Isotretinoin and the Risk of Depression in Patients With Acne Vulgaris
Bibliographic record
Abstract
OBJECTIVE: To determine whether isotretinoin increases the risk of depression in patients with acne vulgaris. METHOD: A case-crossover study was performed among subjects who received > or = 1 isotretinoin prescription from 1984 through 2003. Data were obtained from the Régie de l'Assurance Maladie du Québec (RAMQ) and Quebec's hospital discharge (Med-Echo) administrative databases. Cases were defined as those with a first diagnosis or hospitalization for depression (ICD-9 codes: 296.2, 298.0, 300.4, 309.0, 309.1, and 311) during the study period (1984-2003) and those who filled a prescription for an antidepressant in the 30 days following their diagnosis or hospitalization. The index date was the calendar date of the diagnosis or hospitalization for depression. Cases were covered by the RAMQ drug plan and had > or = 1 acne diagnosis in the 12 months prior to the index date. Those who received an antidepressant in 12 months prior to the index date were excluded. Exposure to isotretinoin in a 5-month risk period immediately prior to the index date was compared to a 5-month control period. Relative risks along with 95% CIs were estimated using conditional logistic regression. RESULTS: Of the 30,496 subjects in the initial cohort, 126 (0.4%) cases met inclusion criteria. The crude relative risk for those exposed to isotretinoin was 2.00 (95% CI = 1.03 to 3.89). After adjusting for potential time-dependent confounders, the relative risk for those exposed to isotretinoin was 2.68 (95% CI = 1.10 to 6.48). CONCLUSION: This is the first controlled study to find a statistically significant association between isotretinoin and depression. Because depression could have serious consequences, close monitoring of isotretinoin users is indicated.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".