Nutrition Therapy in Critically Ill Patients Following Cardiac Surgery: Defining and Improving Practice
Bibliographic record
Abstract
BACKGROUND: Malnutrition is a predictor of poor outcome following cardiac surgery. We define nutrition therapy after cardiac surgery to identify opportunities for improvement. METHODS: International prospective studies in 2007-2009, 2011, and 2013 were combined. Sites provided institutional and patient characteristics from intensive care unit (ICU) admission to ICU discharge for a maximum of 12 days. Patients had valvular, coronary artery bypass graft (CABG) surgery, or combined procedures and were mechanically ventilated and staying in the ICU for ≥3 days. RESULTS: There were 787 patients from 144 ICUs. In total, 120 patients (15.2%) had valvular surgery, 145 patients (18.4%) had CABG, and 522 patients (66.3%) underwent a combined procedure. Overall, 60.1% of patients received artificial nutrition support. For these patients, 78% received enteral nutrition (EN) alone, 17% received a combination of EN and parenteral nutrition (PN), and 5% received PN alone. The remaining 314 patients (40%) received no nutrition. The mean (SD) time from ICU admission to EN initiation was 2.3 (1.8) days. The adequacy of calories was 32.4% ± 31.9% from EN and PN and 25.5% ± 27.9% for patients receiving only EN. In EN patients, 57% received promotility agents and 20% received small bowel feeding. There was no significant relationship between increased energy or protein provision and 60-day mortality. CONCLUSION: Postoperative cardiac surgery patients who stay in the ICU for 3 or more days are at high risk for inadequate nutrition therapy. Further studies are required to determine if targeted nutrition therapy may alter clinical outcomes.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".