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Gregory Υ. Η. Lip

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Open access Aug 2026

Integrated management of atrial fibrillation with digital health support: a pooled analysis of individual participant data from the mAFA-II and MIRACLE-AF trials.

AIMS Adherence with a holistic or integrated care management of atrial fibrillation (AF) based on the AF better care (ABC) pathway has been associated with improved clinical outcomes. Two prospective randomized trials (mAFA and MIRACLE-AF) have evaluated this approach. The multicentre mAFA-II trial delivered the ABC pa...

Gregory Υ. Η. Lip, Yang Chen, Ming-Fang Li et al. · 0 citations
Open access Aug 2026

Sex and Age Differences in Outcomes After Endovascular Thrombectomy of Patients With Acute Ischemic Stroke and Atrial Fibrillation: A Danish Nationwide Study.

Women with AF had higher odds of good functional outcome and men with AF showed higher successful reperfusion rates with advancing age, suggesting age-and sex-specific influences on EVT outcomes associated with AF.

M. Alobaida, D. Lane, J. N. Hedegaard et al. · 0 citations
Open access Jul 2026

Frailty may confound the association between MASLD and cardiovascular mortality in people with cardiometabolic risk factors.

BACKGROUND While metabolic dysfunction-associated steatotic liver disease (MASLD) has been consistently associated with increased cardiovascular risk in the general population, its association with cardiovascular disease (CVD) mortality in adults with established cardiometabolic risk factor (including obesity, hyperten...

Ruoting Wang, Wenli Li, J. Lazarus et al. · 0 citations
Open access Jul 2026

Atrial fibrillation in patients with left ventricular non-compaction: incidence and associations with stroke, heart failure, and mortality.

In this observational cohort, LVNC was associated with a high incidence of AF, and the presence of AF was associated with higher risks of stroke, heart failure, and all-cause death.

A. Askarinejad, T. Lüscher, Gregory Υ. Η. Lip · 1 citation
Open access Jul 2026

Risk-Guided Screening for Atrial Fibrillation Using Electronic Health Records

The EHR-based machine learning model, FIND-AF 2.0, identifies a high-risk subpopulation for AF diagnosis among patients at elevated risk of stroke and could enable scalable, EHR-driven, risk-guided AF screening.

R. Nadarajah, Jianhua Wu, A. Wahab et al. · 0 citations

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