Heart Failure With Preserved Ejection Fraction and Its Cardiac MR Characteristics of Different Subtypes

Using cardiac magnetic resonance imaging technology, the ejection fraction of heart failure (HFpEF) and different subtypes of cardiac magnetic resonance characteristics, and combined with the clinical characteristics and prognosis of the patient, explore the value of cardiac magnetic resonance in disease diagnosis, classification, treatment and prognosis, and provide new ideas for clinical practice.

1. Study Objectives To compare clinical characteristics among HFpEF patients with different comorbidity subtypes (hypertension, type 2 diabetes, renal insufficiency, obesity). To identify distinct cardiac magnetic resonance (CMR) features associated with HFpEF and its comorbidity subtypes. To evaluate prognostic differences (mortality, heart failure readmission, healthcare costs) across HFpEF subtypes. 2. Study Design Type: Single-center, prospective, observational cohort study. Duration: April 1, 2023 - December 31, 2026. Sample Size: 500 HFpEF patients, with \~200 patients per subgroup. 3. Data Collection Framework Baseline Data: Clinical Parameters: Demographics (age, gender, BMI). Comorbidities (hypertension, diabetes, renal function). Biochemical markers (BNP/NT-proBNP, HbA1c, lipid profile, renal function). Medications (ACE inhibitors, beta-blockers, diuretics). Imaging Data: Echocardiography: Left ventricular ejection fraction (LVEF ≥50%). CMR: Ventricular volumes, mass, strain analysis, T1 mapping, and late gadolinium enhancement (LGE). Follow-Up Protocol: Frequency: Every 6 months post-discharge. Endpoints: Primary: Cardiovascular mortality, HF-related readmission. Secondary: Changes in CMR parameters, medication adjustments, healthcare utilization. 4. Subgroup Classification Comorbidity Subgroups: HFpEF + Hypertension. HFpEF + Type 2 Diabetes. HFpEF + Renal Insufficiency. HFpEF + Obesity. Control Group: HFpEF patients without the above comorbidities. 5. CMR Protocol Imaging Sequences: Cine imaging for ventricular function. T1 mapping for myocardial fibrosis assessment. LGE for scar detection. Post-Processing: Analysis of myocardial strain, extracellular volume (ECV), and perfusion reserve. 6. Statistical Analysis Methods: Regression analysis for associations between CMR features and clinical outcomes. Survival analysis (Kaplan-Meier, Cox proportional hazards models). Subgroup comparisons using ANOVA or non-parametric tests. Software: SPSS 20.0 (significance threshold: p \<0.05). 7. Ethical and Data Management Privacy Protection: De-identified data storage with restricted access. Data Validation: Double-entry verification for 10% of randomly selected cases. Compliance: Adherence to institutional review board (IRB) guidelines and GCP standards.