Patient-reported health and 1-year mortality in patients with ischemic heart disease – findings from the Denheart study
Bibliographic record
Abstract
Abstract Background Though survival has improved markedly in ischemic heart disease (IHD), it remains a leading cause of death worldwide. Screening tools to identify patients at risk are ever in demand. Large-scale studies exploring the association between patients' self-reported mental and physical health and mortality are lacking. Purpose (i) to describe patient-reported outcomes (PROs) at discharge in IHD patients deceased and alive at one year, (ii) to investigate the discriminant predictive performance of PRO instruments on mortality, (iii) to investigate differences in time to death among survey responders/non-responders and among three diagnostic sub-groups (chronic ischemic heart disease/stable angina, non-STEMI/unstable angina and STEMI), and (iv) to investigate predictors of one-year mortality among sociodemographic, clinical and self-reported factors. Methods Data from the national DenHeart survey with register-data linkage was used. A total of 14,115 adults with IHD were discharged during one year. Eligible (n=13,476) were invited to complete a questionnaire and 7,167 (53%) responded. Questionnaires included the Health survey short form 12-items (SF-12), Hospital Anxiety and Depression Scale (HADS), EuroQoL-5-dimensions (EQ-5D), HeartQoL, Edmonton Symptom Assessment Scale (ESAS) and ancillary questions. Clinical and demographic characteristics were obtained from registries as were data on one-year mortality. Comparative analyses investigated differences in PROs, and discriminant PRO-performance was explored by Receiver Operating Characteristics (ROC) curves. Kaplan-Meier survival analysis explored differences in time to death across sub-groups. Predictors of mortality were explored using multifactorially adjusted cox regression analyses with time to death as underlying timescale. Results Highly significant and clinically important differences in PROs were found between those alive and those deceased at one year. The best discriminant performance was observed for the physical component scale of the SF-12 (Area Under the Curve (AUC) 0.706) (Figure 1). One-year mortality among responders and non-responders was 2% and 7%, respectively. Significant differences in time to death was observed between responders and non-responders (p<0.001) and among diagnostic subgroups (p<0.001). Strongest predictors of one-year mortality included STEMI (hazard ratio (HR) 2.9 95% confidence interval (CI) 2.3–3.7), Tu comorbidity index score 3+ (HR 3.6, 95% CI 2.7–4.8) and patient-reported feeling unsafe about returning home from hospital (HR 2.07, 95% CI 1.2–3.61). Conclusions One-year post-discharge mortality was expectedly low, however notably higher in certain subgroups. Though clinical predictors may be difficult to modify, factors such as feeling unsafe about returning home should be addressed at discharge. PRO-performance estimates may guide clinicians and researchers in choosing appropriate predictive patient-reported outcome tools. Figure 1. PRO instruments ROC curves Funding Acknowledgement Type of funding source: None
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".