Effect of Critical Care Medicine Fellows on Patient Outcome in the Intensive Care Unit
Bibliographic record
Abstract
BACKGROUND: The impact that physician trainees have on patient outcomes in academic adult medical/surgical intensive care units (ICUs) has not been adequately assessed. METHOD: All admissions to adult ICUs within the Calgary Health Region over a three-year period when a critical care medicine fellow (CCMF) was on service were compared to when an attending physician was alone on service. Primary outcomes were ICU and in-hospital mortality and length of stay (LOS). RESULTS: CCMFs and attending physicians admitted 3,341 patients, while attending physicians alone admitted 3,224 patients. There was no difference in ICU or in-hospital mortality between the two groups; regression analysis determined CCMFs did not affect patient LOS. CONCLUSION: In teaching hospitals with adult mixed medical/surgical ICUs, CCMFs do not have an effect on patient outcome or LOS. Improved patient outcomes at academic institutions previously attributed to the presence of CCMFs may instead be due to institution and patient-related factors.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".