Close to recommended caloric and protein intake by enteral nutrition is associated with better clinical outcome of critically ill septic patients: secondary analysis of a large international nutrition database
Bibliographic record
Abstract
INTRODUCTION: Current international sepsis guidelines recommend low-dose enteral nutrition (EN) for the first week. This contradicts other nutrition guidelines for heterogenous groups of ICU patients. Data on the optimal dose of EN in septic patients are lacking. Our aim was to evaluate the effect of energy and protein amount given by EN on clinical outcomes in a large cohort of critically ill septic patients. METHODS: We conducted a secondary analysis of pooled data collected prospectively from international nutrition studies. Eligible patients had a diagnosis of sepsis and/or pneumonia and were admitted to the ICU for ≥3 days, mechanically ventilated within 48 hours of ICU admission and only receiving EN. Patients receiving parenteral nutrition were excluded. Data were collected from ICU admission up to a maximum of 12 days. Regression models were used to examine the impact of calorie and protein intake on 60-day mortality and ventilator-free days. RESULTS: Of the 13,630 patients included in the dataset, 2,270 met the study inclusion criteria. Patients received a mean amount of 1,057 kcal/d (14.5 kcal/kg/day) and 49 g protein/day (0.7 g/kg/d) by EN alone. Patients were mechanically ventilated for a median of 8.4 days and 60-day mortality was 30.5%. An increase of 1,000 kcal was associated with reduced 60-day mortality (odds ratio (OR) 0.61; 95% confidence interval (CI) 0.48 to 0.77, P <0.001) and more ventilator-free days (2.81 days, 95% CI 0.53 to 5.08, P = 0.02) as was an increase of 30 g protein per day (OR 0.76; 95% CI 0.65 to 0.87, P <0.001 and 1.92 days, 95% CI 0.58 to 3.27, P = 0.005, respectively). CONCLUSIONS: In critically ill septic patients, a calorie and protein delivery closer to recommended amounts by EN in the early phase of ICU stay was associated with a more favorable outcome.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.004 |
| 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) | 0.002 | 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".