Beliefs of physician directors on the management of devastating brain injuries at the Canadian emergency department and intensive care unit interface: a national site-level survey
Bibliographic record
Abstract
PURPOSE: Insufficient evidence-based recommendations to guide care for patients with devastating brain injuries (DBIs) leave patients vulnerable to inconsistent practice at the emergency department (ED) and intensive care unit (ICU) interface. We sought to characterize the beliefs of Canadian emergency medicine (EM) and critical care medicine (CCM) physician site directors regarding current management practices for patients with DBI. METHODS: We conducted a cross-sectional survey of EM and CCM physician directors of adult EDs and ICUs across Canada (December 2022 to March 2023). Our primary outcome was the proportion of respondents who manage (or consult on) patients with DBI in the ED. We conducted subgroup analyses to compare beliefs of EM and CCM physicians. RESULTS: Of 303 eligible respondents, we received 98 (32%) completed surveys (EM physician directors, 46; CCM physician directors, 52). Most physician directors reported participating in the decision to withdraw life-sustaining measures (WLSM) for patients with DBI in the ED (80%, n = 78), but 63% of these (n = 62) said this was infrequent. Physician directors reported that existing neuroprognostication methods are rarely sufficient to support WLSM in the ED (49%, n = 48) and believed that an ICU stay is required to improve confidence (99%, n = 97). Most (96%, n = 94) felt that providing caregiver visitation time prior to WLSM was a valid reason for ICU admission. CONCLUSION: In our survey of Canadian EM and CCM physician directors, 80% participated in WLSM in the ED for patients with DBI. Despite this, most supported ICU admission to optimize neuroprognostication and patient-centred end-of-life care, including organ donation.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".