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Vitamin A for COVID-19: real-time meta analysis of 11 studies
Covid Analysis, August 14, 2022, DRAFT
https://c19early.com/vameta.html
0 0.5 1 1.5+ All studies 50% 8 17,951 Improvement, Studies, Patients Relative Risk Mortality 63% 4 267 ICU admission 67% 1 40 Hospitalization 26% 2 2,208 Recovery 37% 2 100 Cases 64% 2 15,436 Viral clearance 44% 1 40 RCTs 87% 2 100 RCT mortality 87% 2 100 Peer-reviewed 63% 4 17,575 Sufficiency 73% 3 217 Prophylaxis 49% 3 17,584 Early 79% 2 240 Late 48% 3 127 Vitamin A for COVID-19 c19early.com/va Aug 2022 Favorsvitamin A Favorscontrol after exclusions
Statistically significant improvements are seen for recovery, cases, and viral clearance. 4 studies from 3 independent teams in 3 different countries show statistically significant improvements in isolation (2 for the most serious outcome).
Meta analysis using the most serious outcome reported shows 50% [-9‑77%] improvement, without reaching statistical significance. Results are better for Randomized Controlled Trials, similar after exclusions, and better for peer-reviewed studies. Results are consistent with early treatment being more effective than late treatment.
Sufficiency studies, analyzing outcomes based on serum levels, show 73% [51‑85%] improvement for patients with higher vitamin A levels (3 studies).
0 0.5 1 1.5+ All studies 50% 8 17,951 Improvement, Studies, Patients Relative Risk Mortality 63% 4 267 ICU admission 67% 1 40 Hospitalization 26% 2 2,208 Recovery 37% 2 100 Cases 64% 2 15,436 Viral clearance 44% 1 40 RCTs 87% 2 100 RCT mortality 87% 2 100 Peer-reviewed 63% 4 17,575 Sufficiency 73% 3 217 Prophylaxis 49% 3 17,584 Early 79% 2 240 Late 48% 3 127 Vitamin A for COVID-19 c19early.com/va Aug 2022 Favorsvitamin A Favorscontrol after exclusions
While many treatments have some level of efficacy, they do not replace vaccines and other measures to avoid infection. Only 25% of vitamin A studies show zero events in the treatment arm. Multiple treatments are typically used in combination, and other treatments may be more effective.
No treatment, vaccine, or intervention is 100% available and effective for all variants. All practical, effective, and safe means should be used. Denying the efficacy of treatments increases mortality, morbidity, collateral damage, and endemic risk.
All data to reproduce this paper and sources are in the appendix.
Highlights
Vitamin A reduces risk for COVID-19 with very high confidence for recovery, cases, and viral clearance, low confidence for pooled analysis, and very low confidence for ICU admission, hospitalization, and progression.
We show traditional outcome specific analyses and combined evidence from all studies, incorporating treatment delay, a primary confounding factor in COVID-19 studies.
Real-time updates and corrections, transparent analysis with all results in the same format, consistent protocol for 43 treatments.
A
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Al-Sumiadai 86% 0.14 [0.03-0.61] death 2/70 14/70 Improvement, RR [CI] Treatment Control Al-Sumiadai 67% 0.33 [0.07-1.57] progression 2/50 6/50 Tau​2 = 0.00, I​2 = 0.0%, p = 0.004 Early treatment 79% 0.21 [0.07-0.61] 4/120 20/120 79% improvement Sarohan -282% 3.83 [1.58-9.24] death 9/10 4/17 Improvement, RR [CI] Treatment Control Beigm.. (SB RCT) 89% 0.11 [0.01-1.98] death 0/30 4/30 ICU patients CT​1 Elkazzaz (RCT) 86% 0.14 [0.01-2.60] death 0/20 3/20 Tau​2 = 4.35, I​2 = 77.9%, p = 0.65 Late treatment 48% 0.52 [0.04-7.80] 9/60 11/67 48% improvement Al-Sumiadai 64% 0.36 [0.23-0.54] cases 20/97 65/112 Improvement, RR [CI] Treatment Control Holt 56% 0.44 [0.06-2.96] cases 1/91 445/15,136 Nimer 21% 0.79 [0.45-1.35] hosp. 15/144 204/2,004 Tau​2 = 0.19, I​2 = 65.4%, p = 0.046 Prophylaxis 49% 0.51 [0.27-0.99] 36/332 714/17,252 49% improvement All studies 50% 0.50 [0.23-1.09] 49/512 745/17,439 50% improvement 8 vitamin A COVID-19 studies c19early.com/va Aug 2022 Tau​2 = 0.74, I​2 = 77.1%, p = 0.08 Effect extraction pre-specified(most serious outcome, see appendix) 1 CT: study uses combined treatment Favors vitamin A Favors control
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Al-Sumiadai 86% death Improvement Relative Risk [CI] Al-Sumiadai 67% progression Tau​2 = 0.00, I​2 = 0.0%, p = 0.004 Early treatment 79% 79% improvement Sarohan -282% death Beigm.. (SB RCT) 89% death ICU patients CT​1 Elkazzaz (RCT) 86% death Tau​2 = 4.35, I​2 = 77.9%, p = 0.65 Late treatment 48% 48% improvement Al-Sumiadai 64% case Holt 56% case Nimer 21% hospitalization Tau​2 = 0.19, I​2 = 65.4%, p = 0.046 Prophylaxis 49% 49% improvement All studies 50% 50% improvement 8 vitamin A COVID-19 studies c19early.com/va Aug 2022 Tau​2 = 0.74, I​2 = 77.1%, p = 0.08 Protocol pre-specified/rotate for details1 CT: study uses combined treatment Favors vitamin A Favors control
Figure 1. A. Random effects meta-analysis. This plot shows pooled effects, discussion can be found in the heterogeneity section, and results for specific outcomes can be found in the individual outcome analyses. Effect extraction is pre-specified, using the most serious outcome reported. For details of effect extraction see the appendix. B. Scatter plot showing the distribution of effects reported in studies. C. History of all reported effects (chronological within treatment stages).
