Assessment of Vitamin D Supplementation in People with Intellectual Disability
Bibliographic record
Abstract
Vitamin D levels are often lower than recommended among certain groups, and these so-called at risk populations include institutionalised people with intellectual disabilities. The administration of vitamin D supplements does normalize these levels, but they tend to fall again when treatment is discontinued. The objectives of this study were, first, to assess whether the administration of 20,000 IU of cholecalciferol monthly and 60,000 IU quarterly over a year provide similar satisfactory results, and second, to explore whether the results are associated with following variables: sex, antiepileptic medication, being a wheelchair user or able to walk, and being a resident or day care user. The study population was composed of 204 individuals of both sexes cared for in four centres of the same institution. There were no differences between the levels reached with monthly and quarterly administration. The overall results show that, at the end of the test period, total 25(OH)vitamin D levels were <30 nmol/L in 3.5% of participants, 30 to < 50 nmol/L in 34%, 50 to <75 nmol/L in 41% and ≥75 nmol/L in 21.5%. There were significant differences between centres. We did not observe any harmful adverse effects attributable to the treatment. To conclude, we propose the continuous systematic administration of 60,000 IU of cholecalciferol every three months in this at-risk population.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".