Clinical and neurological study of women with precatamenial epilepsy.
Bibliographic record
Abstract
OBJECTIVE: To describe clinical features and seizure dispersion in precatamenial/pericatamenial epilepsy patients. DESIGN: Case series. PLACE AND DURATION OF STUDY: Department of Neurology (formerly Neuropsychiatry), Jinnah Postgraduate Medical Centre (JPMC), Karachi, from July 1991 to November 2001. PATIENTS AND METHODS: Present study included 33 untreated pericatamenial (n: 23, age: 12-40 years, menstrual cycles: 147) and precatamenial (n: 10, age: 13-32 years, menstrual cycles: 70) epileptics with tonic-clonic seizures. Clinical features and seizure dispersion were evaluated during premenstruation, menstruation, and postmenstruation phases. RESULTS: Women with precatamenial epilepsy had highly significant mean phase day seizures during premenstruation versus other phases, whereas women with pericatamenial epilepsy did not show any significant variations. Premenstrual seizures were found significantly more and others as significantly less in % number in precatamenials compared to those in pericatamenials. Furthermore, precatamenial epileptics with primary generalized seizures were significantly higher in % number and secondary generalized seizures as significantly lower against those in pericatamenial epileptics. All precatamenial epileptics under study had incontinence compared to 65% pericatamenial epileptics that had incontinence. Majority of the patients in both groups showed post-ictal headache. CONCLUSION: The present report describes the extent of exacerbation of premenstrual tonic-clonic seizures with clinical features. These investigations may help in understanding partly the complexity of catamenial/precatamenial/ pericatamenial/noncatamenial seizures, and similarities and dissimilarities between pericatamenial and precise precatamenial seizures.
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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 | 0.001 |
| 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) | 0.001 | 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".