Defining barriers to implementation of nutritional advice in patients with cachexia
Bibliographic record
Abstract
BACKGROUND: Cancer cachexia is a multidimensional wasting syndrome and a reduced dietary intake is both common and strongly correlated with degree of weight loss. Many patients with cachexia do not achieve recommended dietary intake even after nutritional counselling. Prior reports suggest this is likely due to barrier symptoms, but other potential contributory factors have not been studied in detail. METHODS: Dietitian-assigned barriers to successful nutritional intervention were recorded at each visit in all patients attending a multidisciplinary clinic for management of cancer cachexia. The barriers were grouped into 15 categories and classified as either symptom-related or not symptom-related. In addition, symptom scores, dietary intake, and weight change were recorded. RESULTS: Data on 94 new patients showed that 89% of patients had at least one major barrier. Four of the five most common barriers and 65% of all barriers identified were not symptom-related. Over sequential visits the specific barrier(s) in any one patient changed approximately 50% of the time. However, the presence of barriers did not render patients refractory to nutritional intervention and with intervention from the CNR-JGH team, mean dietary intake increased significantly. CONCLUSIONS: In advanced cancer patients with cachexia, non-symptom-related barriers to nutritional intervention are more common than symptom-related. Barriers are dynamic, and repeated careful evaluation over time is required to achieve optimal impact with nutritional intervention in cancer cachexia. Members of the multidisciplinary team need appropriate expertise to address the barriers identified and achieve optimal results with nutritional intervention.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".