Dietary intervention in older adults with early-stage Alzheimer Dementia: Early lessons learned
Bibliographic record
Abstract
In older adults, an adequate diet depends on their ability to procure and prepare food and eat independently or the availability of dietary assistance when needed. Inadequate food intake or increased nutritional requirements lead to poor nutritional status, which is considered a key determinant of morbidity, increased risk of infection, and mortality in elderly individuals. Weight loss among seniors also heralds increased morbidity and mortality. Dietary behaviour disorders affecting food consumption, nutrition status and maintenance of body weight are common in older adults, and have a substantial impact on nutritional status and quality of life among older adults with Alzheimer Dementia (AD). The Nutrition Intervention Study (NIS) is ongoing. It employs a quasi-experimental pre-post intervention design in physically-well, community-dwelling early stage AD patients aged 70 y or older. To date, 34 intervention group patients and 25 control group participants have been recruited with their primary caregivers (CG) from 6 hospital-based memory and geriatric clinics in Montreal. The NIS uses clinical dietetics principles to develop and offer tailored dietary strategies to patients and their CG. This paper reports on the application of dietary intervention strategies in two intervention group participants; one was deemed successful while the other was considered unsuccessful. The report documents challenges encountered in assessing and counselling this clientele, and seeks to explain the outcome of intervention in these patients.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".