Controlled enteral nutrition in critical care patients – A randomized clinical trial of a novel management system
Bibliographic record
Abstract
PURPOSE: Nutritional therapy is essential to ICU care. Successful early enteral feeding is hindered by lack of protocols, gastrointestinal intolerance and feeding interruptions, leading to impaired nutritional intake. smART+ was developed as a nutrition management feeding platform controlling tube positioning, reflux, gastric pressure, and malnutrition. This study evaluated the potential of this new ICU care platform to deliver targeted nutrition and improve ICU outcomes. METHODS: Critically ill patients ≥18 years-old, mechanically ventilated and enterally fed, were randomized to receive ESPEN-guideline-based nutrition or smART+ -guided nutrition for 2-14 days. Primary endpoint was average deviation from daily targeted nutrition determined via calculation of energy targets per calorimetry. Secondary endpoints included gastric residual volumes, length of stay (LOS) and length of ventilation (LOV). RESULTS: smART+ achieved a mean deviation from daily targeted nutrition of 10.5% (n = 48) versus 34.3% for control (n = 50), p < 0.0001. LOS and LOV were decreased in the smART+ group versus control (mean LOS: 10.4 days versus 13.7; reduction 3.3 days, adjusted HR 1.71, 95% CI:1.13,2.60, p = 0.012; mean LOV: 9.5 days versus 12.8 days reduction of 3.3 days, adjusted HR 1.64, 95% CI:1.08-2.51, p = 0.021). Feeding goals were met (within ±10%) on 75.7% of days for smART+ versus 23.3% for control (p < 0.001). No treatment-related adverse events occurred in either group. The study was stopped due to success in a planned interim analysis of the first 100 patients. CONCLUSION: The smART+ Platform improved adherence to feeding goals and reduced LOS and LOV versus standard of care in critically ill patients. TRIAL REGISTRATION: NCT04098224; registered September 23, 2019.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".