Current Clinical Variables in Schizophrenia Cases with Suicide Attempt History
Bibliographic record
Abstract
OBJECTIVE: High suicide risk was shown to be related with depression and low quality of life in studies investigating clinical variables related to suicidal behavior. The aim of this study was to investigate the effects of a suicide attempt on clinical presentation by comparing sociodemographic variables, clinical signs, symptoms of depression, quality of life, social functionality, and reported adverse drug reactions in schizophrenic patients with and without suicide. METHOD: Positive and Negative Syndrome Scale (PANSS), Calgary Depression Scale (CDS), Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q), Social Functioning Scale (SFS), and Udvalg for Kliniske Undersøgelser Side Effect Rating Scale (UKU) were administered to 115 patients with schizophrenia. RESULTS: 44.3% of patients had at least one suicide attempt. Among sociodemographic variables, a family history of suicide, smoking, and total duration of disease were significantly higher in patients with suicide history than without. Scores of CDS and UKU subscores were significantly higher, and quality of life and social occupation in social functionality were significantly lower in patients with a history of suicide. In correlation analysis, CSD was negatively correlated with Q-LES-Q and independency/performance subscore of SFI, and positively correlated with UKU-Neurological subscore. DISCUSSION: In line with this data, suicidal behavior may be suggested to affect clinical presentation and course characteristic of schizophrenic patients. Additional treatments towards factors that may impact on the clinical course and social support programs might be suggested for these patients.
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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 | 0.002 |
| 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) | 0.002 | 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".