Delivery of Critical Care in North American Burn Centers
Bibliographic record
Abstract
The management of severely ill patients is an essential component of burn management. As critical care practices become more specialized, and payers such as the Leapfrog group insist on organizational structure for critical care delivery, we sought to determine how critical care is delivered in North American burn centers. Many surgical and medical intensive care units (ICUs) follow an intensivist model with the following features: 1) ICU physician-director is board-certified in critical care, 2) more than 50% of the ICU physicians are board-certified in critical care, and 3) an intensive care team has authority to write patient orders. We hypothesized that the intensivist model is uncommon in North American burn centers. One hundred twenty-seven burn surgeons were surveyed using a web-based questionnaire that addressed institutional volume, attending critical care certification, involvement of intensivist teams, and implementation of evidenced-based practices. A total of 64 surgeons completed the survey (51%). In accordance with several intensivist, model criteria varied by ICU volume and verification status. Lower ICU volume centers are more likely to have an intensivist team that rounds daily (69% vs. 29%, P = .02). Nonverified centers are more likely to have ICU attending without responsibilities outside of the ICU (22% vs. 0%, P = .01). Verified centers are more likely to have dedicated ICU morbidity and mortality conferences (63% vs. 35%, P = .02). Results of this survey indicate that many North American Burn Centers do not use the intensivist model of critical care delivery.
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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 | 0.001 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 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".