Cross‐Sectional Nutrition Profile of Palliative Home Care Clients in Ontario and Performance of the interRAI Palliative Care Nutrition Clinical Assessment Protocol
Bibliographic record
Abstract
BACKGROUND: The nutrition profile of palliative home care clients is unknown. This study describes this group and their nutrition issues and evaluates the performance of the interRAI nutrition Clinical Assessment Protocol (CAP). METHODS: This was a cross-sectional secondary analysis using Ontario interRAI Palliative Care (interRAI PC) Assessment data. The sample represents 74,963 unique Ontario home care clients assessed between 2011 and 2018. Frequencies and standardized differences (stdiffs) of nutrition characteristics were presented for cancer (n = 62,394) and noncancer (n = 12,569) diagnostic subgroups. Rates of triggering the nutrition CAP were presented by nutrition issue to evaluate its performance. RESULTS: Of this sample, 16.7% were ≥85 years of age, 52.6% had a prognosis between 6 weeks and 6 months, and 41.4% required assistance with eating. The prevalence was higher among those with nervous/mental/behavioral disorders (72.6%) compared with those with cancer (37.6%; stdiff = 0.75). However, most nutrition issues experienced were similar (stdiff < 0.20) across diagnostic groups. Of the entire sample, 21% triggered the nutrition CAP, indicating a need for further evaluation or intervention. Yet, 73.4% of those who experienced dry mouth, 71.8% of those who required assistance with eating, and 68.4% of those who received a nutrition consult within the last 3 days did not trigger the nutrition CAP. CONCLUSIONS: Nutrition issues are prevalent in palliative home care clients, regardless of diagnosis; yet the nutrition CAP identified a small fraction of this group. There is a need to focus research and care guidelines toward life-limiting illnesses beyond cancer and address nutrition-related issues in this population.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".