Application of the modified Nutrition Risk in Critically Ill score to nutritional risk stratification of trauma victims: A multicenter observational study
Bibliographic record
Abstract
BACKGROUND: The modified Nutrition Risk in Critically Ill (mNUTRIC) score was developed to identify patients most likely to benefit from nutritional therapies and to stratify or select study subjects for clinical trials. The score is not validated in trauma victims in whom adequate nutritional support is important and difficult to achieve. We sought to determine whether a higher mNUTRIC score was associated with worse outcomes and whether caloric and protein intake improved outcome more in patients classified as high risk relative to those classified as low risk. METHODS: We analyzed a prospectively collected database of patients from intensive care units globally. The primary outcome was 60-day hospital mortality, and the secondary outcome was time to discharge alive. We compared outcomes between high and low mNUTRIC score groups and also tested whether the association between outcome and nutrition intake was modified by the mNUTRIC score. RESULTS: A total of 771 trauma patients were included. Most (585; 76%) had a low-risk mNUTRIC (0-4) score, and 186 (24%) had a high-risk (5-9) mNUTRIC score. The overall 60-day mortality was 13%. Patients in the high mNUTRIC group had a higher risk of death than those in the low mNUTRIC group (adjusted odds ratio, 2.6; 95% confidence interval, 1.7-4.2). Overall, there was no relationship between caloric or protein intake and clinical outcomes. However, patients in the high mNUTRIC group fared better with increasing caloric and protein intake, whereas subjects in the low mNUTRIC score group did not (p values for interaction with the mNUTRIC score for time to discharge alive was p = 0.014 for calories and was p = 0.004 for protein). CONCLUSION: A high mNUTRIC score identifies trauma patients at higher risk for poor outcomes and those who may benefit from higher caloric and protein intake. LEVEL OF EVIDENCE: Epidemiological/Prognostic, level III.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".