Introduction
We analyze all significant studies concerning the use of vitamin A 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 individual outcomes, for peer-reviewed studies, for Randomized Controlled Trials (RCTs), and after exclusions.
Figure 2 shows stages of possible treatment for COVID-19. Prophylaxis refers to regularly taking medication before becoming sick, in order to prevent or minimize infection. Early Treatment refers to treatment immediately or soon after symptoms appear, while Late Treatment refers to more delayed treatment.
Figure 2. Treatment stages.
Preclinical Research
3 In Silico studies support the efficacy of vitamin A [Chakraborty, Li, Pandya].
2 In Vitro studies support the efficacy of vitamin A [Morita, Tong].
Preclinical research is an important part of the development of treatments, however results may be very different in clinical trials. Preclinical results are not used in this paper.
Results
Figure 3 shows a visual overview of the results, with details in Table 1 and Table 2. Figure 4, 5, 6, 7, 8, 9, 10, 11, 12, and 13 show forest plots for a random effects meta-analysis of all studies with pooled effects, mortality results, ICU admission, hospitalization, progression, recovery, cases, viral clearance, sufficiency studies, and peer reviewed studies.
0 0.5 1 1.5+ ALL STUDIES MORTALITY ICU ADMISSION HOSPITALIZATION RECOVERY CASES VIRAL CLEARANCE RANDOMIZED CONTROLLED TRIALS RCT MORTALITY PEER-REVIEWED SUFFICIENCY After Exclusions ALL STUDIES All Prophylaxis Early Late Vitamin A for COVID-19 C19EARLY.COM/VA AUG 2022
Figure 3. Overview of results.
Treatment timeNumber of studies reporting positive effects Total number of studiesPercentage of studies reporting positive effects Random effects meta-analysis results
Early treatment 2 2 100% 79% improvement
RR 0.21 [0.07‑0.61]
p = 0.004
Late treatment 2 3 66.7% 48% improvement
RR 0.52 [0.04‑7.80]
p = 0.65
Prophylaxis 3 3 100% 49% improvement
RR 0.51 [0.27‑0.99]
p = 0.046
All studies 7 8 87.5% 50% improvement
RR 0.50 [0.23‑1.09]
p = 0.08
Table 1. Results by treatment stage.
Studies Early treatment Late treatment Prophylaxis PatientsAuthors
All studies 879% [39‑93%]48% [-680‑96%]49% [1‑73%] 17,951 61
With exclusions 567% [-57‑93%]87% [3‑98%]48% [-14‑76%] 2,557 20
Peer-reviewed 486% [39‑97%]89% [-98‑99%]24% [-23‑53%] 17,575 47
Randomized Controlled TrialsRCTs 287% [3‑98%] 100 10
Table 2. Results by treatment stage for all studies and with different exclusions.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Al-Sumiadai 86% 0.14 [0.03-0.61] death 2/70 14/70 Improvement, RR [CI] Treatment Control Al-Sumiadai 67% 0.33 [0.07-1.57] progression 2/50 6/50 Tau​2 = 0.00, I​2 = 0.0%, p = 0.004 Early treatment 79% 0.21 [0.07-0.61] 4/120 20/120 79% improvement Sarohan -282% 3.83 [1.58-9.24] death 9/10 4/17 Improvement, RR [CI] Treatment Control Beigm.. (SB RCT) 89% 0.11 [0.01-1.98] death 0/30 4/30 ICU patients CT​1 Elkazzaz (RCT) 86% 0.14 [0.01-2.60] death 0/20 3/20 Tau​2 = 4.35, I​2 = 77.9%, p = 0.65 Late treatment 48% 0.52 [0.04-7.80] 9/60 11/67 48% improvement Al-Sumiadai 64% 0.36 [0.23-0.54] cases 20/97 65/112 Improvement, RR [CI] Treatment Control Holt 56% 0.44 [0.06-2.96] cases 1/91 445/15,136 Nimer 21% 0.79 [0.45-1.35] hosp. 15/144 204/2,004 Tau​2 = 0.19, I​2 = 65.4%, p = 0.046 Prophylaxis 49% 0.51 [0.27-0.99] 36/332 714/17,252 49% improvement All studies 50% 0.50 [0.23-1.09] 49/512 745/17,439 50% improvement 8 vitamin A COVID-19 studies c19early.com/va Aug 2022 Tau​2 = 0.74, I​2 = 77.1%, p = 0.08 Effect extraction pre-specified(most serious outcome, see appendix) 1 CT: study uses combined treatment Favors vitamin A Favors control
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Al-Sumiadai 86% death Improvement Relative Risk [CI] Al-Sumiadai 67% progression Tau​2 = 0.00, I​2 = 0.0%, p = 0.004 Early treatment 79% 79% improvement Sarohan -282% death Beigm.. (SB RCT) 89% death ICU patients CT​1 Elkazzaz (RCT) 86% death Tau​2 = 4.35, I​2 = 77.9%, p = 0.65 Late treatment 48% 48% improvement Al-Sumiadai 64% case Holt 56% case Nimer 21% hospitalization Tau​2 = 0.19, I​2 = 65.4%, p = 0.046 Prophylaxis 49% 49% improvement All studies 50% 50% improvement 8 vitamin A COVID-19 studies c19early.com/va Aug 2022 Tau​2 = 0.74, I​2 = 77.1%, p = 0.08 Protocol pre-specified/rotate for details1 CT: study uses combined treatment Favors vitamin A Favors control
Figure 4. Random effects meta-analysis for all studies with pooled effects. This plot shows pooled effects, discussion can be found in the heterogeneity section, and results for specific outcomes can be found in the individual outcome analyses. Effect extraction is pre-specified, using the most serious outcome reported. For details of effect extraction see the appendix.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Al-Sumiadai 86% 0.14 [0.03-0.61] 2/70 14/70 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.0083 Early treatment 86% 0.14 [0.03-0.61] 2/70 14/70 86% improvement Sarohan -282% 3.83 [1.58-9.24] 9/10 4/17 Improvement, RR [CI] Treatment Control Beigm.. (SB RCT) 89% 0.11 [0.01-1.98] 0/30 4/30 ICU patients CT​1 Elkazzaz (RCT) 86% 0.14 [0.01-2.60] 0/20 3/20 Tau​2 = 4.35, I​2 = 77.9%, p = 0.65 Late treatment 48% 0.52 [0.04-7.80] 9/60 11/67 48% improvement All studies 63% 0.37 [0.04-3.46] 11/130 25/137 63% improvement 4 vitamin A COVID-19 mortality results c19early.com/va Aug 2022 Tau​2 = 4.13, I​2 = 84.7%, p = 0.39 1 CT: study uses combined treatment Favors vitamin A Favors control
