Clinical and Economic Impact in Dysphagia Management: A Preliminary Economic Evaluation for the WeanCare-Dysphameal Approach
Bibliographic record
Abstract
Background/Objectives: Oropharyngeal dysphagia (OD) is a frequent condition among older adults in long-term care facilities, often leading to malnutrition, dehydration, and increased mortality. Modified-texture diets (MTDs) are used to address these risks, though traditional preparation methods often compromise nutritional density and standardization. The WeanCare protocol with Dysphameal® technology introduces an innovative solution by offering IDDSI-compliant, high-density, freeze-dried meals. This study assesses its clinical effectiveness and economic impact. Methods: A six-month quasi-experimental pre–post study was conducted in two Italian nursing homes involving 13 older participants with diagnosed OD. Participants received all meals and hydration through Dysphameal®, and data were collected on anthropometry, biochemical markers, care workload, and economic parameters. Statistical analyses included regression, correlations, and pre–post comparisons. Results: Improvements were noted in fat-free mass (FFM), skeletal muscle mass (ASMM), and basal metabolic rate (BMR) in all participants. Albumin and lymphocyte counts improved, as did participant autonomy at mealtime. Operational time per participant dropped by 44% in kitchen and by 7 min/day in wards. Supplement use decreased, leading to significant cost savings and improved staff allocation. Conclusions: The WeanCare–Dysphameal® system improves nutritional status, reduces caregiver workload, and enhances economic efficiency in institutional settings. It represents a scalable solution for OD management, ensuring consistency, safety, and sustainability in dysphagic care.
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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 | 0.015 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".