 52% 0.48 [0.09-2.58] no recov. 2/95 4/92 Rodrigues (RCT) -200% 3.00 [0.13-71.6] hosp. 1/42 0/42 Sawanpanyalert 42% 0.58 [0.18-1.91] progression n/a n/a Chechter 95% 0.05 [0.00-0.96] hosp. 0/60 3/12 Tau​2 = 0.20; I​2 = 52.7% Early treatment 64% 0.36 [0.28-0.46] 148/20,450 999/34,243 64% improvement Xia 38% 0.62 [0.32-1.22] viral+ 5/10 12/15 Improvement, RR [CI] Treatment Control Chen (RCT) 29% 0.71 [0.29-1.74] progression 5/15 7/15 Zhong 80% 0.20 [0.08-0.52] viral+ 5/115 17/82 Chen (RCT) 57% 0.43 [0.19-0.97] pneumonia 6/31 14/31 Barbosa -147% 2.47 [0.24-25.0] death 2/17 1/21 Tang (RCT) 21% 0.79 [0.38-1.62] viral+ 11/75 14/75 Magagnoli 11% 0.89 [0.45-1.77] death 39/148 18/163 Auld -3% 1.03 [0.67-1.57] death 33/114 29/103 Sánchez-Álvarez 46% 0.54 [0.34-0.84] death 322 (n) 53 (n) Mallat -203% 3.03 [1.11-7.69] viral time 23 (n) 11 (n) Membrillo de Nov.. 55% 0.45 [0.29-0.71] death 27/123 21/43 Geleris -4% 1.04 [0.82-1.32] int./death 262/811 84/565 Alberici 43% 0.57 [0.24-1.13] death 17/72 9/22 Rosenberg -35% 1.35 [0.76-2.40] death 189/735 28/221 Shabrawishi 15% 0.85 [0.45-1.62] viral+ 12/45 15/48 Mahévas -20% 1.20 [0.40-3.30] death 9/84 8/89 Yu 60% 0.40 [0.22-0.72] death 9/48 238/502 Kim 51% 0.49 [0.28-0.87] hosp. time 22/22 40/40 Singh 5% 0.95 [0.74-1.22] death 104/910 109/910 Luo 32% 0.68 [0.08-5.88] death 19 (n) 264 (n) Hraiech 65% 0.35 [0.08-1.56] death 2/17 5/15 Ip 1% 0.99 [0.80-1.22] death 432/1,914 115/598 Goldman 22% 0.78 [0.40-1.52] death 10/109 34/288 Huang 67% 0.33 [0.19-0.57] viral time 197 (n) 176 (n) Kuderer -134% 2.34 [1.62-3.21] death 45/181 121/928 Rogado 92% 0.08 [0.00-0.87] death 1/8 7/9 RECOVERY (RCT) -9% 1.09 [0.97-1.23] death 421/1,561 790/3,155 Wang 6% 0.94 [0.75-1.19] death 1,866 (n) 5,726 (n) Luo -2% 1.02 [0.39-2.65] death 11/35 4/13 Paccoud 11% 0.89 [0.23-3.47] death 21/38 26/46 Sbidian -5% 1.05 [0.77-1.33] death 111/623 830/3,792 Faíco-Filho 81% 0.19 [0.00-8.66] viral rate 34 (n) 32 (n) Fontana 50% 0.50 [0.16-1.55] death 4/12 2/3 Bousquet 43% 0.57 [0.24-1.36] death 5/27 23/81 Lagier 59% 0.41 [0.27-0.62] death 35/3,119 58/618 Sosa-García -11% 1.11 [0.32-3.78] death 7/38 3/18 Komissarov -25% 1.25 [0.71-2.21] viral load 26/26 10/10 Mikami 47% 0.53 [0.41-0.68] death 575/2,077 231/743 Martinez-Lopez 33% 0.67 [0.39-1.14] death 47/148 9/19 Arshad 51% 0.49 [0.39-0.60] death 162/1,202 108/409 An 3% 0.97 [0.57-1.67] viral+ 31/31 195/195 Rivera-Izquierdo 19% 0.81 [0.24-2.76] death 215 (n) 23 (n) Chen -29% 1.29 [0.58-2.86] viral+ 16/28 4/9 Chen (RCT) 24% 0.76 [0.20-2.84] viral+ 4/21 3/12 Cravedi -53% 1.53 [0.84-2.80] death 36/101 10/43 Lecronier 42% 0.58 [0.27-1.24] death 9/38 9/22 Trullàs 36% 0.64 [0.39-1.07] death 20/66 16/34 Gupta -6% 1.06 [0.92-1.22] death 631/1,761 153/454 Lyngbakken (RCT) 4% 0.96 [0.06-14.6] death 1/27 1/26 McGrail -70% 1.70 [0.41-7.07] death 4/33 3/42 Krishnan 20% 0.80 [0.52-1.21] death 86/144 6/8 Bernaola 17% 0.83 [0.77-0.89] death 236/1,498 28/147 Kelly -143% 2.43 [1.06-5.56] death 23/82 6/52 Rivera -2% 1.02 [0.67-1.53] death 44/179 59/327 Cavalcanti (RCT) 16% 0.84 [0.28-2.53] death 8/331 5/173 D'Arminio Monforte 34% 0.66 [0.39-1.11] death 53/197 47/92 Davido 55% 0.45 [0.23-0.89] int./hosp. 12/80 13/40 Yu 83% 0.17 [0.02-1.27] progression 1/231 32/1,291 Berenguer 18% 0.82 [0.74-0.90] death 681/2,618 438/1,377 Kamran 5% 0.95 [0.34-2.69] progression 11/349 5/151 Kalligeros -67% 1.67 [0.29-9.36] death 36 (n) 72 (n) Saleemi -21% 1.21 [1.00-1.46] viral time 65/65 20/20 Roomi -38% 1.38 [0.40-2.76] death 13/144 6/32 Abd-Elsalam (RCT) -20% 1.20 [0.38-3.80] death 6/97 5/97 Peters -9% 1.09 [0.81-1.47] death 419/1,596 53/353 Pinato 59% 0.41 [0.29-0.58] death 30/182 181/446 Dubernet 88% 0.12 [0.02-0.88] ICU 1/17 9/19 Gonzalez 27% 0.73 [0.66-0.81] death 1,246/8,476 341/1,168 Pasquini 16% 0.84 [0.62-1.14] death 23/33 15/18 Catteau 32% 0.68 [0.62-0.76] death 804/4,542 957/3,533 Di Castelnuovo 30% 0.70 [0.59-0.84] death 386/2,634 90/817 Fried -27% 1.27 [1.18-1.36] death 1,048/4,232 1,466/7,489 Albani 18% 0.82 [0.61-1.06] death 60/211 172/605 Synolaki 24% 0.76 [0.49-1.18] death 21/98 60/214 Alamdari 55% 0.45 [0.25-0.83] death 54/427 9/32 Heberto 54% 0.46 [0.19-0.97] death 139 (n) 115 (n) Lauriola 74% 0.27 [0.17-0.41] death 102/297 35/63 Ashinyo 33% 0.67 [0.47-0.96] hosp. time 61/61 61/61 Serrano 43% 0.57 [0.28-1.18] death 6/14 6/8 Ulrich (RCT) -6% 1.06 [0.38-2.98] death 7/67 6/61 Shoaibi 15% 0.85 [0.79-0.91] death 686/5,047 3,923/24,404 Lammers 32% 0.68 [0.47-0.99] death/ICU 30/189 101/498 Ayerbe 52% 0.48 [0.37-0.62] death 237/1,857 49/162 Almazrou 65% 0.35 [0.09-1.35] ventilation 3/95 6/66 Nachega 28% 0.72 [0.49-1.06] death 69/630 28/96 Ader (RCT) 6% 0.94 [0.43-2.05] death 11/145 12/148 Soto-Becerra 18% 0.82 [0.76-0.89] death 346/692 1,606/2,630 Aparisi 63% 0.37 [0.27-0.50] death 122/605 27/49 Annie 4% 0.96 [0.65-1.37] death 48/367 50/367 SOLIDARITY (RCT) -19% 1.19 [0.89-1.59] death 104/947 84/906 Guisado-Vasco 20% 0.80 [0.47-1.26] death 127/558 14/49 Solh -18% 1.18 [0.93-1.51] death 131/265 134/378 Ñamendys-Silva 32% 0.68 [0.48-0.96] death 24/54 42/64 Dubee (RCT) 46% 0.54 [0.21-1.42] death 6/124 11/123 Lano 33% 0.67 [0.28-1.31] death 56 (n) 66 (n) Coll 46% 0.54 [0.41-0.72] death 55/307 108/328 Frontera (PSM) 37% 