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H. Morita

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Aug 2026

Association of HFA-PEFF Score with Left Atrial Mechanics, Pressure and Reverse Remodeling in Atrial Fibrillation.

BACKGROUND Diagnosis of heart failure with preserved left ventricular ejection fraction (HFpEF) remains a significant clinical challenge, particularly in patients with atrial fibrillation (AF). Recently, the HFA-PEFF score was introduced to aid in the diagnostic work-up of HFpEF. This study aimed to investigate the distribution of the HFA-PEFF score and its relationship with left atrial (LA) function, pressure, and reverse remodeling in patients with AF. METHODS We investigated 155 AF patients who underwent their first catheter ablation (CA). Echocardiography was performed before CA, and the HFA-PEFF score was calculated. Direct LA pressure (LAP) was measured at CA. Echocardiography was repeated 6 months after CA to evaluate LA reverse remodeling. RESULTS High (5-6), intermediate (2-4) and low (0-1) HFA-PEFF scores were observed in 19 (12.3%), 99 (63.9%) and 37 (23.9%) patients, respectively. Higher HFA-PEFF scores were associated with worse LA function and LA stiffness (both P<0.05). Elevated LAP was detected in 31.6%, 19.2%, and 5.4% of the high, intermediate, and low HFA-PEFF score groups, respectively. In the intermediate HFA-PEFF score group, LA stiffness was a good predictor of elevated LAP, whereas left ventricular global longitudinal strain was more predictive in the high HFA-PEFF score group. Six months after CA, all groups exhibited LA reverse remodeling, while the high-score group retained larger LA size and worse LA function. CONCLUSIONS Higher HFA-PEFF scores were associated with advanced LA functional remodeling and elevated LAP in AF patients. Persistent LA remodeling after CA in the high-score group demonstrates the need for careful follow-up.

Satoshi Konoma, K. Nakanishi, M. Daimon et al. · 0 citations
Open access Jul 2026

Comprehensive Echocardiography Interpretation Using Video and Multiview Vision-Language AI.

A multiview video-language framework improved report retrieval compared with conventional image-based approaches and support the utility of video-based, multiview representation learning for echocardiographic report retrieval.

R. Takizawa, Chiemi Yamazaki, S. Kodera et al. · 0 citations

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