Figure 5. Random effects meta-analysis for mortality results.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Elkazzaz (RCT) 67% 0.33 [0.08-1.46] 2/20 6/20 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.14 Late treatment 67% 0.33 [0.08-1.46] 2/20 6/20 67% improvement All studies 67% 0.33 [0.08-1.46] 2/20 6/20 67% improvement 1 vitamin A COVID-19 ICU result c19early.com/va Aug 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.14 Favors vitamin A Favors control
Figure 6. Random effects meta-analysis for ICU admission.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Beigm.. (SB RCT) 41% 0.59 [0.17-1.28] hosp. 4/30 16/30 ICU patients CT​1 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.29 Late treatment 41% 0.59 [0.17-1.28] 4/30 16/30 41% improvement Nimer 21% 0.79 [0.45-1.35] hosp. 15/144 204/2,004 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.35 Prophylaxis 21% 0.79 [0.45-1.35] 15/144 204/2,004 21% improvement All studies 26% 0.74 [0.48-1.16] 19/174 220/2,034 26% improvement 2 vitamin A COVID-19 hospitalization results c19early.com/va Aug 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.19 1 CT: study uses combined treatment Favors vitamin A Favors control
Figure 7. Random effects meta-analysis for hospitalization.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Al-Sumiadai 67% 0.33 [0.07-1.57] 2/50 6/50 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.17 Early treatment 67% 0.33 [0.07-1.57] 2/50 6/50 67% improvement All studies 67% 0.33 [0.07-1.57] 2/50 6/50 67% improvement 1 vitamin A COVID-19 progression result c19early.com/va Aug 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.17 Favors vitamin A Favors control
Figure 8. Random effects meta-analysis for progression.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Beigm.. (SB RCT) 45% 0.55 [0.38-0.78] SOFA 30 (n) 30 (n) ICU patients CT​1 Improvement, RR [CI] Treatment Control Elkazzaz (RCT) 35% 0.65 [0.55-0.76] recov. time 20 (n) 20 (n) Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Late treatment 37% 0.63 [0.54-0.73] 0/50 0/50 37% improvement All studies 37% 0.63 [0.54-0.73] 0/50 0/50 37% improvement 2 vitamin A COVID-19 recovery results c19early.com/va Aug 2022 Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 1 CT: study uses combined treatment Favors vitamin A Favors control
Figure 9. Random effects meta-analysis for recovery.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Al-Sumiadai 64% 0.36 [0.23-0.54] cases 20/97 65/112 Improvement, RR [CI] Treatment Control Holt 56% 0.44 [0.06-2.96] cases 1/91 445/15,136 Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Prophylaxis 64% 0.36 [0.24-0.54] 21/188 510/15,248 64% improvement All studies 64% 0.36 [0.24-0.54] 21/188 510/15,248 64% improvement 2 vitamin A COVID-19 case results c19early.com/va Aug 2022 Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Favors vitamin A Favors control
Figure 10. Random effects meta-analysis for cases.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Elkazzaz (RCT) 44% 0.56 [0.48-0.65] viral time 20 (n) 20 (n) Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Late treatment 44% 0.56 [0.48-0.65] 0/20 0/20 44% improvement All studies 44% 0.56 [0.48-0.65] 0/20 0/20 44% improvement 1 vitamin A COVID-19 viral clearance result c19early.com/va Aug 2022 Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Favors vitamin A Favors control
Figure 11. Random effects meta-analysis for viral clearance.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Tomasa-Irriguible 71% 0.29 [0.10-0.67] ventilation 4/34 48/86 Improvement, RR [CI] High Levels Low Levels Tepasse 70% 0.30 [0.07-0.97] death 4/29 5/11 Voelkle 76% 0.24 [0.07-0.69] death/ICU 4/35 11/22 All studies 73% 0.27 [0.15-0.49] 12/98 64/119 73% improvement 3 vitamin A COVID-19 sufficiency studies c19early.com/va Aug 2022 Tau​2 = 0.00, I​2 = 0.0%, p < 0.0001 Effect extraction pre-specified(most serious outcome, see appendix) Favors vitamin A Favors control
Figure 12. Random effects meta-analysis for sufficiency studies. Effect extraction is pre-specified, using the most serious outcome reported, see the appendix for details.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Al-Sumiadai 86% 0.14 [0.03-0.61] death 2/70 14/70 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.0083 Early treatment 86% 0.14 [0.03-0.61] 2/70 14/70 86% improvement Beigm.. (SB RCT) 89% 0.11 [0.01-1.98] death 0/30 4/30 ICU patients CT​1 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.13 Late treatment 89% 0.11 [0.01-1.98] 0/30 4/30 89% improvement Holt 56% 0.44 [0.06-2.96] cases 1/91 445/15,136 Improvement, RR [CI] Treatment Control Nimer 21% 0.79 [0.45-1.35] hosp. 15/144 204/2,004 Tau​2 = 0.00, I​2 = 0.0%, p = 0.27 Prophylaxis 24% 0.76 [0.47-1.23] 16/235 649/17,140 24% improvement All studies 63% 0.37 [0.13-1.06] 18/335 667/17,240 63% improvement 4 vitamin A COVID-19 peer reviewed trials c19early.com/va Aug 2022 Tau​2 = 0.58, I​2 = 52.8%, p = 0.064 Effect extraction pre-specified(most serious outcome, see appendix) 1 CT: study uses combined treatment Favors vitamin A Favors control
Figure 13. Random effects meta-analysis for peer reviewed studies. [Zeraatkar] analyze 356 COVID-19 trials, finding no significant evidence that peer-reviewed studies are more trustworthy. They also show extremely slow review times during a pandemic. Authors recommend using preprint evidence, with appropriate checks for potential falsified data, which provides higher certainty much earlier. Effect extraction is pre-specified, using the most serious outcome reported, see the appendix for details.
