Novel, Family‐Centered Intervention to Improve Nutrition in Patients Recovering From Critical Illness: A Feasibility Study
Bibliographic record
Abstract
BACKGROUND: Critically ill patients are at increased risk of developing malnutrition-related complications because of physiological changes, suboptimal delivery, and reduced intake. Strategies to improve nutrition during critical illness recovery are required to prevent iatrogenic underfeeding and risk of malnutrition. The purpose of this study was to assess the feasibility and acceptability of a novel family-centered intervention to improve nutrition in critically ill patients. MATERIALS AND METHODS: A 3-phase, prospective cohort feasibility study was conducted in 4 intensive care units (ICUs) across 2 countries. Intervention feasibility was determined by patient eligibility, recruitment, and retention rates. The acceptability of the intervention was assessed by participant perspectives collected through surveys. Participants included family members of the critically ill patients and ICU and ward healthcare professionals (HCPs). RESULTS: A total of 75 patients and family members, as well as 56 HCPs, were enrolled. The consent rate was 66.4%, and 63 of 75 (84%) of family participants completed the study. Most family members (53/55; 98.1%) would recommend the nutrition education program to others and reported improved ability to ask questions about nutrition (16/20; 80.0%). Family members viewed nutrition care more positively in the ICU. HCPs agreed that families should partner with HCPs to achieve optimal nutrition in the ICU and the wards. Health literacy was identified as a potential barrier to family participation. CONCLUSION: The intervention was feasible and acceptable to families of critically ill patients and HCPs. Further research to evaluate intervention impact on nutrition intake and patient-centered outcomes is required.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".