Patient-reported outcomes at hospital discharge among patients with arrhythmia: Results from the national DenHeart survey
Bibliographic record
Abstract
BACKGROUND: Patient-reported outcomes are important predictors of mortality, cardiovascular events and hospitalisation in patients with cardiac diseases, but differences in patient-reported outcomes between groups of patients with arrhythmia have not yet been investigated. AIMS: To describe and compare patient-reported outcomes at discharge among patients with different types of cardiac arrhythmia and to examine the associations between demographic characteristics, inhospital factors and patient-reported outcomes. METHODS: Data were derived from the national DenHeart study including patient-reported outcomes from the following questionnaires: the hospital anxiety and depression scale (HADS), HeartQoL, short form 12 (SF-12), current health status (EQ-5D), brief illness perception questionnaire (B-IPQ) and the Edmonton symptom assessment scale (ESAS). Clinical and demographic data were obtained from national registers. Multiple linear and logistic regression models were used to investigate the associations between the potential risk factors and the patient-reported outcomes. RESULTS: A total of 4251 patients diagnosed with arrhythmia completed the questionnaire. Across the arrhythmia subgroups, some differences were observed. In general, patient-reported outcome scores were worst among patients with 'ventricular arrhythmia' (e.g. highest depression scores and highest prevalence of feeling unsafe at discharge). Regression analysis revealed that longer hospital stay, female gender, being unmarried and having a short education were significantly associated with poor health for almost all arrhythmia subgroups. CONCLUSION: Differences exist in self-reported health, quality of life and symptom burden across arrhythmia groups with patients with ventricular arrhythmia reporting poorer patient-reported outcomes. Longer hospital stay, female gender, being unmarried and having a low level of education were significantly associated with worse outcomes among the total population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".