P.146 Exploring the Canadian management of aSAH and delayed cerebral ischemia
Bibliographic record
Abstract
Background: Delayed Cerebral Ischemia (DCI) is a complication of aneurysmal subarachnoid hemorrhage (aSAH) and is associated with significant morbidity and mortality. A paucity of high-quality evidence is available to guide the management of DCI. As such, our objective was to evaluate practice patterns of Canadian physicians regarding the management of aSAH and DCI. Methods: The Canadian Neurosurgery Research Collaborative (CNRC) performed a cross-sectional survey of Canadian neurosurgeons, intensivists, and neurologists who manage aSAH. The survey was distributed to members of the Canadian Neurosurgical and Neurocritical Care Societies, respectively. Responses were analyzed using quantitative and qualitative methods. Results: The response rate was 129/340 (38%). Agreement among respondents included the need for intensive care unit admission, use of clinical and radiographic monitoring, and prophylaxis for prevention of DCI. Indications for starting hyperdynamic therapy varied. There was discrepancy in the proportion of patients felt to require intravenous milrinone, intra-arterial vasodilators, or physical angioplasty for treatment of DCI. Most respondents reported their facility does not utilize a standardized definition for DCI. Conclusions: DCI is an important clinical entity for which no consensus exists in management among Canadian practitioners. The CNRC calls for the development of national standards in the diagnosis and management of DCI.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".