The Relationship Between Depressive Symptoms, Smoking And Disease Severity In Patients With Schizophrenia
Bibliographic record
Abstract
Background and Aims:Patients with schizophrenia have high prevalence of both depression and cigarette smoking. However, no study has simultaneously compared the severity of schizophrenia, depressive symptoms, treatment-resistance and nicotine dependence.The aim of this study was to determine clinical variables associated with the severity of depression in patients with schizophrenia.Methods:This cross-sectional study was carried out in patients with schizophrenia, who were not taking antidepressants. The Fagerstrom Test for Nicotine Dependence (FTND) was used to assess tobacco dependence, Calgary Depression Rating Scale for Schizophrenia (CDSS) to measure depression, and the Positive and Negative Syndrome Scale (PANSS) to evaluate symptoms of schizophrenia. Treatment-resistant schizophrenia (TRS) was defined as a failure of at least two adequate antipsychotic trials.Results:Overall 340 patients were included (median age 45 years, 204 smokers, 300 males and 125 with TRS). The CDSS total score was positively correlated with the PANSS total score (u03c1=0.555; p<0.001), chlorpromazine equivalents (u03c1=0.197; p=0.011) and age (u03c1=0.144; p=0.008). Patients with TRS had higher PANSS total score and all its subscales but also higher CDSS score (p<0.001). The CDSS was similar between smokers and non-smokers, and not related to FTND score.Conclusions:While the severity of depression was not related to smoking status and nicotine dependence, it was correlated with the intensity of psychotic symptoms and antipsychotic dose. Depression in our sample might be induced by more pronounced psychopathology or higher doses of antipsychotics, but not by smoking.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".