POTENTIALLY DEFERRABLE PATIENTS PRESENTING WITH SEIZURES TO EMERGENCY DEPARTMENTS IN LONDON, ONTARIO
Bibliographic record
Abstract
Objective: To estimate the proportion of seizure presentations to London EDs that could be classified as “potentially deferrable” (PD), defined as cases that ωuld be more appropriately cared for in a non-ED setting. To compare non-deferrable patients with PD patients in terms of age, sex, seizure presentation characteristics, history of seizures and health care resource use. Methods: Chart review conducted of patients identified with a seizure that reported to any of the 3 ED sites in London in 2005. Criteria were developed a priori to classify visits as non-deferrable or PD. Epidemiological model building was used to determine explanatory factors for visit deferability. Results: 830 patients presented to an ED, with a total of 1200 visits, 37% were PD. Age, triage code, use of hospital resources, length of stay, witnessed seizures, history of seizures and seizure medications were significantly associated with deferability. Conclusion: One-third of visits were PD, presenting an opportunity for educational intervention.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".