Exclusions
To avoid bias in the selection of studies, we analyze all non-retracted studies. Here we show the results after excluding studies with major issues likely to alter results, non-standard studies, and studies where very minimal detail is currently available. Our bias evaluation is based on analysis of each study and identifying when there is a significant chance that limitations will substantially change the outcome of the study. We believe this can be more valuable than checklist-based approaches such as Cochrane GRADE, which may underemphasize serious issues not captured in the checklists, overemphasize issues unlikely to alter outcomes in specific cases (for example, lack of blinding for an objective mortality outcome, or certain specifics of randomization with a very large effect size), or be easily influenced by potential bias. However, they can also be very high quality.
The studies excluded are as below. Figure 14 shows a forest plot for random effects meta-analysis of all studies after exclusions.
[Al-Sumiadai], minimal details of groups provided.
[Holt], significant unadjusted confounding possible.
[Sarohan], unadjusted results with no group details.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Al-Sumiadai 67% 0.33 [0.07-1.57] progression 2/50 6/50 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.17 Early treatment 67% 0.33 [0.07-1.57] 2/50 6/50 67% improvement Beigm.. (SB RCT) 89% 0.11 [0.01-1.98] death 0/30 4/30 ICU patients CT​1 Improvement, RR [CI] Treatment Control Elkazzaz (RCT) 86% 0.14 [0.01-2.60] death 0/20 3/20 Tau​2 = 0.00, I​2 = 0.0%, p = 0.046 Late treatment 87% 0.13 [0.02-0.97] 0/50 7/50 87% improvement Al-Sumiadai 64% 0.36 [0.23-0.54] cases 20/97 65/112 Improvement, RR [CI] Treatment Control Nimer 21% 0.79 [0.45-1.35] hosp. 15/144 204/2,004 Tau​2 = 0.26, I​2 = 82.6%, p = 0.1 Prophylaxis 48% 0.52 [0.24-1.14] 35/241 269/2,116 48% improvement All studies 56% 0.44 [0.25-0.80] 37/341 282/2,216 56% improvement 5 vitamin A COVID-19 studies after exclusions c19early.com/va Aug 2022 Tau​2 = 0.17, I​2 = 47.8%, p = 0.0069 Effect extraction pre-specified(most serious outcome, see appendix) 1 CT: study uses combined treatment Favors vitamin A Favors control
Figure 14. Random effects meta-analysis for all studies after exclusions. This plot shows pooled effects, discussion can be found in the heterogeneity section, and results for specific outcomes can be found in the individual outcome analyses. Effect extraction is pre-specified, using the most serious outcome reported. For details of effect extraction see the appendix.
Randomized Controlled Trials (RCTs)
Figure 15 shows the distribution of results for Randomized Controlled Trials and other studies, and a chronological history of results. The median effect size for RCTs is 87% improvement, compared to 67% for other studies. Figure 16 shows a forest plot for random effects meta-analysis of all Randomized Controlled Trials. Table 3 summarizes the results.
Figure 15. The distribution of results for Randomized Controlled Trials and other studies, and a chronological history of results.
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Beigm.. (SB RCT) 89% 0.11 [0.01-1.98] death 0/30 4/30 ICU patients CT​1 Improvement, RR [CI] Treatment Control Elkazzaz (RCT) 86% 0.14 [0.01-2.60] death 0/20 3/20 Tau​2 = 0.00, I​2 = 0.0%, p = 0.046 Late treatment 87% 0.13 [0.02-0.97] 0/50 7/50 87% improvement All studies 87% 0.13 [0.02-0.97] 0/50 7/50 87% improvement 2 vitamin A COVID-19 Randomized Controlled Trials c19early.com/va Aug 2022 Tau​2 = 0.00, I​2 = 0.0%, p = 0.046 Effect extraction pre-specified(most serious outcome, see appendix) 1 CT: study uses combined treatment Favors vitamin A Favors control
Figure 16. Random effects meta-analysis for all Randomized Controlled Trials. This plot shows pooled effects, discussion can be found in the heterogeneity section, and results for specific outcomes can be found in the individual outcome analyses. Effect extraction is pre-specified, using the most serious outcome reported. For details of effect extraction see the appendix.
