Hypovitaminosis D in Delirium: a Retrospective Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND: As vitamin D may have a neuroprotective effect, the authors studied the association of biomarkers of vitamin D status and delirium to see if low vitamin D status was common in delirium cases. METHODS: Biochemical measures of vitamin D (25-hydroxyvitamin D [25-OHD]) and calcium metabolism were used in this retrospective cross-sectional analysis of adult in-patients with delirium, admitted at three Canadian academic hospitals from January 2011 to July 2012. Primary outcome was to determine estimates of the prevalence of hypovitaminosis D in this group in whom vitamin D was checked. RESULTS: Seventy-one (5.8%) out of 1,232 delirium inpatients had their vitamin D measured. Thirty-nine (55%) showed vitamin D insufficiency (25-OHD of 25-75 nmol/L) and 8 (11%) showed vitamin D deficiency (25-OHD < 25 nmol/L). Mean serum 25-OHD levels were lower in males (57.1±7.7 nmol/L) than in females (78.2±6.1 nmol/L), p = .01, even when controlled for age and season. Men were younger than the women (74.4±2.3 vs. 82.4±1.7, p = .005). Mean age was 78.7±1.5 years, and 33 (47%) were male. CONCLUSIONS: Although vitamin D is rarely checked during delirium workup and/or management, high rates of hypovitaminosis D were found to be common in the delirium in-patients in whom it was checked. Larger studies would be needed to estimate the prevalence of hypovitaminosis D in delirium and whether hypovitaminosis D plays a role in the pathogenesis of delirium.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".