Treatment adherence and outcomes in the management of convulsive status epilepticus in the emergency room
Bibliographic record
Abstract
ABSTRACT Purpose According to published literature status epilepticus (SE) is associated with 7‐39% mortality. Timely management is one variable that potentially influences the outcome. We sought to review the process of acute management of SE at the University of Alberta Hospital and correlate outcome with adherence to a recommended treatment protocol. Methods We identified 86 patients 18 years of age or older who presented with convulsive SE to our emergency room between 2000 and 2004. We defined SE as continuous convulsive activity for 30 or more minutes or ≥ 2 convulsions with incomplete recovery in the interim. Information was collected pertaining to etiology, epidemiology, and management. We then reviewed the relationship of the treatment protocol in terms of mortality and morbidity. Results Forty five patients were included. There were 18 males and 27 females with a mean age of 45 years; 80% were known to have epilepsy. Subtherapeutic drug levels were found in the majority 60%; benzodiazepines (diazepam 81% and lorazepam 19%) were the first line agent in 93.3% mostly initiated by paramedics (EMS); 48.9% of patients required intubation and 26.7% required admission to intensive care. Four patients died. Control of convulsive SE was obtained sooner for patients in whom therapy was administered according to the recommended time frame (p ≤ 0.02). Conclusion The presence of strict treatment protocols for SE made readily available for the treating staff could potentially improve the outcome of patients. Despite the lack of standardized treatment protocols among various physicians, most patients are treated according to generally recommended sequence and time frames. Analysis of this data will help devise prospective treatment protocols.
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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 | 0.003 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".