Real-world performance of the atrial fibrillation monitor in patients with a subcutaneous ICD

Autor: Deepa Mahajan, Dave Perschbacher, Amy Jean Brisben, Sarah W.E. Baalman, Joris R. de Groot, Suneet Mittal, Lucas V.A. Boersma, Reinoud E. Knops
Přispěvatelé: Cardiology, Graduate School, ACS - Heart failure & arrhythmias, Amsterdam Cardiovascular Sciences
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Adult
Male
medicine.medical_specialty
030204 cardiovascular system & hematology
Sensitivity and Specificity
Intracardiac injection
S‐ICD
Electrocardiography
03 medical and health sciences
0302 clinical medicine
S-ICD
Heart Rate
Subcutaneous Icd
Internal medicine
Heart rate
Devices
Humans
Medicine
Ventricular ectopy
In patient
atrial fibrillation
030212 general & internal medicine
Lead (electronics)
subclinical atrial fibrillation
remote monitoring
Aged
algorithm
business.industry
Atomic force microscopy
Atrial fibrillation
General Medicine
Middle Aged
medicine.disease
Predictive value
Defibrillators
Implantable
subcutaneous implantable cardioverter-defibrillator
subcutaneous implantable cardioverter‐defibrillator
Cardiology
Female
Cardiology and Cardiovascular Medicine
business
Algorithms
Zdroj: Pacing and clinical electrophysiology, 43(12), 1467-1475. Wiley-Blackwell
Pacing and Clinical Electrophysiology
ISSN: 0147-8389
Popis: Introduction The third‐generation subcutaneous implantable cardioverter‐defibrillator (S‐ICD) (EMBLEM™ A219, Boston Scientific) contains a new diagnostic tool to detect atrial fibrillation (AF) in S‐ICD patients, without the use of an intracardiac lead. This is the first study to evaluate the performance of the S‐ICD AF monitor (AFM). Methods The AFM algorithm analyzes a subcutaneous signal for the presence of AF, similar to the signals collected by implantable and wearable diagnostic devices. The AFM algorithm combines heart rate (HR) scatter analysis with an HR histogram. The algorithm was tested against publicly available electrocardiogram databases (simulated performance). Real‐world performance of the algorithm was evaluated by using the S‐ICD LATITUDE remote monitoring (RM) database. Results The simulated performance of the AFM algorithm resulted in a sensitivity of 95.0%, specificity of 100.0%, and positive predictive value (PPV) of 100.0%. To evaluate the real‐world performance of the AFM, 7744 S‐ICD devices were followed for up to 30 months by RM, whereof 99.5% had the AFM enabled. A total of 387 AF episodes were randomly chosen for adjudication, resulting in a PPV of 67.7%. The main cause of misclassification was atrial and ventricular ectopy. Conclusion The AFM exhibited a very high sensitivity and specificity in a simulated setting, designed to maximize PPV in order to minimize the clinical burden of reviewing falsely detected AF events. The real‐world performance of the AFM, enabled in 99.5% of S‐ICD patients, is a PPV of 67.7%.
Databáze: OpenAIRE
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