Patient‐reported dietetic care post hospital for free‐living patients: a Canadian Malnutrition Task Force Study
Bibliographic record
Abstract
BACKGROUND: Transitions out of hospital can influence recovery. Ideally, malnourished patients should be followed by someone with nutrition expertise, specifically a dietitian, post discharge from hospital. Predictors of dietetic care post discharge are currently unknown. The present study aimed to determine the patient factors independently associated with 30-days post hospital discharge dietetic care for free-living patients who transitioned to the community. METHODOLOGY: Nine hundred and twenty-two medical or surgical adult patients were recruited in 16 acute care hospitals in eight Canadian provinces on admission. Eligible patients could speak English or French, provide their written consent, were anticipated to have a hospital stay of ≥2 days and were not considered palliative. Telephone interviews were completed with 747 (81%) participants using a standardised questionnaire to determine whether dietetic care occurred post discharge; 544 patients discharged to the community were included in the multivariate analyses, excluding those who were admitted to nursing homes or rehabilitation facilities. Covariates during and post hospitalisation were collected prospectively and used in logistic regression analyses to determine independent patient-level predictors. RESULTS: Dietetic care post discharge was reported by 61/544 (11%) of participants and was associated with severe malnutrition [Subjective Global Assessment category C: odd's ratio (OR) 2.43 (1.23-4.83)], weight loss post discharge [(OR 2.86 (1.45-5.62)], comorbidity [(OR 1.09 (1.02-1.17)] and a dietitian consultation on admission [(OR 3.41 (1.95-5.97)]. CONCLUSIONS: Dietetic care post discharge occurs in few patients, despite the known high prevalence of malnutrition on admission and discharge. Dietetic care in hospital was the most influential predictor of post-hospital care.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".