A retrospective study of cholinesterase inhibitors for Alzheimer's disease: cerebrovascular disease as a predictor of patient outcomes
Bibliographic record
Abstract
BACKGROUND: Dementia may be caused by Alzheimer's disease (AD), cerebrovascular disease (CVD), or a combination of both. When CVD is associated with dementia, survival is thought to be reduced. It is unclear whether treatment with cholinesterase inhibitors (ChEIs), which has been found to slow disease progression in AD patients, has similar benefits in vascular forms of dementia. OBJECTIVES: The present study was designed to determine whether co-existing CVD is associated with survival or time to nursing home placement (NHP) among AD patients treated with ChEIs. Findings of poorer outcomes in patients with versus without CVD might argue against the use of ChEIs for AD patients in whom CVD co-exists. METHODS: A retrospective cohort study was undertaken using the Régie de l'Assurance Maladie du Québec (RAMQ) databases to examine the time to NHP or death for AD patients aged 66+, with or without CVD, treated with ChEIs between July 1, 2000, and June 30, 2003. Because ChEIs are approved only for AD in Canada, a ChEI prescription was used as a surrogate for an AD diagnosis. Separate analyses were performed for patients with persistent ChEI use and those who discontinued ChEI therapy. RESULTS: A total of 4428 patients met inclusion criteria for AD with CVD; 13 512 were classified as having AD alone. For the composite endpoint of NHP or death, 1000-day survival rates were lower among AD patients with versus without CVD (p < 0.01), but absolute differences were very small (84 vs. 86% with continuous ChEI use; 77 vs. 78% with discontinuous ChEI therapy). Of the secondary endpoints, time to death was shorter for patients with versus without CVD, but time to NHP did not differ between groups. LIMITATIONS: Results may have been affected by selection (misclassification) bias and between-group differences in smoking, body mass index, and duration of ChEI therapy. CONCLUSIONS: Associations between co-existing CVD and time to NHP or death appeared to be of little clinical relevance among AD patients treated with ChEIs. The lack of difference between AD patients with and without CVD suggests that CVD should not be used as a reason to deny AD patients access to ChEI treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".