Nutrition Care after Discharge from Hospital: An Exploratory Analysis from the More-2-Eat Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Many patients leave hospital in poor nutritional states, yet little is known about the post-discharge nutrition care in which patients are engaged. This study describes the nutrition-care activities 30-days post-discharge reported by patients and what covariates are associated with these activities. Quasi-randomly selected patients recruited from 5 medical units across Canada (n = 513) consented to 30-days post-discharge data collection with 48.5% (n = 249) completing the telephone interview. Use of nutrition care post-discharge was reported and bivariate analysis completed with relevant covariates for the two most frequently reported activities, following recommendations post-discharge or use of oral nutritional supplements (ONS). A total of 42% (n = 110) received nutrition recommendations at hospital discharge, with 65% (n = 71/110) of these participants following those recommendations; 26.5% (n = 66) were taking ONS after hospitalization. Participants who followed recommendations were more likely to report following a special diet (p = 0.002), different from before their hospitalization (p = 0.008), compared to those who received recommendations, but reported not following them. Patients taking ONS were more likely to be at nutrition risk (p < 0.0001), malnourished (p = 0.0006), taking ONS in hospital (p = 0.01), had a lower HGS (p = 0.0013; males only), and less likely to believe they were eating enough to meet their body’s needs (p = 0.005). This analysis provides new insights on nutrition-care post-discharge.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it