Predicting Heart Failure Outcomes With Biomarkers and Imaging

Background and Rationale:

Accurate prognosis in heart failure (HF) remains challenging due to phenotypic heterogeneity across the spectrum of left ventricular ejection fraction (LVEF). While biomarkers like N-terminal pro-B-type natriuretic peptide (NT-proBNP) and imaging parameters like LVEF are standard prognostic tools, each has limitations. Emerging imaging parameters, such as epicardial adipose tissue (EAT) density (reflecting fat inflammation/fibrosis) and left ventricular global longitudinal strain (LVGLS), offer potential incremental prognostic value but are not yet integrated into routine clinical models. This study aims to systematically evaluate whether a multi-parameter model combining established blood biomarkers and advanced imaging metrics improves the prognostic stratification of patients with HFrEF, HFmrEF, and HFpEF compared to traditional approaches.

Detailed Methodology:

This is a single-center, retrospective cohort study. The study population consists of consecutive adult patients (≥18 years) with a confirmed diagnosis of chronic HF who had both qualifying blood biomarker assessment (NT-proBNP and/or high-sensitivity cardiac troponin) and cardiac imaging (transthoracic echocardiography and/or cardiac computed tomography) performed within a ±3-month window around an index encounter between January 1, 2012, and December 31, 2024, at Xinjiang Medical University First Affiliated Hospital.

Key data to be extracted from electronic health records include: 1) Clinical variables: demographics, comorbidities (e.g., ischemic etiology, diabetes, hypertension), medications, and NYHA class; 2) Blood biomarkers: NT-proBNP, hs-cTnT/I, hs-CRP, and renal function (eGFR); 3) Imaging parameters: LVEF, LVGLS, left atrial volume index (LAVI), E/e' ratio, and EAT volume/density (from CT, if available).

The primary endpoint is all-cause mortality at one year from the index date. Follow-up data will be obtained from hospital records.

Statistical Analysis Plan:

The incremental prognostic value will be assessed by constructing and comparing nested Cox proportional hazards models:

Model 1 (Base Clinical): Includes age, sex, BMI, ischemic etiology, diabetes, and hypertension.

Model 2 (Biomarker-Enhanced): Model 1 + NT-proBNP + eGFR. Model 3 (Imaging-Enhanced): Model 2 + key imaging parameters (e.g., EAT density or LVGLS).

Model performance will be compared using Harrell's C-statistic, the Akaike Information Criterion (AIC), Net Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI). Pre-specified subgroup analyses will be conducted for HFrEF, HFmrEF, and HFpEF phenotypes. Multiple imputation will be used for variables with low rates of missing data (<10%).

Inclusion criteria

• Age ≥ 18 years.
• Confirmed diagnosis of chronic heart failure.
• Treated at the study center between January 1, 2012, and December 31, 2024.
• Availability of both qualifying blood biomarker test results (NT-proBNP and/or high-sensitivity cardiac troponin) and cardiac imaging (echocardiography and/or cardiac CT) performed within a ±3-month window around the index encounter.

Exclusion criteria

• Heart failure primarily due to severe primary valvular disease, acute myocardial infarction, myocarditis, or pulmonary embolism.
• End-stage renal disease requiring dialysis.
• Clinical records or follow-up data are severely incomplete, precluding outcome assessment.