Top
Introduction
Results
Exclusions
Randomized Controlled Trials..
Heterogeneity
Discussion
Conclusion
Responses
GMK Response
Revisions
Appendix 1. Methods and Study..
References

Treatment studies
Treatment RCTs
Sufficiency studies
Cholecalciferol studies
Calcifediol/calcitriol studies
Treatment with exclusions
Treatment peer-reviewed
Treatment mortality
Treatment ventilation
Treatment ICU admission
Treatment hospitalization
Treatment cases

Feedback
Home
Top  Introduction  Results  ExclusionsExc  RCT  HeterogeneityI2  Discussion  Conclusion  Appendices  References  
Home   COVID-19 treatment studies for Vitamin D  COVID-19 treatment studies for Vitamin D  C19 studies: Vitamin D  Vitamin D   Select treatmentSelect treatmentTreatmentsTreatments
Antiandrogens (meta) Metformin (meta)
Aspirin (meta) Molnupiravir (meta)
Bamlanivimab (meta) Nigella Sativa (meta)
Bromhexine (meta) Nitazoxanide (meta)
Budesonide (meta) Paxlovid (meta)
Casirivimab/i.. (meta) Povidone-Iod.. (meta)
Colchicine (meta) Probiotics (meta)
Conv. Plasma (meta) Proxalutamide (meta)
Curcumin (meta) Quercetin (meta)
Favipiravir (meta) Remdesivir (meta)
Fluvoxamine (meta) Sotrovimab (meta)
Hydroxychloro.. (meta) Vitamin A (meta)
Iota-carragee.. (meta) Vitamin C (meta)
Ivermectin (meta) Vitamin D (meta)
Melatonin (meta) Zinc (meta)

Other Treatments Global Adoption
Antiandrogens
Aspirin
Bamlanivimab
Bromhexine
Budesonide
Casirivimab/i..
Colchicine
Conv. Plasma
Curcumin
Favipiravir
Fluvoxamine
Hydroxychloro..
Iota-carragee..
Ivermectin
Melatonin
Metformin
Molnupiravir
Nigella Sativa
Nitazoxanide
Paxlovid
Povidone-Iod..
Probiotics
Proxalutamide
Quercetin
Remdesivir
Sotrovimab
Vitamin A
Vitamin C
Vitamin D
Zinc
Vitamin D for COVID-19: real-time meta analysis of 142 studies
https://vdmeta.com/
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ All studies 45% 53 66,371 Improvement, Studies, Patients Relative Risk, 95% CI With exclusions 44% 42 49,092 Mortality 50% 31 12,599 Ventilation 35% 11 2,903 ICU admission 54% 14 4,019 Hospitalization 17% 10 23,855 Cases 18% 12 37,126 RCTs 53% 9 774 RCTs w/exc. 59% 7 457 RCT death w/exc. 62% 5 375 Peer-reviewed 44% 47 49,575 Sufficiency 56% 89 41,226 Cholecalciferol 42% 44 58,390 Calcifediol 61% 9 7,981 Prophylaxis 34% 28 61,948 Early 81% 6 912 Late 56% 19 3,511 Vitamin D for COVID-19 vdmeta.com Nov 26, 2021 Favors vitamin D Favors control
85% of 53 vitamin D treatment studies report positive effects. 27 studies show statistically significant improvements in isolation (21 for the most serious outcome).
Random effects meta-analysis with pooled effects using the most serious outcome reported shows 81% [65‑90%] and 45% [37‑53%] improvement for early treatment and for all studies. Results are similar after restriction to 47 peer-reviewed studies: 84% [68‑92%] and 44% [35‑52%], and for the 31 mortality results: 79% [61‑88%] and 50% [34‑62%].
Statistically significant improvements are seen in treatment studies for mortality, ventilation, ICU admission, hospitalization, and cases.
Late stage treatment with calcifediol/calcitriol shows greater improvement compared to cholecalciferol: 78% [67‑85%] vs. 45% [24‑60%].
Sufficiency studies show a strong association between vitamin D sufficiency and outcomes. Meta analysis of the 89 studies with pooled effects using the most serious outcome reported shows 56% [50‑62%] improvement.
While many treatments have some level of efficacy, they do not replace vaccines and other measures to avoid infection. Only 11% of vitamin D treatment 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.
