Abstract 17602: Cardiac Structure and Function and Renal Outcomes in Patients With Heart Failure With Preserved Ejection Fraction: Insights From the PARAGON-HF Trial
Bibliographic record
Abstract
Introduction: Chronic kidney disease is common and associated with a worse prognosis in patients with heart failure (HF). However, the association of cardiac structure and function with renal outcomes in patients with HF with preserved ejection fraction (HFpEF) is not known. Goal: Identify cardiac structural and functional correlates of renal outcomes in HFpEF. Methods: Patients enrolled in the echocardiographic sub-study of the PARAGON-HF trial were included. The endpoint of interest was a composite renal endpoint: a ≥50% decline in estimated glomerular filtration rate (eGFR) relative to baseline, development of end-stage renal disease, or death attributable to renal causes. Multivariable Cox proportional hazards models were used to identify measures of cardiac structural and functional parameters associated with the composite renal endpoint, adjusting for baseline eGFR, systolic blood pressure, NT-proBNP, treatment arm (sacubitril-valsartan or valsartan) and diabetes. Results: In 1,097 patients (53% women, mean age 74±8 years), over a median follow-up of 2.9 years (IQR 2.6-3.4 years) there were 28 composite renal events (0.9 per 100 patient-years). After multivariable adjustment, higher left ventricular (LV) posterior wall thickness and mass index, right ventricular (RV) end-diastolic and end-systolic areas as well as impaired RV function (lower fractional area change and lower absolute RV free wall longitudinal strain), but not LV systolic function (LVEF and global longitudinal strain) were each associated with a significantly higher risk for the composite renal endpoint ( Figure ). Conclusions: In the PARAGON-HF echocardiographic sub-study, evidence of cardiac biventricular remodeling and deterioration of RV function were associated with an increased risk of renal events. These results underscore the close relationship between the heart and kidneys in patients with HF even when LVEF is preserved.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".