Depressive symptoms in first episode schizophrenia patients under treatment: one-year follow-up comparison of classical and atypical antipsychotics
Bibliographic record
Abstract
Objective: Depression is an important syndrome occurring frequently during the course of schizophrenia. In patients using atypical antipsychotics in the treatment of schizophrenia, depressive symptoms are expected at a lower rate. In this retrospective study, evaluation of depressive symptoms in patients who were monitored for one year with first-episode schizophrenia using atypical or conventional antipsychotic treatment was intended. Methods: The study was carried out by examining the records of 93 patients with first-episode schizophrenia. The data of the Brief Psychiatric Rating Scale, Scale for the Assessment of Positive Symptoms, Scale for the Assessment of Negative Symptoms, Hamilton Depression Rating Scale and the Calgary Depression Scale were used for evaluation. Classical antipsychotics (n=21), olanzapine (n=28), risperidone (n=25) or quetiapine (n=19) were found to be used in the treatment of subjects. According to clinical status, the subjects were invited to the controls at intervals not longer than two months. The above scales were applied to subjects at each control to measure the depressive symptoms and to determine the relationship of those with clinical variables. Results: The classic antipsychotic group (57.1%) showed more significantly severe depressive symptoms (HAM-D score≥17) than the atypical antipsychotic group (31.9%). The rate of depression and depressive symptoms were similar among the subjects used atypical antipsychotic agents. Conclusion: Possibly depending on their mechanism of action and the effects on negative symptoms of patients with schizophrenia, the atypical antipsychotic drugs showed lower rate of depression compared to conventional 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 | 0.000 |
| 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 | 0.000 |
| 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".