ImprovementStudies AuthorsPatients
Treatment RCTs 53% [23‑72%] 9 84 774
Treatment studies 45% [37‑53%] 53 529 66,371
Cholecalciferol treatment 42% [32‑51%] 44 418 58,390
Calcifediol/calcitriol treatment 61% [30‑78%] 9 111 7,981
Treatment mortality 50% [34‑62%] 31 283 12,599
Sufficiency studies 56% [50‑62%] 89 744 41,226
    
  
A
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Annweiler 89% 0.11 [0.03-0.48] 80,000IU death 10/57 5/9 Improvement, RR [CI] Dose (5d) Treatment Control Annweiler 63% 0.37 [0.06-2.21] 80,000IU death 3/16 10/32 Burahee 93% 0.07 [0.00-1.06] 400,000IU death 0/12 2/2 Loucera (PSM) 72% 0.28 [0.20-0.39] varies (c) death 193 (n) 193 (n) Asimi 97% 0.03 [0.00-0.44] 10,000IU ventilation 0/270 9/86 CT​1 Sánchez-Zuno (RCT) 89% 0.11 [0.01-1.86] 50,000IU severe case 0/22 4/20 Tau​2 = 0.20; I​2 = 41.2% Early treatment 81% 0.19 [0.10-0.35] 13/570 30/342 81% improvement Tan 80% 0.20 [0.04-0.93] 5,000IU oxygen 3/17 16/26 Improvement, RR [CI] Dose (5d) Treatment Control Krishnan 19% 0.81 [0.49-1.34] n/a death 8/16 84/136 Castillo (RCT) 85% 0.15 [0.01-2.93] 0.8mg (c) death 0/50 2/26 Rastogi (RCT) 53% 0.47 [0.24-0.92] 300,000IU viral+ 6/16 19/24 Murai (DB RCT) -49% 1.49 [0.55-4.05] 200,000IU death 9/119 6/118 Ling 80% 0.20 [0.08-0.48] 40,000IU death 73 (n) 253 (n) Jevalikar 82% 0.18 [0.02-1.69] 60,000IU death 1/128 3/69 Giannini 37% 0.63 [0.35-1.09] 400,000IU death/ICU 14/36 29/55 Nogués (QR) 79% 0.21 [0.10-0.43] 0.8mg (c) death 21/447 62/391 Lakkireddy (RCT) 61% 0.39 [0.08-1.91] 300,000IU death 2/44 5/43 Lohia 11% 0.89 [0.32-1.89] n/a death 26 (n) 69 (n) Alcala-Diaz 81% 0.19 [0.04-0.83] 0.8mg (c) death 4/79 90/458 Güven 25% 0.75 [0.37-1.24] 300,000IU death 43/113 30/62 Assiri -66% 1.66 [0.25-7.87] n/a death 12/90 2/28 Soliman (RCT) 63% 0.37 [0.09-2.78] 200,000IU death 7/40 3/16 Elamir (RCT) 86% 0.14 [0.01-2.63] 2.5μg (t) death 0/25 3/25 Yildiz 81% 0.19 [0.03-1.37] 300,000IU death 1/37 24/170 Maghbooli (DB RCT) 40% 0.60 [0.15-2.38] 125μg (c) death 3/53 5/53 Leal (RCT) 86% 0.14 [0.03-0.80] 10,000IU death 1/40 7/40 CT​1 Tau​2 = 0.28; I​2 = 61.9% Late treatment 56% 0.44 [0.32-0.63] 135/1,449 390/2,062 56% improvement Blanch-Rubió 8% 0.92 [0.63-1.36] n/a cases 62/1,303 47/799 Improvement, RR [CI] Dose (1m) Treatment Control Hernández -4% 1.04 [0.26-4.10] varies death 2/19 20/197 Annweiler 93% 0.07 [0.01-0.61] 50,000IU death 2/29 10/32 Cereda -73% 1.73 [0.81-2.74] varies death 7/18 40/152 Louca 8% 0.92 [0.88-0.97] n/a cases population-based cohort Cangiano 70% 0.30 [0.10-0.87] 50,000IU death 3/20 39/78 Vasheghani 30% 0.70 [0.33-1.49] n/a death 7/88 48/420 Ma 30% 0.70 [0.50-0.97] n/a cases 49/363 1,329/7,934 Sulli 76% 0.24 [0.17-0.36] n/a cases case control Mazziotti 19% 0.81 [0.45-1.47] varies death 116 (n) 232 (n) Meltzer 36% 0.64 [0.29-1.41] n/a cases 6/131 239/3,338 Holt 7% 0.93 [0.76-1.15] n/a cases 141/5,640 305/9,587 Ünsal 71% 0.29 [0.11-0.76] varies pneumonia 4/28 14/28 Oristrell 43% 0.57 [0.41-0.80] 7.4μg (t) death 2,296 (n) 3,407 (n) Levitus 31% 0.69 [0.37-1.24] varies severe case 65 (n) 64 (n) Dudley 22% 0.78 [0.23-2.61] 22,400IU symp. case 15/58 2/6 Fasano 