Depression in Kraepelinian Schizophrenia
Bibliographic record
Abstract
Objective. Depressive symptoms are prevalent, under- recognised and clinically important in patients suffering from schizophrenia. Depressive symptoms in schizophrenia patients are associated with distinct morbidity and mortality. The objective of this study was to investigate the prevalence of depressive symptoms in a subgroup of chronic schizophrenia, Kraepelinian schizophrenia, and the association with severity of illness. Kraepelinian schizophrenia is characterised by a chronic, unremitting, severe course of illness and severe deterioration of functioning in social, work and self-care domains. Method. The Calgary Depression Scale for Schizophrenia (CDSS) and the Clinical Global Impression Severity (CGI-S) scale were administered to 113 patients who fulfilled the criteria of Kraepelinian schizophrenia. Results. Sixty-eight males and 45 females participated in the study. Of this group, 17.7% scored 5 or more on the CDSS. The CGI-S scores indicated that almost half of the patients were moderately ill (i.e. a score of 4 on the CGI-S scale). Of the patients, 94 were receiving first-generation antipsychotic medication and 19 second- generation antipsychotic medication. Thirteen patients were also receiving antidepressant medication. Conclusion. The findings of this study are consistent with current reports in the literature that depressive symptoms are not common in Kraepelinian schizophrenia, even though patients are moderately to severely ill in both symptom and functional domains.
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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 | 0.001 |
| 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".