Cognitive, sleep, and neurophysiological markers among suicidal depressed patients
Bibliographic record
Abstract
Background Depressive disorders are associated with the highest probability of suicide. Different cognitive factors raise the probability of suicide. Sleep disorders are closely related to depression and may play a role in suicide. Aims Evaluation of whether suicidal depressed patients reveals distinct signs of cognitive, sleep, and neurophysiologic damage compared with depressed people who are not suicidal. Settings and design A case–control study involving suicidal depressed patients and non-suicidal in comparison to the control group. Patients and methods A random collection of 120 participants, who were divided into three groups at a ratio of 1:1:1 to be subjected to structured clinical interview for DSM-5(SCID-I), Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment scale (MoCA), Hamilton Depression Rating Scale (HDRS), Beck Scale for Suicidal Ideation (BSSI), Epworth Sleepiness Scale (ESS), and Standard Electroencephalogram (EEG). Statistical analysis SPSS, version 22, for analysis of data. Results Cognitive impairment, especially attention, language, visuospatial, naming, abstract thinking, and sleep disorders were significantly higher in suicidal depressed patients than in non-suicidal depressed patients and control. EEG shows no significant difference among the groups. Conclusion Suicidal depressed patients had significant impairment in different cognitive domains and sleep but no significant difference in EEG compared with non-suicidal depressed patients or control.
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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 | 0.005 | 0.101 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".