42% 0.58 [0.34-0.99] n/a cases 13/329 92/1,157 Campi 88% 0.12 [0.09-0.15] n/a severe case case control Oristrell -1% 1.01 [0.93-1.09] varies (c) death population-based cohort Jimenez 50% 0.50 [0.28-0.90] 3.7μg (p) death 16/94 65/191 Israel 9% 0.91 [0.85-0.97] n/a hosp. 737/2,406 6,216/18,453 Mohseni 12% 0.88 [0.75-1.03] n/a cases 99/192 242/411 Sinaci 90% 0.10 [0.01-1.70] n/a severe case 0/36 7/123 Golabi -25% 1.25 [0.86-1.84] n/a cases case control Pecina -70% 1.70 [0.36-8.20] n/a death 29 (n) 63 (n) Bagheri 71% 0.29 [0.10-0.83] n/a progression 131 (n) 379 (n) Lázaro 27% 0.73 [0.07-7.96] n/a cases 1/97 2/142 Arroyo-Díaz -12% 1.12 [0.73-1.66] n/a death 50/189 167/1,078 Tau​2 = 0.10; I​2 = 91.6% Prophylaxis 34% 0.66 [0.57-0.78] 1,214/13,677 8,884/48,271 34% improvement All studies 45% 0.55 [0.47-0.63] 1,362/15,696 9,304/50,675 45% improvement All 53 vitamin D COVID-19 treatment studies vdmeta.com Nov 26, 2021 1 CT: study uses combined treatmentTau​2 = 0.14; I​2 = 89.4%; Z = 8.03 Effect extraction pre-specified, see appendix Favors vitamin D Favors control
    
  
B
    
  
C
    
  
D
Figure 1. A. Random effects meta-analysis of 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 five days for treatment, and the monthly dose for prophylaxis. Calcifediol, calcitriol, and paricalcitol treatment are indicated with (c), (t), and (p). For details of effect extraction and full dosage information see the appendix. B. Scatter plot showing the distribution of effects reported in serum level analysis (sufficiency) studies and treatment studies (the vertical lines and shaded boxes show the median and interquartile range). C and D. Chronological history of all reported effects for treatment studies and sufficiency studies.
Introduction
We analyze all significant studies regarding vitamin D and 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 studies analyzing outcomes based on sufficiency, for all treatment studies, for mortality results only, and for treatment studies within each treatment stage.
Vitamin D.
Vitamin D undergoes two conversion steps before reaching the biologically active form as shown in Figure 2. The first step is conversion to calcidiol, or 25(OH)D, in the liver. The second is conversion to calcitriol, or 1,25(OH)2D, which occurs in the kidneys, the immune system, and elsewhere. Calcitriol is the active, steroid-hormone form of vitamin D, which binds with vitamin D receptors found in most cells in the body. Vitamin D was first identified in relation to bone health, but is now known to have multiple functions, including an important role in the immune system [Carlberg, Martens]. For example, [Quraishi] show a strong association between pre-operative vitamin D levels and hospital-acquired infections, as shown in Figure 3. There is a significant delay involved in the conversion from cholecalciferol, therefore calcifediol (calcidiol) or calcitriol may be preferable for treatment.
Figure 2. Simplified view of vitamin D sources and conversion.
Figure 3. Risk of hospital-acquired infections as a function of pre-operative vitamin D levels, from [Quraishi].
Sufficiency.
