Contribution of Cardiac and Extra-Cardiac Disease Burden to Risk of Cardiovascular Outcomes Varies by Ejection Fraction in Heart Failure
Bibliographic record
Abstract
AIMS: Patients with heart failure (HF) often have multiple co-morbidities that contribute to the risk of adverse cardiovascular (CV) and non-CV outcomes. We assessed the relative contribution of cardiac and extra-cardiac disease burden and demographic factors to CV outcomes in HF patients with reduced (HFrEF) or preserved (HFpEF) left ventricular ejection fraction (LVEF). METHODS AND RESULTS: We utilized data from the CHARM trial, which enrolled HF patients across the ejection fraction spectrum. We decomposed the previously validated MAGGIC risk score into cardiac (LVEF, New York Heart Association class, systolic blood pressure, time since HF diagnosis, HF medication use), extra-cardiac (body mass index, creatinine, diabetes mellitus, chronic obstructive pulmonary disease, smoker), and demographic (age, gender) categories, and calculated subscores for each patient representing the burden of each component. Cox proportional hazards models were used to estimate the population attributable risk (PAR) associated with each component to the outcomes of death, CV death, HF, myocardial infarction, and stroke relative to patients with the lowest risk score. PARs for each component were depicted across the spectrum of LVEF. in 2675 chronic HF patients from North America [HFrEF (LVEF ≤40%): n = 1589, HFpEF (LVEF >40%): n = 1086] with data available for calculation of the MAGGIC score, the highest risk of death and CV death was attributed to cardiac burden. This was especially evident in HFrEF patients (PAR: 76% cardiac disease vs. 58% extra-cardiac disease, P < 0.05). Conversely, in HFpEF patients, extra-cardiac burden accounted for a greater proportion of risk for death than cardiac burden (PAR: 15% cardiac disease vs. 49% extra-cardiac disease, P < 0.05). For HF hospitalization, the contribution of both cardiac and extra-cardiac burden was comparable in HFpEF patients (PAR: 42% cardiac disease vs. 53% extra-cardiac disease, P = NS). In addition, demographic burden was especially high in HFpEF patients, with 62% of deaths attributable to demographic characteristics. CONCLUSION: In North American HF patients enrolled in the CHARM trials, the relative contribution of cardiac and extra-cardiac disease burden to CV outcomes and death differed depending on LVEF. The high risk of events attributable to non-cardiac disease burden may help explain why cardiac disease-modifying medication proven to be efficacious in HFrEF patients has not proven beneficial in HFpEF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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".