Antipsychotic Use and Risk of Low-Energy Fractures in People With Schizophrenia: A Nationwide Nested Case-Control Study in Finland
Bibliographic record
Abstract
BACKGROUND: Low-energy fractures (LEF) are more frequent in people with schizophrenia than the general population, and the role of prolactin-increasing antipsychotics is unknown. STUDY DESIGN: We conducted a nested case-control study using Finnish nationwide registers (inpatient, specialized outpatient care, prescription drug purchases). We matched each person with schizophrenia aged 16-85 years and incident LEF (cases) with 5 age/sex/illness duration-matched controls with schizophrenia, but no LEF. We investigated the association between cumulative exposure (duration, and Defined Daily Doses, DDDs) to prolactin-increasing/sparing antipsychotics and LEF. Adjusted conditional logistic regression analyses were performed. Sensitivity analyses were conducted. STUDY RESULTS: Out of 61 889 persons with schizophrenia between 1972 and 2014, we included 4960 cases. Compared with 24 451 controls, 4 years or more of exposure to prolactin-increasing antipsychotics was associated with increased risk of LEF (adjusted odds ratio (aOR) from aOR = 1.22, 95%CI = 1.09-1.37 to aOR = 1.38, 95%CI = 1.22-1.57, for 4-< 7 />13 years of exposure, respectively), without a significant association for prolactin-sparing antipsychotics. All cumulative doses higher than 1000 DDDs of prolactin-increasing antipsychotics were associated with LEF (from aOR = 1.21, 95%CI = 1.11-1.33, 1000-<3000 DDDs, to aOR = 1.64, 95%CI = 1.44-1.88, >9000 DDDs). Only higher doses of prolactin-sparing antipsychotics reached statistical significance (aOR = 1.24, 95%CI = 1.01-1.52, 6000-<9000 DDDs, aOR = 1.45, 95%CI = 1.13-1.85, >9000 DDDs). Sensitivity analyses confirmed the main analyses for prolactin-increasing antipsychotics. For prolactin-sparing antipsychotics, significant associations were limited to extreme exposure, major LEF, older age group, and males. CONCLUSIONS: Long-term exposure to prolactin-increasing antipsychotics at any dose, and high cumulative doses of prolactin-sparing antipsychotics is associated with significantly increased odds of LEF. Monitoring and addressing hyperprolactinemia is paramount in people with schizophrenia receiving prolactin-increasing antipsychotics.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".