Many vitamin D studies analyze outcomes based on serum vitamin D levels which may be maintained via sun exposure, diet, or supplementation. We refer to these studies as sufficiency studies, as they typically present outcomes based on vitamin D sufficiency. These studies do not establish a causal link between vitamin D and outcomes. In general, low vitamin D levels are correlated with many other factors that may influence COVID-19 susceptibility and severity. Therefore, beneficial effects found in these studies may be due to factors other than vitamin D. On the other hand, if vitamin D is causally linked to the observed benefits, it is possible that adjustments for correlated factors could obscure this relationship. COVID-19 disease may also affect vitamin D levels [Silva], suggesting additional caution in interpreting results for studies where the vitamin D levels are measured during the disease. For these reasons, we analyze sufficiency studies separately from treatment studies. We include all sufficiency studies that provide a comparison between two groups with low and high levels. A few studies only provide results as a function of change in vitamin D levels [Butler-Laporte, Raisi-Estabragh], which may not be indicative of results for deficiency/insufficiency versus sufficiency (increasing already sufficient levels may be less useful for example). A few studies show the average vitamin D level for patients in different groups [Al-Daghri, Chodick, D'Avolio, Kerget, Mardani, Vassiliou], all of which show lower D levels for worse outcomes. Other studies analyze vitamin D status and outcomes in geographic regions [Jayawardena, Marik, Papadimitriou, Rafailia, Rhodes, Sooriyaarachchi, Walrand, Yadav], all finding worse outcomes to be more likely with lower D levels.
Sufficiency studies vary widely in terms of when vitamin D levels were measured, the cutoff level used, and the population analyzed (for example studies with hospitalized patients exclude the effect of vitamin D on the risk of hospitalization). We do not analyze sufficiency studies in more detail because there are many controlled treatment studies now, and these studies provide better information on the use of vitamin D as a treatment for COVID-19.
Treatment.
For studies regarding treatment with vitamin D, we distinguish three stages as shown in Figure 4. Prophylaxis refers to regularly taking vitamin D before being infected in order to minimize the severity of infection. Due to the mechanism of action, vitamin D is unlikely to completely prevent infection, although it may prevent infection from reaching a level detectable by PCR. Early Treatment refers to treatment immediately or soon after symptoms appear, while Late Treatment refers to more delayed treatment.
Figure 4. Treatment stages.
Results
Figure 1 shows the effects reported in sufficiency studies and treatment studies. Figure 5 and 6 show results by treatment stage. Figure 7 shows a forest plot for random effects meta-analysis of sufficiency studies, while Figure 8, 9, 10, 11, 12, 13, 14, 15, and 16 show forest plots for all treatment studies with pooled effects, cholecalciferol studies, calcifediol/calcitriol studies, for studies reporting mortality, mechanical ventilation, ICU admission, hospitalization, and case results only. Table 1 summarizes the results.
Study typeNumber of studies reporting positive results Total number of studiesPercentage of studies reporting positive results Random effects meta-analysis results
Analysis of outcomes based on sufficiency 83 89 93.3% 56% improvement
RR 0.44 [0.38‑0.50]
p < 0.0001
Early treatment 6 6 100% 81% improvement
RR 0.19 [0.10‑0.35]
p < 0.0001
Late treatment 17 19 89.5% 56% improvement
RR 0.44 [0.32‑0.63]
p < 0.0001
Prophylaxis 22 28 78.6% 34% improvement
RR 0.66 [0.57‑0.78]
p < 0.0001
All treatment studies 45 53 84.9% 45% improvement
RR 0.55 [0.47‑0.63]
p < 0.0001
Table 1. Results.
    
  
Figure 5. Results by treatment stage.
    
  
Figure 6. Results by treatment stage.
