Questioning vitamin D status of elderly fallers and nonfallers: a meta‐analysis to address a ‘forgotten step’
Bibliographic record
Abstract
BACKGROUND: Previous meta-analyses to determine the efficacy of vitamin D supplementation to prevent falls in the elderly have shown mixed results. Inconsistencies might depend on the dose of supplements, suggesting that serum 25-hydroxyvitamin D (25OHD) concentration could influence the risk of falling. Our objective was to systematically review and quantitatively analyse the relationship between serum 25OHD concentration and the occurrence of falls. METHODS: A Medline search was conducted in December 2013, with no date limit, using the Medical Subject Heading terms 'Vitamin D' OR 'Ergocalciferols' OR 'Vitamin D deficiency' combined with 'Accidental Falls' OR 'Gait disorders, neurologic' OR 'Gait apraxia' OR 'Gait' OR 'Recurrent Falls' OR 'Falling'. Fixed and random-effects meta-analyses were performed to determine the following: (i) the effect size of the difference in 25OHD concentration between fallers and nonfallers and (ii) the risk of falling according to serum 25OHD concentration. RESULTS: Of the 659 retrieved studies, 18 observational studies - including ten cross-sectional and eight cohort studies - met the selection criteria. All were of good quality. The number of participants ranged from 80 to 2957 (44-100% women); 11.0% to 69.3% were fallers. Serum 25OHD concentrations were 0.33 × SD lower in fallers compared to nonfallers [pooled effect size 0.33; 95% confidence interval (CI) 0.18-0.47]. The risk of falls was inversely associated with serum 25OHD concentration [summary odds ratio (OR) 0.97; 95% CI 0.96-0.99]. The association between falls and hypovitaminosis D varied according to the definition used; the summary OR for falls was 1.23 (95% CI 0.94-1.60) for 25OHD <10 ng mL(-1) , 1.44 (95% CI 1.17-1.76) for 25OHD <20 ng mL(-1) and 0.95 (95% CI 0.81-1.11) for 25OHD <30 ng mL(-1) . CONCLUSIONS: Fallers have lower 25OHD concentrations, notably more often <20 ng mL(-1) , than nonfallers. These findings help to determine the profile of target populations that would most benefit from vitamin D supplements to prevent falls.
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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 | 0.040 | 0.076 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.055 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".