Treatment timeNumber of studies reporting positive effects Total number of studiesPercentage of studies reporting positive effects Random effects meta-analysis results
Randomized Controlled Trials 2 2 100% 87% improvement
RR 0.13 [0.02‑0.97]
p = 0.046
RCT mortality results 2 2 100% 87% improvement
RR 0.13 [0.02‑0.97]
p = 0.046
Table 3. Randomized Controlled Trial results.
Heterogeneity
Heterogeneity in COVID-19 studies arises from many factors including:
Treatment delay.
The time between infection or the onset of symptoms and treatment may critically affect how well a treatment works. For example an antiviral may be very effective when used early but may not be effective in late stage disease, and may even be harmful. Oseltamivir, for example, is generally only considered effective for influenza when used within 0-36 or 0-48 hours [McLean, Treanor]. Figure 17 shows a mixed-effects meta-regression for efficacy as a function of treatment delay in COVID-19 studies from 43 treatments, showing that efficacy declines rapidly with treatment delay. Early treatment is critical for COVID-19.
Figure 17. Meta-regression showing efficacy as a function of treatment delay in COVID-19 studies from 43 treatments. Early treatment is critical.
Patient demographics.
Details of the patient population including age and comorbidities may critically affect how well a treatment works. For example, many COVID-19 studies with relatively young low-comorbidity patients show all patients recovering quickly with or without treatment. In such cases, there is little room for an effective treatment to improve results (as in [López-Medina]).
Effect measured.
Efficacy may differ significantly depending on the effect measured, for example a treatment may be very effective at reducing mortality, but less effective at minimizing cases or hospitalization. Or a treatment may have no effect on viral clearance while still being effective at reducing mortality.
Variants.
There are many different variants of SARS-CoV-2 and efficacy may depend critically on the distribution of variants encountered by the patients in a study. For example, the Gamma variant shows significantly different characteristics [Faria, Karita, Nonaka, Zavascki]. Different mechanisms of action may be more or less effective depending on variants, for example the viral entry process for the omicron variant has moved towards TMPRSS2-independent fusion, suggesting that TMPRSS2 inhibitors may be less effective [Peacock, Willett].
Regimen.
Effectiveness may depend strongly on the dosage and treatment regimen.
Other treatments.
The use of other treatments may significantly affect outcomes, including anything from supplements, other medications, or other kinds of treatment such as prone positioning.
Medication quality.
The quality of medications may vary significantly between manufacturers and production batches, which may significantly affect efficacy and safety. [Williams] analyze ivermectin from 11 different sources, showing highly variable antiparasitic efficacy across different manufacturers. [Xu] analyze a treatment from two different manufacturers, showing 9 different impurities, with significantly different concentrations for each manufacturer.
Meta analysis.
The distribution of studies will alter the outcome of a meta analysis. Consider a simplified example where everything is equal except for the treatment delay, and effectiveness decreases to zero or below with increasing delay. If there are many studies using very late treatment, the outcome may be negative, even though the treatment may be very effective when used earlier.
In general, by combining heterogeneous studies, as all meta analyses do, we run the risk of obscuring an effect by including studies where the treatment is less effective, not effective, or harmful.
When including studies where a treatment is less effective we expect the estimated effect size to be lower than that for the optimal case. We do not a priori expect that pooling all studies will create a positive result for an effective treatment. Looking at all studies is valuable for providing an overview of all research, important to avoid cherry-picking, and informative when a positive result is found despite combining less-optimal situations. However, the resulting estimate does not apply to specific cases such as early treatment in high-risk populations. While we present pooled results for all studies, we also present individual outcome and treatment time analyses, which are more relevant for specific use cases.
Discussion
Publication bias.
Publishing is often biased towards positive results, however evidence suggests that there may be a negative bias for inexpensive treatments for COVID-19. Both negative and positive results are very important for COVID-19, media in many countries prioritizes negative results for inexpensive treatments (inverting the typical incentive for scientists that value media recognition), and there are many reports of difficulty publishing positive results [Boulware, Meeus, Meneguesso]. For vitamin A, there is currently not enough data to evaluate publication bias with high confidence.
One method to evaluate bias is to compare prospective vs. retrospective studies. Prospective studies are more likely to be published regardless of the result, while retrospective studies are more likely to exhibit bias. For example, researchers may perform preliminary analysis with minimal effort and the results may influence their decision to continue. Retrospective studies also provide more opportunities for the specifics of data extraction and adjustments to influence results.
67% of retrospective studies report positive effects, compared to 100% of prospective studies, consistent with a bias toward publishing negative results. The median effect size for retrospective studies is 21% improvement, compared to 67% for prospective studies, suggesting a potential bias towards publishing results showing lower efficacy. Figure 18 shows a scatter plot of results for prospective and retrospective treatment studies.
Figure 18. Prospective vs. retrospective studies.
Funnel plot analysis.
Funnel plots have traditionally been used for analyzing publication bias. This is invalid for COVID-19 acute treatment trials — the underlying assumptions are invalid, which we can demonstrate with a simple example. Consider a set of hypothetical perfect trials with no bias. Figure 19 plot A shows a funnel plot for a simulation of 80 perfect trials, with random group sizes, and each patient's outcome randomly sampled (10% control event probability, and a 30% effect size for treatment). Analysis shows no asymmetry (p > 0.05). In plot B, we add a single typical variation in COVID-19 treatment trials — treatment delay. Consider that efficacy varies from 90% for treatment within 24 hours, reducing to 10% when treatment is delayed 3 days. In plot B, each trial's treatment delay is randomly selected. Analysis now shows highly significant asymmetry, p < 0.0001, with six variants of Egger's test all showing p < 0.05 [Egger, Harbord, Macaskill, Moreno, Peters, Rothstein, Rücker, Stanley]. Note that these tests fail even though treatment delay is uniformly distributed. In reality treatment delay is more complex — each trial has a different distribution of delays across patients, and the distribution across trials may be biased (e.g., late treatment trials may be more common). Similarly, many other variations in trials may produce asymmetry, including dose, administration, duration of treatment, differences in SOC, comorbidities, age, variants, and bias in design, implementation, analysis, and reporting.
