Consensus‐based nutrition care pathways for hospital‐to‐community transitions and older adults in primary and community care
Bibliographic record
Abstract
BACKGROUND: Practical guidance for providers on preventing, detecting, and treating malnutrition in primary care (PC) and the community is limited. The purpose of this study was to develop nutrition care pathways for adult patients (aged ≥18 years) transitioning from hospital to community and community-dwelling older adults (aged ≥65 years) who are at risk for malnutrition. METHODS: A review of best-practice nutrition evidence and guidelines published between 2009 and 2019 was performed using PubMed and CINAHL. Findings were summarized into two draft care pathways by the Primary Care Working Group of the Canadian Malnutrition Task Force. Diverse stakeholders (n = 21) reviewed and suggested revisions at a 1-day meeting. Revisions were made and an online survey was conducted to determine the relevance and importance of discrete care practices, and to establish consensus for which practices should be retained in the pathways. Providers (e.g., dietitians, physicians, nurses; n = 291) across healthcare settings completed the survey. Consensus on relevance and importance of practices was set at ≥80%. RESULTS: One hundred twenty-eight resources were identified and used to develop the draft pathways. Survey participants assigned ratings of ≥80% for relevance and importance for all nutrition care practices, except community service providers monitoring patient weight and appetite. CONCLUSION: These evidence- and consensus-based nutrition pathways offer guidance to healthcare and service providers on how to deliver nutrition care during hospital-to-community transitions for malnourished adult patients and community-dwelling older adults at risk for malnutrition. These pathways are flexible for diverse PC and community models.
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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 | 0.095 | 0.224 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".