    
  
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Lau 45% 0.55 [0.18-1.68] ICU 2/5 11/15 Improvement, RR [CI] Treatment Control Mendy 7% 0.93 [0.33-2.47] death 21/600 5/89 Panagiotou 52% 0.48 [0.24-0.95] ICU 8/44 34/90 Faul 69% 0.31 [0.10-0.95] ventilation 4/21 8/12 Merzon 46% 0.54 [0.23-1.02] hosp. 79 (n) 703 (n) Carpagnano 71% 0.29 [0.10-0.85] death 5/34 4/8 Im 73% 0.27 [0.15-0.47] cases case control Hastie 17% 0.83 [0.57-1.20] death population-based cohort Baktash 29% 0.71 [0.18-2.78] death 4/31 6/39 Meltzer 44% 0.56 [0.36-0.89] cases 39/317 32/172 Israel 21% 0.79 [0.75-0.84] cases population-based cohort Radujkovic 93% 0.07 [0.01-0.34] death 144 (n) 12 (n) Kaufman 53% 0.47 [0.30-0.74] cases population-based cohort Maghbooli 52% 0.48 [0.22-1.05] death 7/72 27/134 Karahan 83% 0.17 [0.08-0.41] death 5/46 64/103 Yılmaz 73% 0.27 [0.01-5.14] severe case 0/11 2/29 Faniyi 29% 0.71 [0.59-0.86] seropositive 170/331 44/61 Ye 93% 0.07 [0.01-0.81] hosp. 2/36 8/26 Macaya 55% 0.45 [0.15-1.06] severe case 11/35 20/45 Tomasa-Irriguible 35% 0.65 [0.31-1.24] ventilation 15/27 18/78 Hernández 83% 0.17 [0.07-0.41] death/ICU 35 (n) 162 (n) Abrishami 76% 0.24 [0.06-0.93] death 3/47 9/26 Cereda -120% 2.20 [1.01-3.22] death 10/30 24/99 Walk -0% 1.00 [0.60-1.67] int./death 48/110 10/23 Luo 63% 0.37 [0.17-0.81] progression 335 (n) 560 (n) Jain 85% 0.15 [0.04-0.61] death 2/64 19/90 De Smet 70% 0.30 [0.10-0.80] death 7/77 20/109 Katz 78% 0.22 [0.17-0.27] cases population-based cohort Alguwaihes 86% 0.14 [0.04-0.59] death 111 (n) 328 (n) Vassiliou 91% 0.09 [0.01-1.51] death 0/15 5/15 Abdollahi 54% 0.46 [0.29-0.73] cases 108 (n) 294 (n) Szeto -6% 1.06 [0.49-2.26] death 14/58 8/35 Karonova 79% 0.21 [0.03-1.28] death 1/23 12/57 Amin -32% 1.32 [0.88-1.89] progression population-based cohort Angelidi 88% 0.12 [0.02-0.60] death 6/65 20/79 Li 36% 0.64 [0.53-0.78] severe case population-based cohort Bennouar 86% 0.14 [0.04-0.50] death 4/30 15/32 Vasheghani 64% 0.36 [0.20-0.65] ICU 13/185 53/323 Orchard 59% 0.41 [0.22-0.76] ICU 9/40 41/75 Barassi 65% 0.35 [0.05-2.69] death 1/31 8/87 Tehrani 48% 0.52 [0.29-0.96] death 34/180 9/25 Demir 89% 0.11 [0.03-0.40] severe case 13 (n) 99 (n) Susianti 91% 0.09 [0.01-1.34] death 0/8 9/42 Basaran 69% 0.31 [0.03-0.90] severe case 82/119 80/85 Infante 55% 0.45 [0.19-1.10] death 4/19 55/118 Gavioli -5% 1.05 [0.78-1.40] death 80/260 52/177 Sulli 79% 0.21 [0.15-0.29] cases case control Ricci 88% 0.12 [0.01-2.28] death 0/30 3/22 Lohia 15% 0.85 [0.47-1.41] death 88 (n) 95 (n) Mazziotti 2% 0.98 [0.61-1.48] death 187 (n) 161 (n) Charoenngam 34% 0.66 [0.32-1.33] death 12/100 29/187 Vanegas-Cedillo 53% 0.47 [0.28-0.81] death 95/494 21/57 Meltzer 35% 0.65 [0.39-1.10] cases 61/1,097 118/1,251 Freitas 41% 0.59 [0.38-0.91] death 23/179 68/311 Gaudio 79% 0.21 [0.14-0.31] cases case control Bayramoğlu 70% 0.30 [0.09-0.77] severe case 