A Randomized Controlled Trial of High-Dose Vitamin D2 Followed by Intranasal Insulin in Alzheimer's Disease
Bibliographic record
Abstract
Poor vitamin D nutrition is linked with dementia, but vitamin D has not been tested in a randomized controlled trial (RCT) in Alzheimer's disease (AD). Nasal insulin acutely improves cognition and vitamin D upregulates insulin receptor expression and enhances insulin action. In an RCT we examined the effect of high-dose vitamin D followed by nasal insulin on memory and disability in mild-moderate AD. 63 community-dwelling individuals aged > 60 were recruited; 32 with mild-moderate disease (Folstein Mini-Mental State Examination [MMSE] score 12-24) met entry criteria and were randomized. All took low-dose vitamin D (1000 IU/day) throughout. After run-in (8 weeks), they were randomized to additional high-dose D/placebo for 8 weeks, followed immediately by randomization to nasal insulin (60 IU qid)/placebo for 48 h. Primary outcome measures were Alzheimer's disease assessment scale-cognitive subscale (ADAS-cog) and Disability Assessment in Dementia (after high-dose D) and ADAS-cog and Wechsler Memory Scale-Revised Logical memory (WMS-R LM) for immediate and delayed recall (after nasal insulin). Baseline median (interquartile range, IR) age, MMSE, and ADAS-cog were 77.5 (69-80), 19.5 (17-22), and 25.5 (20-31), respectively. Median 25OHD increased from 49 to 60 nM (p < 0.01) after run-in and was 187 nM after high-dose vitamin D and 72 nM after placebo (p < 0.001). Neither cognition nor disability changed significantly after high-dose D. ADAS-cog improved by a median (IR) of 9 (1-11) with nasal insulin after placebo high-dose vitamin D (p = 0.02), but may represent regression to the mean as WLS-R LM did not change. We conclude that high-dose vitamin D provides no benefit for cognition or disability over low-dose vitamin D in mild-moderate AD.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".