Prognostic and Therapeutic Role of Vitamin D in COVID-19: Systematic Review and Meta-analysis
Bibliographic record
Abstract
PURPOSE: Vitamin D deficiency/insufficiency may increase the susceptibility to coronavirus disease 2019 (COVID-19). We aimed to determine the association between vitamin D deficiency/insufficiency and susceptibility to COVID-19, its severity, mortality, and role of vitamin D in its treatment. METHODS: We searched CINAHL, Cochrane library, EMBASE, PubMED, Scopus, and Web of Science up to May 30, 2021, for observational studies on association between vitamin D deficiency/insufficiency and susceptibility to COVID-19, severe disease, and death among adults, and, randomized controlled trials (RCTs) comparing vitamin D treatment against standard care or placebo, in improving severity or mortality among adults with COVID-19. Risk of bias was assessed using Newcastle-Ottawa scale for observational studies and AUB-KQ1 Cochrane tool for RCTs. Study-level data were analyzed using RevMan 5.3 and R (v4.1.0). Heterogeneity was determined by I2 and sources were explored through prespecified sensitivity analyses, subgroup analyses, and meta-regressions. RESULTS: Of 1877 search results, 76 studies satisfying eligibility criteria were included. Seventy-two observational studies were included in the meta-analysis (n = 1 976 099). Vitamin D deficiency/insufficiency increased the odds of developing COVID-19 (odds ratio [OR] 1.46; 95% CI, 1.28-1.65; P < 0.0001; I2 = 92%), severe disease (OR 1.90; 95% CI, 1.52-2.38; P < 0.0001; I2 = 81%), and death (OR 2.07; 95% CI, 1.28-3.35; P = 0.003; I2 = 73%). The 25-hydroxy vitamin D concentrations were lower in individuals with COVID-19 compared with controls (mean difference [MD] -3.85 ng/mL; 95% CI, -5.44 to -2.26; P ≤ 0.0001), in patients with severe COVID-19 compared with controls with nonsevere COVID-19 (MD -4.84 ng/mL; 95% CI, -7.32 to -2.35; P = 0.0001) and in nonsurvivors compared with survivors (MD -4.80 ng/mL; 95% CI, -7.89 to -1.71; P = 0.002). The association between vitamin D deficiency/insufficiency and death was insignificant when studies with high risk of bias or studies reporting unadjusted effect estimates were excluded. Risk of bias and heterogeneity were high across all analyses. Discrepancies in timing of vitamin D testing, definitions of severe COVID-19, and vitamin D deficiency/insufficiency partly explained the heterogeneity. Four RCTs were widely heterogeneous precluding meta-analysis. CONCLUSION: Multiple observational studies involving nearly 2 million adults suggest vitamin D deficiency/insufficiency increases susceptibility to COVID-19 and severe COVID-19, although with a high risk of bias and heterogeneity. Association with mortality was less robust. Heterogeneity in RCTs precluded their meta-analysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.040 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".