Exploring the Association Between Atypical Neuroleptic Agents and Diabetes Mellitus in Older Adults
Bibliographic record
Abstract
STUDY OBJECTIVE: To explore the suggested association between atypical neuroleptic use and the development of diabetes mellitus, with a focus on older adults. DESIGN: Retrospective cohort study. SUBJECTS: Eleven thousand one hundred four older (> 65 yrs) residents of long-term care institutions in Ontario, Canada, who received either atypical neuroleptic agents, typical neuroleptic agents, benzodiazepines, or corticosteroids. MEASUREMENTS AND MAIN RESULTS: Each subject was followed for the development of a diabetic event, defined as newly prescribed antidiabetic drug therapy. Our Cox regression model was adjusted for age, sex, socioeconomic status, comorbidity, and concomitant use of beta-blockers, thiazide diuretics, and antiepileptic agents. The adjusted hazard ratio for the development of diabetes in patients receiving atypical neuroleptics compared with those receiving benzodiazepines (control group) was 0.89 (95% confidence interval [CI] 0.66-1.21). The adjusted hazard ratio for typical neuroleptic users compared with the benzodiazepine group was 1.27 (95% CI 0.91-1.77). As expected, patients receiving corticosteroid therapy were almost twice as likely to develop diabetes as those receiving benzodiazepines (adjusted hazard ratio 2.2, 95% CI 1.41-3.12). For patients receiving atypical neuroleptic agents, no statistically significant difference in the percentage of diabetic events was found among individual agents (2.1% olanzapine, 1% quetiapine, 2.1% risperidone). CONCLUSION: Drug therapy with atypical neuroleptic agents in older adults did not increase their risk of developing diabetes mellitus.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".