10/60 24/43 Livingston 51% 0.49 [0.25-0.83] cases 16/52 31/52 Ünsal 81% 0.19 [0.01-3.87] death 0/29 2/27 Savitri 88% 0.12 [0.05-0.32] symp. case 3/25 17/17 Li 9% 0.91 [0.79-1.06] cases 610/13,650 290/4,498 AlSafar 59% 0.41 [0.16-0.99] death 16/337 10/127 Sánchez-Zuno 6% 0.94 [0.44-2.02] severe case 4/8 18/34 Pimental 29% 0.71 [0.15-3.43] death 3/17 2/8 Diaz-Curiel 73% 0.27 [0.07-0.67] ICU 3/214 91/1,017 Dror 85% 0.15 [0.04-0.44] severe case 109/120 76/133 Campi 24% 0.76 [0.31-1.83] death 6/39 13/64 Jude 72% 0.28 [0.25-0.32] hosp. n/a n/a Zelzer 46% 0.54 [0.29-0.98] death 24/121 10/27 Bianconi 18% 0.82 [0.41-1.65] death 94 (n) 106 (n) Jimenez -8% 1.08 [0.59-1.98] death 50 (n) 110 (n) Cozier 39% 0.61 [0.39-0.96] cases 94/1,601 33/373 Al-Salman 44% 0.56 [0.33-0.95] ICU 113 (n) 337 (n) Matin 66% 0.34 [0.21-0.56] cases case control Nimavat 50% 0.50 [0.19-1.27] death 13/131 5/25 Ribeiro 50% 0.50 [0.28-0.87] cases n/a n/a Eden 64% 0.36 [0.11-1.21] death 3/26 8/25 Alpcan 73% 0.27 [0.20-0.36] cases case control Sinaci 79% 0.21 [0.10-0.43] m/s case 8/100 23/59 di Filippo 11% 0.89 [0.35-2.29] death 5/28 12/60 Golabi 90% 0.10 [0.04-0.24] symp. 34 (n) 10 (n) Pecina 36% 0.64 [0.04-6.25] death 6/77 1/15 Karonova 78% 0.22 [0.07-0.67] death 8/96 10/37 Derakhshanian 45% 0.55 [0.30-0.98] death 148 (n) 142 (n) Afaghi 55% 0.45 [0.34-0.59] death 97/537 51/109 Ramirez-Sandoval 32% 0.68 [0.57-0.83] death 2,337 (n) 571 (n) Hurst 68% 0.32 [0.13-0.73] death 68 (n) 191 (n) Atanasovska 41% 0.59 [0.16-2.23] death 2/9 9/24 Asghar 53% 0.47 [0.22-0.99] death 73 (n) 18 (n) Gönen 66% 0.34 [0.04-3.22] death 1/80 3/82 All studies 56% 0.44 [0.38-0.50] 1,843/26,245 1,710/14,981 56% improvement All 89 vitamin D COVID-19 sufficiency studies vdmeta.com Nov 26, 2021 Tau​2 = 0.33; I​2 = 91.7%; Z = 11.20 Effect extraction pre-specified, see appendix Favors vitamin D Favors control
Figure 7. Random effects meta-analysis for sufficiency studies. This plot pools studies with different effects, different vitamin D cutoff levels and measurement times, and studies may be within hospitalized patients, excluding the risk of hospitalization. However, the prevalence of positive effects is notable.
    
  
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Annweiler 89% 0.11 [0.03-0.48] 80,000IU death 10/57 5/9 Improvement, RR [CI] Dose (5d) Treatment Control Annweiler 63% 0.37 [0.06-2.21] 80,000IU death 3/16 10/32 Burahee 93% 0.07 [0.00-1.06] 400,000IU death 0/12 2/2 Loucera (PSM) 72% 0.28 [0.20-0.39] varies (c) death 193 (n) 193 (n) Asimi 97% 0.03 [0.00-0.44] 10,000IU ventilation 0/270 9/86 CT​1 Sánchez-Zuno (RCT) 89% 0.11 [0.01-1.86] 50,000IU severe case 0/22 4/20 Tau​2 = 0.20; I​2 = 41.2% Early treatment 81% 0.19 [0.10-0.35] 13/570 30/342 81% improvement Tan 80% 0.20 [0.04-0.93] 5,000IU oxygen 3/17 16/26 Improvement, RR [CI] Dose (5d) Treatment Control Krishnan 19% 0.81 [0.49-1.34] n/a