A Descriptive Analysis of Prognostic Indicators in Patients with Non-Convulsive Status Epilepticus in a Tertiary Hospital Population
Why this work is in the frame
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Bibliographic record
Abstract
Background: Non-convulsive status epilepticus (NCSE) is defined as a change in mental state of at least 30 minutes associated with continuous or nearly continuous epileptiform discharges. Identification of prognostic indicators can guide decision making surrounding the use of poorly established treatment interventions in this heterogeneous population. Methods: We identified 66 consecutive inpatients with NCSE. Data surrounding clinical, electrographic, and treatment factors were collected via a retrospective systematic review of medical records and electronic EEGs, and were correlated with discharge outcome (return to baseline, new disability, or death). Results: Of all subjects, 21% returned to baseline, 26% acquired new disability, and 53% died, of whom half had anoxic encephalopathy. On univariate analysis, seventeen variables correlated significantly with death, although multivariate logistic regression analysis subsequently identified only comatose state and number of life threatening comorbidities as independent predictors of mortality. Of survivors, comatose state, critical care environment, length of hospital stay, and acute symptomatic seizures predicted new disability, with the latter two showing independent significance. Following exclusion of cases with anoxic encephalopathy, the use of an anaesthetic infusion was also an independent predictor of mortality. Conclusions: NCSE is associated with variable morbidity and mortality. While one fifth of our NCSE patients returned to baseline, those comatose with acute structural/metabolic seizures, anaesthetic infusions, and life threatening comorbidities were unlikely to survive without disability at discharge.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| 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) | 0.000 | 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 it