Kiki Jae Estes-Schmalzl, Mitchell Wolden, KRISTIN M. LEFEBVRE
Journal of Clinical Practice and Research - 2025;47(5):462-471
This systematic review demonstrates substantial diagnostic discordance between the H2FPEF and HFA-PEFF algorithms, with discordance rates ranging from 28% to 41% across diverse study populations. These findings support prior observations that the two scoring systems frequently yield inconsistent classifications when applied to the same patient cohort. This variability complicates clinical decision-making, especially in borderline or intermediate-probability cases, and raises concerns about the consistency and generalizability of diagnostic outcomes. The observed discordance appears rooted in fundamental algorithmic design differences that reflect distinct diagnostic philosophies. The H2FPEF algorithm prioritizes readily available clinical parameters, making it more applicable in primary care settings but potentially susceptible to confounding by comorbidities. In contrast, the HFA-PEFF algorithm's hierarchical structure demands advanced cardiac imaging and biomarker testing, creating diagnostic gaps in resource-limited environments. Our findings also underscore the persistent omission of social determinants of health in current diagnostic paradigms. None of the reviewed studies incorporated SDoH variables, despite robust evidence linking factors such as socioeconomic status, race and ethnicity, health literacy, and geographic access to care with HFpEF prevalence, diagnostic delay, and clinical outcomes. Artificial intelligence, particularly explainable models, offers concrete solutions to address these shortcomings. Future research should prioritize the development of integrated diagnostic frameworks that combine the clinical utility of existing algorithms with comprehensive SDoH assessment.
