Vitamin D3 supplementation as an adjunct in the management of childhood infectious diarrhea: a systematic review
Bibliographic record
Abstract
Abstract Background Some studies have reported the possible role of vitamin D 3 in ameliorating disease outcomes in childhood infectious diarrhea. However, findings about its effectiveness and the association of serum vitamin D levels with diarrhea risk appear inconsistent. We aimed to determine the efficacy of oral vitamin D 3 as an adjunct in managing childhood infectious diarrhea and the relationship between vitamin D status and the disease. Methods We searched the PubMed and Google Scholar electronic databases for relevant articles without limiting their year of publication. We selected primary studies that met the review’s inclusion criteria, screened their titles and abstracts, and removed duplicates. We extracted data items from selected studies using a structured data-extraction form. We conducted a quality assessment of randomized controlled trials (RCTs) and non-randomized studies with the Cochrane collaboration tool and the Newcastle Ottawa Scale, respectively. We assessed the strength of the relationship between serum vitamin D levels and diarrhea using the correlation model. We estimated the I 2 and tau 2 values to assess between-study heterogeneity. Results Nine full-text articles were selected, consisting of one RCT, three cross-sectional studies, two cohort studies, two longitudinal/prospective studies, and one case-control study. A total of 5,545 participants were evaluated in the nine studies. Six non-randomized studies provided weak evidence of the relationship between vitamin D levels and diarrhea risk as there was no correlation between the two variables. The only RCT failed to demonstrate any beneficial role of vitamin D 3 in reducing the risk of recurrent diarrhea. The calculated I 2 and tau 2 values of 86.5% and 0.03, respectively suggested a high between-study heterogeneity which precluded a meta-analysis of study results. Conclusion Oral vitamin D 3 may not be an effective adjunct in managing childhood infectious diarrhea. Additionally, the relationship between vitamin D status and infectious diarrhea appears weak. We recommend more adequately-powered RCTs to determine the effectiveness of vitamin D 3 as an adjunct therapy in infectious diarrhea.
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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 | 0.008 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".