death 8/16 84/136 Castillo (RCT) 85% 0.15 [0.01-2.93] 0.8mg (c) death 0/50 2/26 Rastogi (RCT) 53% 0.47 [0.24-0.92] 300,000IU viral+ 6/16 19/24 Murai (DB RCT) -49% 1.49 [0.55-4.05] 200,000IU death 9/119 6/118 Ling 80% 0.20 [0.08-0.48] 40,000IU death 73 (n) 253 (n) Jevalikar 82% 0.18 [0.02-1.69] 60,000IU death 1/128 3/69 Giannini 37% 0.63 [0.35-1.09] 400,000IU death/ICU 14/36 29/55 Nogués (QR) 79% 0.21 [0.10-0.43] 0.8mg (c) death 21/447 62/391 Lakkireddy (RCT) 61% 0.39 [0.08-1.91] 300,000IU death 2/44 5/43 Lohia 11% 0.89 [0.32-1.89] n/a death 26 (n) 69 (n) Alcala-Diaz 81% 0.19 [0.04-0.83] 0.8mg (c) death 4/79 90/458 Güven 25% 0.75 [0.37-1.24] 300,000IU death 43/113 30/62 Assiri -66% 1.66 [0.25-7.87] n/a death 12/90 2/28 Soliman (RCT) 63% 0.37 [0.09-2.78] 200,000IU death 7/40 3/16 Elamir (RCT) 86% 0.14 [0.01-2.63] 2.5μg (t) death 0/25 3/25 Yildiz 81% 0.19 [0.03-1.37] 300,000IU death 1/37 24/170 Maghbooli (DB RCT) 40% 0.60 [0.15-2.38] 125μg (c) death 3/53 5/53 Leal (RCT) 86% 0.14 [0.03-0.80] 10,000IU death 1/40 7/40 CT​1 Tau​2 = 0.28; I​2 = 61.9% Late treatment 56% 0.44 [0.32-0.63] 135/1,449 390/2,062 56% improvement Blanch-Rubió 8% 0.92 [0.63-1.36] n/a cases 62/1,303 47/799 Improvement, RR [CI] Dose (1m) Treatment Control Hernández -4% 1.04 [0.26-4.10] varies death 2/19 20/197 Annweiler 93% 0.07 [0.01-0.61] 50,000IU death 2/29 10/32 Cereda -73% 1.73 [0.81-2.74] varies death 7/18 40/152 Louca 8% 0.92 [0.88-0.97] n/a cases population-based cohort Cangiano 70% 0.30 [0.10-0.87] 50,000IU death 3/20 39/78 Vasheghani 30% 0.70 [0.33-1.49] n/a death 7/88 48/420 Ma 30% 0.70 [0.50-0.97] n/a cases 49/363 1,329/7,934 Sulli 76% 0.24 [0.17-0.36] n/a cases case control Mazziotti 19% 0.81 [0.45-1.47] varies death 116 (n) 232 (n) Meltzer 36% 0.64 [0.29-1.41] n/a cases 6/131 239/3,338 Holt 7% 0.93 [0.76-1.15] n/a cases 141/5,640 305/9,587 Ünsal 71% 0.29 [0.11-0.76] varies pneumonia 4/28 14/28 Oristrell 43% 0.57 [0.41-0.80] 7.4μg (t) death 2,296 (n) 3,407 (n) Levitus 31% 0.69 [0.37-1.24] varies severe case 65 (n) 64 (n) Dudley 22% 0.78 [0.23-2.61] 22,400IU symp. case 15/58 2/6 Fasano 42% 0.58 [0.34-0.99] n/a cases 13/329 92/1,157 Campi 88% 0.12 [0.09-0.15] n/a severe case case control Oristrell -1% 1.01 [0.93-1.09] varies (c) death population-based cohort Jimenez 50% 0.50 [0.28-0.90] 3.7μg (p) death 16/94 65/191 Israel 9% 0.91 [0.85-0.97] n/a hosp. 737/2,406 6,216/18,453 Mohseni 12% 0.88 [0.75-1.03] n/a cases 99/192 242/411 Sinaci 90% 0.10 [0.01-1.70] n/a severe case 0/36 7/123 Golabi -25% 1.25 [0.86-1.84] n/a cases case control Pecina -70% 1.70 [0.36-8.20] n/a death 29 (n) 63 (n) Bagheri 71% 0.29 [0.10-0.83] n/a progression 131 (n) 379 (n) Lázaro 27% 0.73 [0.07-7.96] n/a cases 1/97 2/142 Arroyo-Díaz -12% 1.12 [0.73-1.66] n/a death 50/189 167/1,078 Tau​2 = 0.10; I​2 = 91.6% Prophylaxis 34% 0.66 [0.57-0.78] 1,214/13,677 8,884/48,271 34% improvement<