Depressive symptoms in first‐episode psychosis: a 10‐year follow‐up study
Bibliographic record
Abstract
AIMS: The present study examined if any patient characteristics at baseline predicted depressive symptoms at 10 years and whether patients prone to depressive symptoms in the first year of treatment had a different prognosis in the following years. METHOD: A total of 299 first-episode psychosis (FEP) patients with schizophrenia spectrum disorders were assessed for depressive symptoms with PANSS depression item (g6) at baseline, and 1, 2, 5 and 10 years of follow up. At 10 years, depressive symptoms were also assessed with Calgary Depression Scale for Schizophrenia (CDSS). A PANSS g6 ≥ 4 and CDSS score ≥ 6 were used as a cut-off score for depression. RESULTS: A total of 122 (41%) patients were scored as depressed at baseline, 75 (28%) at 1 year, 50 (20%) at 2 years, 33 (16%) at 5 years, and 35 (19%) at 10 years of follow up. Poor childhood social functioning and alcohol use at baseline predicted depression at 10 years of follow up. Thirty-eight patients were depressed at both baseline and 1 year follow up. This group had poorer symptomatic and functional outcome in the follow-up period compared to a group of patients with no depression in the first year of treatment. CONCLUSION: Depressive symptoms are frequent among FEP patients at baseline but decrease after treatment because their general symptoms have been initiated. Patients with poor social functioning in childhood and alcohol use at baseline are more prone to have depressive symptoms at 10 years of follow up. Patients struggling with depressive symptoms in the first year of treatment should be identified as having poorer long-term prognosis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".