Frequency of Suicidal Intent in patients with Epilepsy
Bibliographic record
Abstract
Objective: To determine the frequency of suicidal intent in patients with epilepsy. Methodology: This cross-sectional study was conducted at the Department of Psychiatry, Department of Neurology, and Department of Medical and Surgical Emergency, Services Hospital, Lahore from January to July 2022. The inclusion criteria were patients with epilepsy of both male and female gender, aged between 15-45 years. Total 226 patients fulfilling inclusion criteria were enrolled after informed consent. The patients were assessed for suicidal risk using Beck's suicide intent scale. The data was obtained by using a self-devised proforma. The patients scoring >15 were classified to have suicidal intent. Results: In this study, out of 226 cases, 43(19.03%) were between 15-30 years of age, whereas 183(80.97%) were between 31-45 years of age. The mean age was 36.97±5.98 years. Among patients, 125(55.31%) were males, whereas 101(44.69%) were females. Out of 226 patients, 54(23.89%) patients showed suicidal intent. The frequency of suicidal intent in patients with epilepsy was 54 (23.89%). Conclusion: The frequency of suicidal intent was higher in patients with epilepsy. Therefore, screening all epilepsy patients should be done for early diagnosis and treatment.
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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 | 0.000 |
| 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".