Association Between Risk Factors and Intensive Nutritional Intervention Outcomes in Elderly Individuals
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to identify risk factors for intensive nutritional intervention outcomes in elderly undernourished patients to help reduce the number of patients with prolonged hospital stay or without recuperation of previous activities of daily living and quality of life. METHODS: In total, 230 patients who received interventions from a nutrition support team (NST) between January 2016 and July 2018 were included. Patients were classified into two groups based on NST intervention outcomes: patients with improved nutritional status were included in the successful group, whereas those whose nutritional status did not improve, as defined by progressive illness or death, were classified into the non-successful group. We assessed patient characteristics, laboratory data, and nutrition support methods. RESULTS: Our multivariate Cox proportional hazard analysis showed that: 1) The presence of peripheral parenteral nutrition (hazard ratio (HR): 1.80; 95% confidence interval (CI): 1.13 - 2.88) was identified as an independent risk factor for NST intervention outcomes; 2) The energy fill rate to total energy expenditure was < 66.0% (HR: 1.61; 95% CI: 0.98 - 2.66); and 3) A geriatric nutritional risk index score < 70.0 (HR: 1.54; 95% CI: 0.92 - 2.56) tended to be negatively associated with NST intervention outcomes. CONCLUSIONS: In addition to the nutrition therapy provided by a traditional NST, patients with the risk factors require nutritional intervention. Elderly individuals should also receive nutrition care because they have been recuperating at their home or in long-term care facilities, to prevent experiencing adverse conditions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".