Nutrition Care of Critically Ill Patients with Leukemia: A Retrospective Study
Bibliographic record
Abstract
Adults with acute leukemia (AL) are at high risk of malnutrition due to their disease and treatment side effects and may be admitted to the intensive care unit (ICU), further increasing the risk of malnutrition. Although ICU care includes some form of nutrition, patients typically receive less than prescribed energy and protein. Our objective was to characterize the nutrition care for critically ill patients with AL. We completed a retrospective review of adults with AL admitted to the Medical/Surgical ICU >24 hours. Descriptive statistics were performed on collected data including: demographics, APACHE II and Nutric scores, nutrition therapy, reasons for withholding nutrition, and mortality status at discharge. Data were collected on 154 AL patients with an average APACHE II score of 27 and Nutric score of 5.96. ICU mortality was 36%. Enteral nutrition (EN) was most commonly prescribed. Patients on EN received 55% of energy and 51% of protein prescribed. EN was commonly withheld for airway management and gastrointestinal impairment. Patients with AL received low amounts of energy and protein in the ICU and had a high Nutric score. Strategies and barriers to improve protein intake in this population are identified.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".