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<p>Atrial fibrillation (AF) is the most common arrhythmia worldwide and is associated with significant morbidity and mortality. FibriCheck is a medical analysis platform that uses an end-to-end algorithm to detect AF based on photoplethysmography signals recorded on consumer smartphones. The study aimed to validate FibriCheck in a multicenter, multinational cohort of 236 subjects across ten popular smartphone devices. The 12-lead electrocardiogram was used as the reference diagnosis. FibriCheck demonstrated high overall performance: accuracy 98.5% (95% CI: 98.0–99.0%); sensitivity 96.3% (95% CI: 94.4–97.7%); specificity 99.3% (95% CI: 98.8–99.7%). Performance was not affected by smartphone device or comorbid heart failure, vascular disease, hypertension, diabetes, or stroke. Sensitivity was reduced in individuals with darker skin tones and higher BMIs, but this was mitigated by technician verification. The study confirms the high accuracy, sensitivity, and specificity of the FibriCheck algorithm in detecting AF across various smartphone models and clinical subgroups.</p>

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Fibricheck detection capabilities for atrial fibrillation (FDA–AF): a multicenter validation study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月20日

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  • John Sollee,
  • Baljash Cheema,
  • David Slotwiner,
  • Alexander Volodarskiy,
  • Lien Desteghe,
  • Christophe Buyck,
  • Hein Heidbuchel,
  • Stavros Stavrakis,
  • Laurent Pison,
  • Dieter Nuyens,
  • Maximo Rivero-Ayerza,
  • Hugo Van Herendael,
  • James Thomas

摘要

Atrial fibrillation (AF) is the most common arrhythmia worldwide and is associated with significant morbidity and mortality. FibriCheck is a medical analysis platform that uses an end-to-end algorithm to detect AF based on photoplethysmography signals recorded on consumer smartphones. The study aimed to validate FibriCheck in a multicenter, multinational cohort of 236 subjects across ten popular smartphone devices. The 12-lead electrocardiogram was used as the reference diagnosis. FibriCheck demonstrated high overall performance: accuracy 98.5% (95% CI: 98.0–99.0%); sensitivity 96.3% (95% CI: 94.4–97.7%); specificity 99.3% (95% CI: 98.8–99.7%). Performance was not affected by smartphone device or comorbid heart failure, vascular disease, hypertension, diabetes, or stroke. Sensitivity was reduced in individuals with darker skin tones and higher BMIs, but this was mitigated by technician verification. The study confirms the high accuracy, sensitivity, and specificity of the FibriCheck algorithm in detecting AF across various smartphone models and clinical subgroups.