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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".