Comparative risk of new-onset diabetes following commencement of antipsychotics in New Zealand: a population-based clustered multiple baseline time series design
Bibliographic record
Abstract
OBJECTIVE: Newer antipsychotics are increasingly prescribed off-label for non-psychotic ailments both in primary and secondary care settings, despite the purported risk of weight gain and development of type 2 diabetes mellitus. This study aims to determine any relationship between the development of clinically significant new-onset type 2 diabetes mellitus and novel antipsychotic use in New Zealand using hypnotic drugs as control. DESIGN: A population-based clustered multiple baseline time series design. SETTING: Routinely collected data from a complete national pharmaceutical database in New Zealand between 2005 and 2011. PARTICIPANTS: Patients aged 40-60 years in the year 2006 who were ever dispensed antipsychotics (exposure groups-first-generation antipsychotics, second-generation antipsychotics and antipsychotics with low, medium and high risk for weight gain) or hypnotics (control group) between 2006 and 2011. MAIN OUTCOME MEASURE: First ever metformin dispensed to patients in each study group between 2006 and 2011 as proxy for development of clinically significant type 2 diabetes mellitus, no longer amendable by lifestyle modifications. RESULTS: Patients dispensed a second-generation antipsychotic had 1.49 times increased risk (95% CI 1.10 to 2.03, p=0.011) of subsequently commencing metformin. Patients dispensed an antipsychotic with high risk of weight gain also had a 2.41 times increased risk of commencing on metformin (95% CI 1.42 to 4.09, p=0.001). CONCLUSIONS: Patients dispensed a second-generation antipsychotic and antipsychotics with high risk of weight gain appear to be at increased risk of being secondarily dispensed metformin. Caution should be taken with novel antipsychotic use for patients with increased baseline risk of type 2 diabetes mellitus.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".