The Effect of Paternal Age on Relapse in First-Episode Schizophrenia
Bibliographic record
Abstract
OBJECTIVE: Multiple etiological and prognostic factors have been implied in schizophrenia and its outcome. Advanced paternal age has been reported as a risk factor in schizophrenia. Whether this may affect schizophrenia outcome was not previously studied. We hypothesized that advanced paternal age may have a negative effect on the outcome of relapse in schizophrenia. METHOD: We interviewed 191 patients with first-episode schizophrenia and their relatives for parental ages, sociodemographic factors at birth, birth rank, family history of psychotic disorders, and obstetric complications. The outcome measure was the presence of relapse at the end of the first year of treatment. RESULTS: In the 1-year follow-up period, 42 (22%) patients experienced 1 or more relapses. The mean paternal age was 34.62 years (SD 7.69). Patients who relapsed had significantly higher paternal age, poorer medication adherence, were female, and were hospitalized at onset, compared with patients who did not relapse. A multivariate regression analysis showed that advanced paternal age (OR 1.05, 95% CI 1.01 to 1.10), medication nonadherence (OR 2.37, 95% CI 1.12 to 4.99), and female sex (OR 2.44, 95% CI 1.14 to 5.24) independently contributed to a higher risk of relapse. Analysis between different paternal age groups found a significantly higher relapse rate with paternal age over 40. CONCLUSIONS: Advanced paternal age is found to be modestly but significantly related to more relapses, and such an effect is the strongest at a cut-off of paternal age of 40 years or older. The effect is less likely to be mediated through less effective parental supervision or nonadherence to medication. Other possible biological mechanisms need further explorations.
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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 | 0.012 |
| 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) | 0.002 | 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".