Evaluating depressive symptoms and their impact on outcome in schizophrenia applying the Calgary Depression Scale
Bibliographic record
Abstract
Schennach-Wolff R, Obermeier M, Seemüller F, Jäger M, Messer T, Laux G, Pfeiffer H, Naber D, Schmidt LG, Gaebel W, Klosterkötter J, Heuser I, Maier W, Lemke MR, Rüther E, Klingberg S, Gastpar M, Möller H-J, Riedel M. Evaluating depressive symptoms and their impact on outcome in schizophrenia applying the Calgary Depression Scale. Objective: To examine depressive symptoms, their course during treatment, and influence on outcome. Method: Weekly Calgary Depression Scale for Schizophrenia ratings were performed in 249 inpatients with schizophrenia. Early response was defined as a 20% reduction in the total score of the Positive and Negative Syndrome Scale for Schizophrenia from admission to week 2, response as a 50% reduction in the total score of the Positive and Negative Syndrome Scale for Schizophrenia (PANSS) from admission to discharge and remission according to the consensus criteria. Results: Thirty six per cent of the patients were depressed at admission, with 23% of them still being depressed at discharge. Depressed patients scored significantly higher on the PANSS negative and general psychopathology subscore, featured more impairments in subjective well-being (P < 0.0001) and functioning (P < 0.0001). They suffered from more suicidality (P = 0.0021), and had greater insight into their illness (P = 0.0105). No significant differences were found regarding early response, response, and remission. Conclusion: Patients with depressive symptoms should be monitored closely, given the burden of negative symptoms, their impairments in well-being and functioning and the threat of suicidality.
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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) | 0.000 | 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".