Figure 19. Example funnel plot analysis for simulated perfect trials.
Conflicts of interest.
Pharmaceutical drug trials often have conflicts of interest whereby sponsors or trial staff have a financial interest in the outcome being positive. Vitamin A for COVID-19 lacks this because it is an inexpensive and widely available supplement. In contrast, most COVID-19 vitamin A trials have been run by physicians on the front lines with the primary goal of finding the best methods to save human lives and minimize the collateral damage caused by COVID-19. While pharmaceutical companies are careful to run trials under optimal conditions (for example, restricting patients to those most likely to benefit, only including patients that can be treated soon after onset when necessary, and ensuring accurate dosing), not all vitamin A trials represent the optimal conditions for efficacy.
Early/late vs. mild/moderate/severe.
Some analyses classify treatment based on early/late administration (as we do here), while others distinguish between mild/moderate/severe cases. We note that viral load does not indicate degree of symptoms — for example patients may have a high viral load while being asymptomatic. With regard to treatments that have antiviral properties, timing of treatment is critical — late administration may be less helpful regardless of severity.
Notes.
1 of 8 studies combine treatments. The results of vitamin A alone may differ. 1 of 2 RCTs use combined treatment.
Conclusion
Statistically significant improvements are seen for recovery, cases, and viral clearance. 4 studies from 3 independent teams in 3 different countries show statistically significant improvements in isolation (2 for the most serious outcome). Meta analysis using the most serious outcome reported shows 50% [-9‑77%] improvement, without reaching statistical significance. Results are better for Randomized Controlled Trials, similar after exclusions, and better for peer-reviewed studies. Results are consistent with early treatment being more effective than late treatment. Sufficiency studies, analyzing outcomes based on serum levels, show 73% [51‑85%] improvement for patients with higher vitamin A levels (3 studies).
Study Notes
[Al-Sumiadai (C)] Treatment and prophylaxis studies of vitamin A in Iraq.

The treatment study contained 100 patients, 50 treated with 200,000IU vitamin A for two days, showing lower progression to severe disease, and shorter duration of symptoms.

The prophylaxis study contained 209 contacts of COVID-19 patients, 97 treated with vitamin A, showing significantly lower cases with treatment, and shorter duration of symptoms.
0 0.5 1 1.5 2+ Progression 67% Improvement Relative Risk Recovery time 38% no CI c19early.com/va Al-Sumiadai et al. Vitamin A for COVID-19 EARLY Favors vitamin A Favors control
[Al-Sumiadai (B)] Treatment and prophylaxis studies of vitamin A in Iraq.

The treatment study contained 100 patients, 50 treated with 200,000IU vitamin A for two days, showing lower progression to severe disease, and shorter duration of symptoms.

The prophylaxis study contained 209 contacts of COVID-19 patients, 97 treated with vitamin A, showing significantly lower cases with treatment, and shorter duration of symptoms.
0 0.5 1 1.5 2+ Mortality 86% Improvement Relative Risk c19early.com/va Al-Sumiadai et al. Vitamin A for COVID-19 EARLY Favors vitamin A Favors control
[Al-Sumiadai] Retrospective 70 severe condition patients treated with vitamin A (200,000IU for two days), salbutamol, and budesonide, and 70 patients not treated with vitamin A, showing significantly lower mortality with the addition of vitamin A.
0 0.5 1 1.5 2+ Mortality 89% Improvement Relative Risk Hospitalization >7 days 41% SOFA score @day 7 45% c19early.com/va Beigmohammadi et al. Vitamin A for COVID-19 RCT ICU Favors vitamin A Favors control
[Beigmohammadi] Small RCT 60 ICU patients in Iran, 30 treated with vitamins A, B, C, D, and E, showing significant improvement in SOFA score and several inflammatory markers at day 7 with treatment.

5,000 IU vitamin A daily, 600,000 IU vitamin D once, 300 IU of vitamin E twice a day, 500 mg vitamin C four times a day, and one ampule daily of B vitamins [thiamine nitrate 3.1 mg, sodium riboflavin phosphate 4.9 mg (corresponding to vitamin B2 3.6 mg), nicotinamide 40 mg, pyridoxine hydrochloride 4.9 mg (corresponding to vitamin B6 4.0 mg), sodium pantothenate 16.5 mg (corresponding to pantothenic acid 15 mg), sodium ascorbate 113 mg (corresponding to vitamin C 100 mg), biotin 60 μg, folic acid 400 μg, and cyanocobalamin 5 μg]. IRCT20200319046819N [irct.ir].
0 0.5 1 1.5 2+ Mortality 86% Improvement Relative Risk ICU admission 67% Recovery time 35% Time to viral- 44% c19early.com/va Elkazzaz et al. NCT04353180 Vitamin A RCT LATE TREATMENT Favors vitamin A Favors control
[Elkazzaz] RCT with 20 13-cis-retinoic acid patients and 20 control patients, showing faster recovery and viral clearance with treatment. Aerosolized 13-cis-retinoic acid with increasing dose from 0.2 mg/kg/day to 4 mg/kg/day for 14 days, plus oral 13-cis-retinoic acid 20 mg/day. 13-cis retinoic acid is a synthetic vitamin A derivative, and is teratogenic. NCT04353180.
