Initial Cholinesterase Inhibitor Therapy Dose and Serious Events in Older Women and Men
Bibliographic record
Abstract
OBJECTIVES: To examine dose-related prescribing and short-term serious events associated with initiation of cholinesterase inhibitor (ChEI) therapy. DESIGN: Retrospective, population-based cohort study. SETTING: Ontario, Canada. PARTICIPANTS: Women (n=47,829) and men (n=32,503) aged 66 and older who initiated a ChEI between April 1, 2010, and June 30, 2016. MEASUREMENTS: All-cause serious events (emergency department (ED) visits, inpatient hospitalizations, death) within 30 days of ChEI initiation. Multivariable Cox proportional hazards models were used to estimate adjusted rates of serious events. RESULTS: Overall, 4.8% of older adults were dispensed a lower-than-recommended ChEI starting dose, 87.9% a recommended dose, and 7.3% a higher-than-recommended starting dose. Eight thousand six hundred seventy-one (10.8%) individuals experienced a serious event within 30 days of initiating therapy, primarily ED visits (8,540, 10.6%). Relative to those initiated on a recommended starting dose, those initiated on a higher dose had a significantly increased rate of serious events (women adjusted hazard ratio (aHR) 1.50, 95% confidence interval (CI) =1.38-1.63; men aHR 1.31, 95% CI=1.19-1.45). Similar patterns were found for ED visits and inpatient hospitalizations but not death. The relative effect of higher-than-recommended starting dose dispensed vs. recommended starting dose dispensed was greater in women than it was in men: the number needed to harm was 22 (95% confidence interval (CI)=18-29) for women and 36 (95% CI= 26-61) for men. CONCLUSION: Serious events immediately after initiation of ChEIs were associated with starting ChEI dose. This association was stronger in women.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".