Prognostic value of symptom burden as a simple patient-reported outcome measure in older patients with heart failure
Bibliographic record
Abstract
This study was performed to investigate the prognostic value of assessing symptom burden using the Edmonton Symptom Assessment System (ESAS) in older patients with Heart Failure (HF). This prospective cohort study was performed in consecutive patients ≥ 60 years old hospitalized with HF at a university hospital between September 2020 and June 2023. ESAS was used to assess nine common symptoms at hospital discharge (total score: 0-90) with higher scores indicating greater severity. The primary outcome was the combined event of HF readmission and all-cause mortality within 6 months. The median ESAS sum score in the study population consisting of 306 patients (median age, 79 years; 54.9% male) was 13 points. The commonly reported moderate-to-severe symptoms were impaired well-being (34.9%), anxiety (27.5%), drowsiness (25.8%), tiredness (24.9%), and depression (22.2%). In multivariate analyses, ESAS sum score was significantly associated with the combined event (adjusted hazard ratio for each 5-point increase, 1.10 (95% confidence interval: 1.04-1.17; p < 0.001). Inclusion of ESAS sum score in the risk model significantly increased both continuous net reclassification improvement (p = 0.028) and integrated discrimination improvement (p = 0.002) for the primary outcome. Comprehensive assessment of symptom burden with ESAS provided additional prognostic information to conventional risk factors in older patients with HF.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".