0.63 [0.44-0.91] death 121/1,006 424/2,467 Choi -22% 1.22 [1.10-1.35] viral time 701/701 701/701 Tehrani 13% 0.87 [0.54-1.40] death 16/65 54/190 López 64% 0.36 [0.14-0.89] progression 5/36 14/36 Salazar -37% 1.37 [0.77-2.42] death 12/92 80/811 Rodriguez-Nava -6% 1.06 [0.72-1.56] death 22/65 79/248 Maldonado 91% 0.09 [0.02-0.50] death 1/11 1/1 Núñez-Gil 8% 0.92 [0.87-0.94] death 200/686 100/268 Self (RCT) -6% 1.06 [0.57-1.87] death 25/241 25/236 Rodriguez 59% 0.41 [0.13-1.31] death 8/39 2/4 Águila-Gordo 67% 0.33 [0.09-1.24] death 151/346 47/70 Sheshah 80% 0.20 [0.09-0.45] death 267 (n) 33 (n) Boari 55% 0.45 [0.30-0.68] death 41/202 25/56 Budhiraja 65% 0.35 [0.24-0.50] death 69/834 34/142 Falcone (PSM) 65% 0.35 [0.07-1.73] death 40/238 30/77 Qin 34% 0.66 [0.22-2.00] death 3/43 75/706 Burdick -59% 1.59 [0.89-2.83] death 142 (n) 148 (n) van Halem 32% 0.68 [0.47-1.00] death 34/164 47/155 Rodriguez-Gonzalez 23% 0.77 [0.51-1.17] death 251/1,148 17/60 Lambermont 32% 0.68 [0.48-0.96] death 97/225 14/22 Abdulrahman (PSM) 17% 0.83 [0.26-2.69] death 5/223 6/223 Capsoni 40% 0.60 [0.29-1.25] ventilation 12/40 6/12 Peng 11% 0.89 [0.62-1.29] progression 29/453 256/3,567 Modrák 59% 0.41 [0.19-1.03] death 108 (n) 105 (n) Ozturk 44% 0.56 [0.28-1.13] death 165/1,127 6/23 Guglielmetti 35% 0.65 [0.33-1.30] death 181 (n) 37 (n) Johnston (RCT) 30% 0.70 [0.19-2.54] hosp. 5/148 4/83 Alqassieh 18% 0.82 [0.64-1.05] hosp. time 63 (n) 68 (n) Bielza 22% 0.78 [0.59-1.05] death 33/91 249/539 Tan 35% 0.65 [0.43-0.98] hosp. time 8 (n) 277 (n) Naseem 33% 0.67 [0.30-1.53] death 77 (n) 1,137 (n) Orioli 13% 0.87 [0.26-2.94] death 8/55 3/18 De Luna -105% 2.05 [0.29-14.6] death 15/132 1/18 Signes-Costa 47% 0.53 [0.37-0.75] death 4,854 (n) 993 (n) Matangila 55% 0.45 [0.07-1.27] death 25/147 8/13 Cangiano 73% 0.27 [0.12-0.61] death 5/33 37/65 Taccone 25% 0.75 [0.58-0.95] death 449/1,308 183/439 Chari 33% 0.67 [0.37-1.22] death 8/29 195/473 Güner 77% 0.23 [0.03-1.76] ICU 604 (n) 100 (n) Vernaz (PSM) 15% 0.85 [0.42-1.70] death 12/93 16/105 Texeira -79% 1.79 [0.95-3.38] death 17/65 14/96 Psevdos -63% 1.63 [0.55-4.84] death 17/52 3/15 Sands -70% 1.70 [1.18-2.42] death 101/973 56/696 Lotfy -25% 1.25 [0.39-3.96] death 6/99 5/103 Sarfaraz -45% 1.45 [0.98-2.15] death 40/94 27/92 Yegerov 95% 0.05 [0.00-0.75] death 0/23 20/1,049 Li -40% 1.40 [0.99-1.98] viral time 18 (n) 19 (n) Li 50% 0.50 [0.23-1.10] no disch. 14 (n) 14 (n) Di Castelnuovo 40% 0.60 [0.50-0.70] death 3,270 (n) 1,000 (n) Roig 16% 0.84 [0.49-1.44] death 33/67 7/12 Ubaldo 18% 0.82 [0.52-1.28] death 17/25 5/6 Ouedraogo 33% 0.67 [0.28-1.62] death 397 (n) 59 (n)