2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS)
The Task Force for the diagnosis and management of atrial fibrillation of the European Society of Cardiology (ESC) Developed with the special contribution of the European Heart Rhythm Association (EHRA) of the ESC Authors/Task Force Members: Gerhard Hindricks* (Chairperson) (Germany), Tatjana Potpara* (Chairperson) (Serbia), Nikolaos Dagres (Germany), Elena Arbelo (Spain), Jeroen J. Bax (Netherlands), Carina Blomstro¨m-Lundqvist (Sweden),
Giuseppe Boriani (Italy), Manuel Castella1 (Spain), Gheorghe-Andrei Dan(Romania), Polychronis E. Dilaveris (Greece), Laurent Fauchier (France),Gerasimos Filippatos (Greece), Jonathan M. Kalman (Australia), Mark La Meir1(Belgium), Deirdre A. Lane (United Kingdom), Jean-Pierre Lebeau (France),
7 Screening for atrial fibrillation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 392
7.1 Screening tools . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . 392
7.2 Screening types and strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . 394
7.3 Benefits from and risks of screening for atrial fibrillation .. . . . . 394
7.4 Cost-effectiveness of screening for atrial fibrillation . . .. . . . . . . . 394
7.5 Screening in high-risk populations . . . . . . . . . . . . . . . . . . . . . . . . . 395
7.1 Screening tools The systems used for AF screening are shown in Table 5 and
Figure 6. 173,187
Mobile health technologies are rapidly developing for AF detection and other purposes (>100 000 mHealth apps and >_400 wearable activity monitors are currently available).197 Caution is needed in their clinical use, as many are not clinically validated. Several studies evaluated AF detection using smartwatches,198,199 thus opening new perspectives for AF detection targeting specific populations at risk. Machine learning and artificial intelligence may be capable of identifying individuals with previous AF episodes from a sinus rhythm ECG recording,200 which would be a major technological breakthrough in AF detection.200 The Apple Heart study201 included 419 297 self-enrolled smartwatch app users (mean age 40 years) in the United States of America (USA), of whom 0.5% received an irregular pulse notification (0.15% of those aged <40 years, 3.2% among those aged >65 years). Subsequent (notification-triggered) 1-week ECG patch monitoring revealed AF in 34% of monitored participants. The Huawei Heart study202 included 187 912 individuals (mean age 35 years, 86.7% male), of whom 0.23% received a 『suspected AF』 notification. Of those effectively followed up, 87.0% were confirmed as having AF, with the positive predictive value of photoplethysmography signals being 91.6% [95% confidence interval (CI) 91.5 - 91.8]. Of those with identified AF, 95.1% entered an integrated AF management programme using a mobile AF App (mAFA). When AF is detected by a screening tool, including mobile or wearable devices, a single-lead ECG tracing of >_30 s or 12-lead ECG showing AF analysed by a physician with expertise in ECG rhythm interpretation is necessary to establish a definitive diagnosis of AF (devices capable of ECG recording enable direct analysis of the device-provided tracings). When AF detection is not based on an ECG recording (e.g. with devices using photoplethysmography) or in case of uncertainty in the interpretation of device-provided ECG
tracing, a confirmatory ECG diagnosis has to be obtained using additional ECG recording (e.g. 12-lead ECG, Holter monitoring, etc.)
Figure 6 Systems used for AF screening. Pulse palpation, automated BP monitors, single-lead ECG devices, PPG devices, other sensors (using seismocardiography, accelerometers, and gyroscopes, etc.) used in applications for smartphones, wrist bands, and watches. Intermittent smartwatch detection of AFis possible through PPG or ECG recordings. Smartwatches and other 『wearables』 can passively measure pulse rate from the wrist using an optical sensorfor PPG and alerting the consumer of a pulse irregularity (based on a specific algorithm for AF detection analysing pulse irregularity and variability).172,173,188196 AF = atrial fibrillation; BP = blood pressure; ECG = electrocardiogram; PPG = photoplethysmography
7.4 Cost-effectiveness of screening foratrial fibrillationHigher AF-related medical costs justify strategies to identify andtreat undiagnosed AF.219 Opportunistic AF screening is associatedwith lower costs than systematic screening.173 Appropriate choiceof the screening tool and setting is important,220 and a favourablecost-effectiveness profile has been estimated for screening programmes based on pulse palpation, hand-held ECG devices, andTable 5 Sensitivity and specificity of various AF screening tools considering the 12-lead ECG as the gold standard173Sensitivity SpecificityPulse taking203 87 - 97% 70 - 81%Automated BP monitors204207 93 - 100% 86 - 92%Single lead ECG208211 94 - 98% 76 - 95%Smartphone apps188,189,191,195,212,213 91.5 - 98.5% 91.4 - 100%Watches196,198,213,214 97 - 99% 83 - 94%AF = atrial fibrillation; BP = blood pressure; ECG = electrocardiogram.©ESC 2020Figure 7 Potential benefits from and risks of screening for AF. AF = atrial fibrillation; ECG = electrocardiogram; OAC = oral anticoagulant; SE =systemicembolism.394 ESC GuidelinesDownloaded from https://academic.oup.com/eurheartj/article/42/5/373/5899003 by guest on 12 February 2021.. smartphones with pulse photoplethysmography algorithms.172Both systematic and opportunistic screening are more costeffective than routine practice for patients >_65 years, with opportunistic screening more likely to be cost-effective than systematicpopulation screening.1491
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