Physical and emotional symptom burden of patients with end-stage heart failure: what to measure, how and why
Bibliographic record
Abstract
OBJECTIVE: Much of our understanding about symptom burden near the end of life is based on studies of cancer patients. The aim of this study was to explore physical and emotional symptom experience among end-stage chronic heart failure patients, looking for those symptoms mostly related to their global health status. METHODS: Forty-six patients with end-stage heart failure compiled the following: Edmonton Symptom Assessment Scale (ESAS) and Kansas City Cardiomyopathy Questionnaire (KCCQ). RESULTS: End-stage heart failure patients have many complaints and poor global health status. The most distressing symptoms reported were general discomfort and tiredness followed by anorexia and dyspnea. The KCCQ summary scores were highly correlated with ESAS (r = -0.78; P = 0.0001). Among the domains explored by the KCCQ, social functioning and self-efficacy showed the lowest correlation coefficients with ESAS (r = -0.50; P = 0.001 and r = -0.31; P = 0.003, respectively); concerning the physical limitation domain, the symptom score and the quality-of-life domain, the correlation coefficients were as follows: r = -0.71 (P = 0.0001), r = -0.75 (P = 0.0001) and r = -0.74 (P = 0.0001), respectively. In the multiple regression analysis of ESAS and KCCQ scores, general discomfort, depression and anxiety were the symptoms that mostly related with the results in the domains explored by the KCCQ. No independent predictor was found among symptoms and quality of life. CONCLUSION: General discomfort together with depression and anxiety were the symptoms that were mostly related with the physical limitation domain of global health status, but did not influence the social functioning and the self-efficacy domains. When ESAS is used together with KCCQ, comprehensive and quantitative information on a patient's physical, emotional and social distress is provided.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".