The effect of an intensive care unit staffing model on tidal volume in patients with acute lung injury
Bibliographic record
Abstract
INTRODUCTION: Little is known about the mechanisms through which intensivist physician staffing influences patient outcomes. We aimed to assess the effect of closed-model intensive care on evidence-based ventilatory practice in patients with acute lung injury (ALI). METHODS: We conducted a secondary analysis of a prospective population-based cohort of 759 patients with ALI who were alive and ventilated on day three of ALI, and were cared for in 23 intensive care units (ICUs) in King County, Washington. RESULTS: We compared day three tidal volume (VT) in open versus closed ICUs adjusting for potential patient and ICU confounders. In 13 closed model ICUs, 429 (63%) patients were cared for. Adjusted mean VT (mL/Kg predicted body weight (PBW) or measured body weight if height not recorded) for patients in closed ICUs was 1.40 mL/Kg PBW (95% confidence interval (CI) = 0.57 to 2.24 mL/Kg PBW) lower than patients in open model ICUs. Patients in closed ICUs were more likely (odds ratio (OR) = 2.23, 95% CI = 1.09 to 4.56) to receive lower VT (<or= 6.5 mL/Kg PBW) and were less likely (OR = 0.30, 95% CI = 0.17 to 0.55) to receive a potentially injurious VT (>or= 12 mL/Kg PBW) compared with patients cared for in open ICUs, independent of other covariates. The effect of closed ICUs on hospital mortality was not changed after accounting for delivered VT. CONCLUSIONS: Patients with ALI cared for in closed model ICUs are more likely to receive lower VT and less likely to receive higher VT, but there were no other differences in measured processes of care. Moreover, the difference in delivered VT did not completely account for the improved mortality observed in closed model ICUs.
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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".