Antipsychotic Drugs and Hyperglycemia in Older Patients With Diabetes
Bibliographic record
Abstract
BACKGROUND: Evidence suggests that there is an association between antipsychotic drugs and new-onset diabetes, but little is known about the risk of hyperglycemia among persons with preexisting diabetes. METHODS: Using a nested case-control design and population-based health databases in Ontario, Canada, persons aged 66 years or older with diabetes who started treatment with an antipsychotic drug from April 1, 2002, to March 31, 2006, were followed up from treatment start until March 31, 2007. The cohort was subdivided into 3 groups: insulin-treated, oral hypoglycemic agent only-treated, and no diabetes treatment. We defined cases as patients hospitalized (emergency department visit or hospital admissions) for hyperglycemia. Each case was matched with up to 10 controls. We compared the likelihood of hyperglycemia among current users of atypical and typical antipsychotic agents with that among remote antipsychotic users (discontinued >180 days), based on prescriptions closest to event date. RESULTS: Of 13 817 patients studied, 1515 (11.0%) were hospitalized for hyperglycemia. Current antipsychotic treatment was associated with a higher risk of hyperglycemia compared with remote antipsychotic use in all diabetes treatment groups (overall adjusted rate ratio, 1.50; 95% confidence interval, 1.29-1.74). The risk was increased among patients who were treated with atypical and typical antipsychotic agents and was extremely high among patients who were just starting treatment (only 1 prescription before event). CONCLUSIONS: Among older patients with diabetes, the initiation of treatment with antipsychotic drugs was associated with a significantly increased risk of hospitalization for hyperglycemia (P < .001). The risk was particularly high during the initial course of treatment and was increased with the use of all antipsychotic agents.
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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 | 0.000 | 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 | 0.000 |
| 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".