A Randomized, Crossover Trial of High-Carbohydrate Foods in Nursing Home Residents With Alzheimer's Disease: Associations Among Intervention Response, Body Mass Index, and Behavioral and Cognitive Function
Bibliographic record
Abstract
BACKGROUND: Despite recognition that weight loss is a problem in elderly persons with probable Alzheimer's disease (AD), increasing their food intake remains a challenge. To effectively enhance intake, interventions must work with individuals' changing needs and intake patterns. Previously, the authors reported greater food consumption at breakfast, a high-carbohydrate meal, compared with dinner, and shifts toward carbohydrate preference at dinner in those with increased behavioral difficulties, low body mass index, or both. METHODS: Thirty-four nursing home residents with probable AD who ate independently participated in a randomized, crossover, nonblinded study of two nutrition interventions. The intervention described here included replacing 12 nonconsecutive "traditional" dinners with meals high in carbohydrate but comparable to traditional dinners in protein. Measures included weighed food intake, body weight, cognitive function (as assessed using the Severe Impairment Battery and Global Deterioration Scale), behavioral disturbances (as assessed using the Neuropsychiatric Inventory-Nursing Home Version), and behavioral function (as assessed using the London Psychogeriatric Rating Scale). RESULTS: Group mean dinner and 24-hour energy intake increased during the intervention phase compared with baseline, protein intake was unaffected, and carbohydrate intake increased. Increased dinner intake, attributable to intervention foods, was achieved in 20 of 32 of participants who completed the study and was associated with increased carbohydrate preference, poorer memory, and increased aberrant motor behavior. Those with low body mass indices were the most resistant to the intervention. CONCLUSIONS: Providing a high-carbohydrate meal for dinner increases food intake in seniors at later stages of the disease who are experiencing cognitive and behavioral difficulties, possibly as a result of a shift in preference for high-carbohydrate foods.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".