Creating a Culture of Clinical Excellence in Critical Care Nutrition
Bibliographic record
Abstract
OBJECTIVE: To develop, validate, and implement a system to reward top performers in critical care nutrition practice and to illuminate characteristics of top-performing intensive care units (ICUs). DESIGN: An international, prospective, observational, cohort study conducted in May 2008. SETTING: 179 ICUs from 18 countries. PATIENTS: 2956 consecutively enrolled mechanically ventilated adult patients who stayed in the ICU for at least 72 hours. INTERVENTIONS: To qualify for the "Best of the Best" (BOB) award, sites had to have implemented a nutrition protocol and contributed complete data on a minimum of 20 patients. MEASUREMENTS AND MAIN RESULTS: Data on nutrition practices were collected from ICU admission to ICU discharge for a maximum of 12 days. Eligible sites were ranked based on their performance on the following 5 criteria: adequacy of provision of energy, use of enteral nutrition (EN), early initiation of EN, use of promotility drugs and small bowel feeding tubes, and adequate glycemic control. Of the 179 participating ICUs, 81 qualified for the BOB award. Overall, the average nutrition adequacy across sites was 56.2% (site range, 20.3%-90.1%). The top 10 performers were identified and publicly recognized. Regression analysis suggested that the presence of a dietitian in the ICU was associated with a high BOB award ranking, whereas being located in the United States or China, relative to other participating countries, was associated with worst performance. CONCLUSIONS: There is variable performance with respect to critical care nutrition practices across the world.
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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 | 0.065 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".