The physical functional capacity of frail elderly persons undergoing ambulatory rehabilitation is related to their nutritional status
Bibliographic record
Abstract
OBJECTIVES: To estimate the prevalence of malnutrition in frail elders undergoing rehabilitation and the association between their nutritional status and physical function. DESIGN: Observational study of new participants undergoing ambulatory rehabilitation. SETTING: Two Geriatric Day Hospitals (GDH) in Montreal, Quebec. PARTICIPANTS: 121 women and 61 men. INTERVENTION: Evaluation of nutritional status, body composition and physical function. MEASUREMENTS: The nutritional status was assessed with a composite index based on anthropometric measurements and serum albumin, as well as using the Mini Nutritional Assessment (MNA) questionnaire. Patients were classified as well-nourished, having mild/at risk of malnutrition or malnourished. Body composition was estimated by bioimpedance and handgrip strength and gait speed by standard methods. RESULTS: 13% of patients were found to be mildly malnourished, whereas 6% were malnourished. Malnourished patients were older and had worse cognition, lower BMI, and % body fat (all p<0.05). Malnourished patients and those with mild malnutrition had lower weight, triceps skinfold thickness, muscle and fat mass (all, p<0.003). Handgrip strength was different according to the nutritional status (p=0.034) and correlated with muscle mass (r=0.65, p<0.001). MNA classified 53% of patients as being at risk whereas 3% were malnourished and it correlated with gait speed (r=0.26, p=0.001). CONCLUSION: There is a high prevalence of patients in GDH at risk or with mild malnutrition. Being malnourished was associated with worse physical performance, which suggests that a nutritional intervention may be of benefit in improving their physical function.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".