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Cross-sectional study reveals significant sex-specific differences in comorbidities and medication patterns among patients with heart failure, highlighting distinct cardiovascular profiles.
Background: Heart failure (HF) is associated with substantial morbidity and frequently occurs alongside multiple comorbidities, contributing to complex medication use. This study aimed to describe the clinical characteristics, comorbidities, laboratory findings, and medication use among patients with HF in Saudi Arabia, focusing on sex differences. Methods: A retrospective cross-sectional study was conducted among adults with heart failure at King Abdul-Aziz Medical City, Saudi Arabia. Data from electronic medical records (2016–2018) were analyzed for demographic, clinical, laboratory, comorbidity, and medication characteristics. Differences between male and female patients were assessed using appropriate statistical tests, with odds ratios and 95% confidence intervals calculated for selected variables. Statistical significance was set at p < 0.05. Results: Among 1363 patients, 669 (49.1%) were male and 694 (50.9%) female. Females had higher BMI (34.64 ± 7.99 vs. 28.99 ± 6.91 kg/m2, p < 0.001), hypertension (50.7% vs. 41.4%; p < 0.001), diabetes (47.4% vs. 40.7%; p = 0.012), and atrial fibrillation (29.7% vs. 20.0%; p < 0.001). Males had higher smoking prevalence (60.4% vs. 3.3%; p < 0.001), ischaemic heart disease (43.6% vs. 27.1%; OR 2.08, 95% CI 1.66–2.61; p < 0.001), creatinine (p < 0.001), and BNP (p = 0.004). Beta-blocker and ACE inhibitor use was higher among males, whereas ARB use was higher among females (all p < 0.05). Conclusions: In this study, patients with heart failure had a high burden of cardiovascular and cardiometabolic comorbidities, with notable sex-related differences in clinical characteristics, comorbidities, laboratory measures, and medication use. These findings provide real-world evidence on HF profiles and medication use in a Saudi tertiary-care setting and highlight the need for multicenter studies to characterize these patterns across diverse populations.
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Alshahrani et al. (2026) studied this question.
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