Association Between Inflammatory Bowel Disease and Vitamin D Deficiency
Bibliographic record
Abstract
BACKGROUND: Vitamin D plays a role in several immune-mediated diseases, but its association with inflammatory bowel disease (IBD) is unclear. We conducted a systematic review and meta-analysis to assess the association between IBD and vitamin D deficiency. METHODS: We searched electronic databases from inception to December 2014 for observational studies reporting the presence of vitamin D deficiency (defined as serum 25-hydroxycholecalciferol [25(OH)D] level of ≤20 ng/mL) in IBD patients and having a control group without IBD. Odds ratios (ORs) were combined using a random-effects model. Meta-regression was performed using latitude as a moderator. Study quality was assessed using the Newcastle-Ottawa scale. RESULTS: Out of 816 citations, 14 eligible studies were identified, comprising 1891 participants (938 IBD cases and 953 controls). Meta-analysis showed that patients with IBD had 64% higher odds of vitamin D deficiency when compared with controls (OR = 1.64; 95% confidence interval, 1.30-2.08; I = 7%; P < 0.0001). Patients with ulcerative colitis had more than double the odds of vitamin D deficiency when compared with normal controls (OR = 2.28; 95% confidence interval, 1.18-4.41; I = 41%; P = 0.01). Latitude did not influence the association between IBD and vitamin D deficiency (P = 0.34). Generalizability of our results might be limited as we summarized unadjusted ORs, because of nonavailability of adjusted ORs in individual studies. CONCLUSIONS: IBD is significantly associated with having higher odds of vitamin D deficiency. Well-designed randomized controlled trials and longitudinal studies are needed to further explain the role of vitamin D in IBD pathogenesis and its therapy.
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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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.013 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".