Intervention time and adverse events in a canadian epilepsy monitoring unit: An updated audit
Bibliographic record
Abstract
Background: Optimizing patient safety in the epilepsy monitoring unit (EMU) has become a topic of increasing interest. We performed an audit of our center's new single-floor EMU, assessing intervention rate (IR), intervention time (IT), and adverse events (AEs). Methods: A prospective study was conducted on all clinical seizures of patients admitted over a one-year period at our Canadian academic tertiary care center's new single-floor EMU. This single-floor EMU was supervised by EEG technologists during daytime (similar to the old set-up) and beneficiary attendants during nighttime/weekends (versus live video feed to the central nursing station on the neurology ward previously). Among 153 admissions, 79 were analyzed, and a total of 537 seizures were reviewed to assess IR, IT, and AEs. Univariate comparisons were performed with our double-floor EMU, which we reported in a previous publication. Results: In our new single-floor EMU, the IR was 61.1 % and overall median IT was 29.0s (19.0s-45.9s). The AE rate was 4.8 %. Compared to previously reported numbers for our old double-floor EMU (IR = 27.8 %; IT = 21.0s; AE = 1.2 %), the IR was significantly higher ((p < 0.001) but unexpectedly, the median IT was higher (p < 0.001) as well as the AE rate (p < 0.001). Conclusion: This prospective evaluation revealed a small but non-negligible rate of complications in our EMU, higher than our prior retrospective audit. Heightened levels of supervision in our new single-floor EMU led to higher IR. This may have led to artificially longer ITs.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".