Malnutrition at Hospital Admission—Contributors and Effect on Length of Stay
Bibliographic record
Abstract
BACKGROUND: In hospitals, length of stay (LOS) is a priority but it may be prolonged by malnutrition. This study seeks to determine the contributors to malnutrition at admission and evaluate its effect on LOS. MATERIALS AND METHODS: This is a prospective cohort study conducted in 18 Canadian hospitals from July 2010 to February 2013 in patients ≥ 18 years admitted for ≥ 2 days. Excluded were those admitted directly to the intensive care unit; obstetric, psychiatry, or palliative wards; or medical day units. At admission, the main nutrition evaluation was subjective global assessment (SGA). Body mass index (BMI) and handgrip strength (HGS) were also performed to assess other aspects of nutrition. Additional information was collected from patients and charts review during hospitalization. RESULTS: One thousand fifteen patients were enrolled: based on SGA, 45% (95% confidence interval [CI], 42%-48%) were malnourished, and based on BMI, 32% (95% CI, 29%-35%) were obese. Independent contributors to malnutrition at admission were Charlson comorbidity index > 2, having 3 diagnostic categories, relying on adult children for grocery shopping, and living alone. The median (range) LOS was 6 (1-117) days. After controlling for demographic, socioeconomic, and disease-related factors and treatment, malnutrition at admission was independently associated with prolonged LOS (hazard ratio, 0.73; 95% CI, 0.62-0.86). Other nutrition-related factors associated with prolonged LOS were lower HGS at admission, receiving nutrition support, and food intake < 50%. Obesity was not a predictor. CONCLUSION: Malnutrition at admission is prevalent and associated with prolonged LOS. Complex disease and age-related social factors are contributors.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".