Relationship between nutrition support and clinical outcomes in post–lung transplant patients in intensive care unit settings: A retrospective study
Bibliographic record
Abstract
BACKGROUND: Nutrition status significantly influences outcomes after solid organ transplantation, yet data on energy and protein intake in lung transplantation (LTx) patients in the intensive care unit (ICU) are scarce. The objective is to examine the medical nutrition therapy and clinical outcomes in mechanically ventilated post-LTx adults. METHODS: This retrospective study (2022-2023) included adults post-LTx receiving mechanical ventilation admitted to the ICU. Clinical and nutrition parameters were recorded for the first 14 days of ICU stay. The Wilcoxon rank sum test or Fisher exact test were used to compare variables followed by a multivariate analysis to determine predictors of ICU length of stay (LOS). RESULTS: . Both ICU and total hospital LOS were prolonged in patients who received >1.2 g/kg/day of protein, but LOS was not affected by energy intake or nutrition status. There were no associations with mortality or infection rate. In a multivariate analysis, no individual main effect variable was significantly associated with ICU LOS. However, a significant interaction between protein intake and Acute Physiology and Chronic Health Evaluation Score (β = 0.0216; p = 0.0092) indicted that the effect of protein intake on ICU LOS is modified by illness severity. CONCLUSION: In critically ill post-LTx patients, higher protein intake was associated with a longer ICU and hospital LOS. This relationship appears to be influenced by illness severity, emphasizing the importance of individualized nutrition strategies in this high-risk population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".