0 0.5 1 1.5 2+ Case 56% Improvement Relative Risk c19early.com/va Holt et al. NCT04330599 Vitamin A Prophylaxis Favors vitamin A Favors control
[Holt] Prospective survey-based study with 15,227 people in the UK, showing lower risk of COVID-19 cases with vitamin A, vitamin D, zinc, selenium, probiotics, and inhaled corticosteroids; and higher risk with metformin and vitamin C. Statistical significance was not reached for any of these. Except for vitamin D, the results for treatments we follow were only adjusted for age, sex, duration of participation, and test frequency. NCT04330599. COVIDENCE UK.
0 0.5 1 1.5 2+ Hospitalization 21% Improvement Relative Risk Severe case 21% c19early.com/va Nimer et al. Vitamin A for COVID-19 Prophylaxis Favors vitamin A Favors control
[Nimer] Retrospective survey based analysis of 2,148 COVID-19 recovered patients in Jordan, showing no significant differences in the risk of severity and hospitalization with vitamin A prophylaxis.
0 0.5 1 1.5 2+ Mortality -282% Improvement Relative Risk c19early.com/va Sarohan et al. Vitamin A for COVID-19 LATE TREATMENT Favors vitamin A Favors control
[Sarohan] Retrospective 27 severe COVID-19 patients and 23 non-COVID-19 patients, showing signifcantly lower vitamin A levels in COVID-19 patients (0.37mg/L vs. 0.52 mg/L, p<0.001). 10 of 27 COVID-19 patients received vitamin A, with higher mortality. Group details are not provided but authors note that 8 of 10 had comorbidities.
0 0.5 1 1.5 2+ Mortality 70% Improvement Relative Risk Progression 45% c19early.com/va Tepasse et al. Vitamin A for COVID-19 Sufficiency Favors vitamin A Favors control
[Tepasse] Prospective analysis of 40 hospitalized patients and 47 age-matched convalescent patients, showing significantly lower vitamin A levels in critical patients, and significantly lower vitamin A levels in hospitalized patients vs. controls. Low vitamin A levels were significantly associated with ARDS and mortality in hospitalized patients.
0 0.5 1 1.5 2+ Ventilation 71% Improvement Relative Risk ICU admission 61% c19early.com/va Tomasa-Irriguible et al. Vitamin A Sufficiency Favors vitamin A Favors control
[Tomasa-Irriguible] Retrospective 120 hospitalized patients in Spain showing vitamin A deficiency associated with higher ICU admission.
0 0.5 1 1.5 2+ Death/ICU 76% Improvement Relative Risk c19early.com/va Voelkle et al. Vitamin A for COVID-19 Sufficiency Favors vitamin A Favors control
[Voelkle] Prospective study of 57 consecutive hospitalized COVID-19 patients in Switzerland, showing higher risk of mortality/ICU admission with vitamin A, vitamin D, and zinc deficiency, with statistical significance only for vitamin A and zinc. Adjustments only considered age.
We performed ongoing searches of PubMed, medRxiv, ClinicalTrials.gov, The Cochrane Library, Google Scholar, Collabovid, Research Square, ScienceDirect, Oxford University Press, the reference lists of other studies and meta-analyses, and submissions to the site c19early.com. Search terms were vitamin A, filtered for papers containing the terms COVID-19 or SARS-CoV-2. Automated searches are performed every few hours with notification of new matches. All studies regarding the use of vitamin A for COVID-19 that report a comparison with a control group are included in the main analysis. Sensitivity analysis is performed, excluding studies with major issues, epidemiological studies, and studies with minimal available information. This is a living analysis and is updated regularly.
We extracted effect sizes and associated data from all studies. If studies report multiple kinds of effects then the most serious outcome is used in pooled analysis, while other outcomes are included in the outcome specific analyses. For example, if effects for mortality and cases are both reported, the effect for mortality is used, this may be different to the effect that a study focused on. If symptomatic results are reported at multiple times, we used the latest time, for example if mortality results are provided at 14 days and 28 days, the results at 28 days are used. Mortality alone is preferred over combined outcomes. Outcomes with zero events in both arms were not used (the next most serious outcome is used — no studies were excluded). For example, in low-risk populations with no mortality, a reduction in mortality with treatment is not possible, however a reduction in hospitalization, for example, is still valuable. Clinical outcome is considered more important than PCR testing status. When basically all patients recover in both treatment and control groups, preference for viral clearance and recovery is given to results mid-recovery where available (after most or all patients have recovered there is no room for an effective treatment to do better). If only individual symptom data is available, the most serious symptom has priority, for example difficulty breathing or low SpO2 is more important than cough. When results provide an odds ratio, we computed the relative risk when possible, or converted to a relative risk according to [Zhang]. Reported confidence intervals and p-values were used when available, using adjusted values when provided. If multiple types of adjustments are reported including propensity score matching (PSM), the PSM results are used. Adjusted primary outcome results have preference over unadjusted results for a more serious outcome when the adjustments significantly alter results. When needed, conversion between reported p-values and confidence intervals followed [Altman, Altman (B)], and Fisher's exact test was used to calculate p-values for event data. If continuity correction for zero values is required, we use the reciprocal of the opposite arm with the sum of the correction factors equal to 1 [Sweeting]. Results are expressed with RR < 1.0 favoring treatment, and using the risk of a negative outcome when applicable (for example, the risk of death rather than the risk of survival). If studies only report relative continuous values such as relative times, the ratio of the time for the treatment group versus the time for the control group is used. Calculations are done in Python (3.9.13) with scipy (1.8.0), pythonmeta (1.26), numpy (1.22.2), statsmodels (0.14.0), and plotly (5.6.0).
