Clinical and genetic associations of depressive symptoms in paranoid schizophrenia
Bibliographic record
Abstract
Objective : to establish clinical and genetic associations in patients with paranoid schizophrenia with and without depressive manifestations. Materials and methods : patients with paranoid schizophrenia after 10–14 days of inpatient treatment were included. Psychometric methods were used: Calgary Depression Scale for Patients with Schizophrenia (CDSS), PANSS scale, Columbia Suicide Risk Rating Scale (C-SSRS). Genotyping of the HTR2A gene (rs6313) was performed by PCR. Statistical methods: Microsoft Excel, IBM SPSS Statistics 26. Results: depressive manifestations were detected in 31.8% (124/390). The least frequent item was “suicide”, but it was expressed most strongly in a severe degree. Conclusions : 31.8% of respondents with paranoid schizophrenia experienced depressive symptoms. An inverse relationship was found between the severity of the condition and the frequency of depressive symptoms: the most common was the absence of symptoms, while severe symptoms were the least common. Hopelessness demonstrated an association with the HTR2A rs6313 gene (p=0.044). No significant correlations were found when comparing the remaining values on the Calgary Depression Scale.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".