Factors associated with nutritional decline in hospitalised medical and surgical patients admitted for 7 d or more: a prospective cohort study
Bibliographic record
Abstract
This prospective cohort study was conducted in eighteen Canadian hospitals with the aim of examining factors associated with nutritional decline in medical and surgical patients. Nutritional decline was defined based on subjective global assessment (SGA) performed at admission and discharge. Data were collected on demographics, medical information, food intake and patients' satisfaction with nutrition care and meals during hospitalisation; 424 long-stay (≥7 d) patients were included; 38% of them had surgery; 51% were malnourished at admission (SGA B or C); 37% had in-hospital changes in SGA; 19·6% deteriorated (14·6% from SGA A to B/C and 5% from SGA B to C); 17·4% improved (10·6% from SGA B to A, 6·8% from SGA C to B/A); and 63·0 % patients were stable (34·4% were SGA A, 21·3% SGA B, 7·3% SGA C). One SGA C patient had weight loss ≥5%, likely due to fluid loss and was designated as stable. A subset of 364 patients with admission SGA A and B was included in the multiple logistic regression models to determine factors associated with nutritional decline. After controlling for SGA at admission and the presence of a surgical procedure, lower admission BMI, cancer, two or more diagnostic categories, new in-hospital infection, reduced food intake, dissatisfaction with food quality and illness affecting food intake were factors significantly associated with nutritional decline in medical patients. For surgical patients, only male sex was associated with nutritional decline. Factors associated with nutritional decline are different in medical and surgical patients. Identifying these factors may assist nutritional care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".