Risperidone and Risk of Gynecomastia in Young Men
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to quantify the risk of gynecomastia with risperidone in adolescent and young adult males. METHODS: We created a cohort of males 15-25 years of age from the IMS LifeLink database, and conducted a case-control study within the cohort by identifying all new cases of gynecomastia. For each case, 10 controls were selected and matched to the cases by age, follow-up, and calendar times (cases and controls had the same follow up time and cohort entry date). Rate ratios (RR) for current use of risperidone were computed adjusting for potential confounding variables. RESULTS: First diagnosis of gynecomastia was made based on International Classification of Diseases, 9th revision (ICD-9) for gynecomastia. There were 401,924 males ages 15-25 in the primary cohort. There were 1556 cases of gynecomastia and 15,560 corresponding controls. Current users of risperidone had approximately four times the risk of developing gynecomastia than non-users (RR=3.91, 95% CI=2.01-7.62). When the analysis was stratified to children and adolescents (≤18 years of age) taking risperidone, the risk of gynecomastia was five times higher than for non-users (RR=5.44, 95% CI=1.50-19.74). CONCLUSIONS: Risperidone is associated with an increase with the risk of gynecomastia in adolescent and young adult males.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".