<i>Outcomes of Screening And Nutritional Intervention</i> Among Older Adults in Healthcare Facilities
Bibliographic record
Abstract
A nutritional screening and early intervention program was administered to older adults in a subacute care facility. The study group was recruited among patients aged 65 or older, who were admitted to the geriatric and rehabilitation units of two hospitals. Two simple, reliable, and valid tools were used to screen subjects for the risk or presence of malnutrition. Those determined to be at high nutritional risk (n=62) were included in the study. Dietitians then conducted a full nutritional assessment and implemented a nutritional care plan for these subjects. Weekly follow-up was completed to measure oral intake, weight, and biochemical indices. A Short-Form 36 Health Survey was administered upon admission and discharge. Results showed significant increases in energy (p=0.0001) and protein (p=0.01) intakes, and in serum albumin (p=0.001), prealbumin (p=0.003), transferrin (p=0.024), and hematocrit (p=0.026) levels. There was also a significant increase in seven of the eight dimensions of the health-related quality of life questionnaire (p<0.05). Outcomes improve when older adults are screened for the risk or presence of malnutrition and receive an early nutritional care program.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".