Forest plots are computed using PythonMeta [Deng] with the DerSimonian and Laird random effects model (the fixed effect assumption is not plausible in this case) and inverse variance weighting. Mixed-effects meta-regression results are computed with R (4.1.2) using the metafor (3.0-2) and rms (6.2-0) packages, and using the most serious sufficiently powered outcome.
We received no funding, this research is done in our spare time. We have no affiliations with any pharmaceutical companies or political parties.
We have classified studies as early treatment if most patients are not already at a severe stage at the time of treatment (for example based on oxygen status or lung involvement), and treatment started within 5 days of the onset of symptoms. If studies contain a mix of early treatment and late treatment patients, we consider the treatment time of patients contributing most to the events (for example, consider a study where most patients are treated early but late treatment patients are included, and all mortality events were observed with late treatment patients). We note that a shorter time may be preferable. Antivirals are typically only considered effective when used within a shorter timeframe, for example 0-36 or 0-48 hours for oseltamivir, with longer delays not being effective [McLean, Treanor].
A summary of study results is below. Please submit updates and corrections at the bottom of this page.
A summary of study results is below. Please submit updates and corrections at https://c19early.com/vameta.html.
Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. For pooled analyses, the first (most serious) outcome is used, which may differ from the effect a paper focuses on. Other outcomes are used in outcome specific analyses.
[Al-Sumiadai (B)], 1/31/2021, prospective, Iraq, preprint, 3 authors. risk of progression, 66.7% lower, RR 0.33, p = 0.27, treatment 2 of 50 (4.0%), control 6 of 50 (12.0%), NNT 13, progression to severe disease.
[Al-Sumiadai], 12/31/2020, retrospective, Iraq, peer-reviewed, 3 authors, excluded in exclusion analyses: minimal details of groups provided. risk of death, 85.7% lower, RR 0.14, p = 0.002, treatment 2 of 70 (2.9%), control 14 of 70 (20.0%), NNT 5.8.
Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. For pooled analyses, the first (most serious) outcome is used, which may differ from the effect a paper focuses on. Other outcomes are used in outcome specific analyses.
[Beigmohammadi], 11/14/2021, Single Blind Randomized Controlled Trial, Iran, peer-reviewed, 6 authors, this trial uses multiple treatments in the treatment arm (combined with vitamins B, C, D, E) - results of individual treatments may vary. risk of death, 88.9% lower, RR 0.11, p = 0.11, treatment 0 of 30 (0.0%), control 4 of 30 (13.3%), NNT 7.5, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of hospitalization >7 days, 41.0% lower, RR 0.59, p = 0.25, treatment 4 of 30 (13.3%), control 16 of 30 (53.3%), NNT 2.5, adjusted per study, odds ratio converted to relative risk.
relative SOFA score @day 7, 45.5% better, RR 0.55, p < 0.001, treatment 30, control 30.
[Elkazzaz], 3/8/2022, Randomized Controlled Trial, Egypt, preprint, 4 authors, study period June 2020 - August 2020, trial NCT04353180 (history). risk of death, 85.7% lower, RR 0.14, p = 0.23, treatment 0 of 20 (0.0%), control 3 of 20 (15.0%), NNT 6.7, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
risk of ICU admission, 66.7% lower, RR 0.33, p = 0.24, treatment 2 of 20 (10.0%), control 6 of 20 (30.0%), NNT 5.0.
recovery time, 35.4% lower, relative time 0.65, p < 0.001, treatment mean 16.3 (±4.5) n=20, control mean 25.23 (±4.72) n=20.
time to viral-, 44.0% lower, relative time 0.56, p < 0.001, treatment mean 13.36 (±1.49) n=20, control mean 23.85 (±4.0) n=20.
[Sarohan], 2/1/2021, retrospective, Turkey, preprint, 4 authors, excluded in exclusion analyses: unadjusted results with no group details. risk of death, 282.5% higher, RR 3.83, p = 0.001, treatment 9 of 10 (90.0%), control 4 of 17 (23.5%).
Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. For pooled analyses, the first (most serious) outcome is used, which may differ from the effect a paper focuses on. Other outcomes are used in outcome specific analyses.
[Al-Sumiadai (C)], 1/31/2021, prospective, Iraq, preprint, 3 authors. risk of case, 64.5% lower, RR 0.36, p < 0.001, treatment 20 of 97 (20.6%), control 65 of 112 (58.0%), NNT 2.7.
[Holt], 3/30/2021, prospective, United Kingdom, peer-reviewed, 34 authors, study period 1 May, 2020 - 5 February, 2021, trial NCT04330599 (history) (COVIDENCE UK), excluded in exclusion analyses: significant unadjusted confounding possible. risk of case, 56.3% lower, RR 0.44, p = 0.41, treatment 1 of 91 (1.1%), control 445 of 15,136 (2.9%), NNT 54, adjusted per study, odds ratio converted to relative risk, minimally adjusted, group sizes approximated.
[Nimer], 2/28/2022, retrospective, Jordan, peer-reviewed, survey, 4 authors, study period March 2021 - July 2021. risk of hospitalization, 21.2% lower, RR 0.79, p = 0.40, treatment 15 of 144 (10.4%), control 204 of 2,004 (10.2%), adjusted per study, odds ratio converted to relative risk, multivariable.
risk of severe case, 20.8% lower, RR 0.79, p = 0.36, treatment 17 of 144 (11.8%), control 243 of 2,004 (12.1%), adjusted per study, odds ratio converted to relative risk, multivariable.
Supplementary Data
References