scholarly journals Early Detection of Pacing Failure by Home Monitoring: A Case Report of Paroxysmal Atrial Fibrillation

2011 ◽  
Vol 27 (Supplement) ◽  
pp. PJ2_023
Author(s):  
Kenji Kawamoto ◽  
Takashi Fujiwara ◽  
Shinpei Fujita ◽  
Hideyuki Suzuki ◽  
Tsuyoshi Miyaji ◽  
...  
2021 ◽  
Author(s):  
Daisuke Hiraoka ◽  
Tomohiko Inui ◽  
Eiryo Kawakami ◽  
Megumi Oya ◽  
Ayumu Tsuji ◽  
...  

BACKGROUND Some attempts have been made to detect atrial fibrillation with a wearable device equipped with photoelectric volumetric pulse wave technology, and it is expected to be applied under real clinical conditions. OBJECTIVE This study is the second part of a two-phase study aimed at developing a method for immediate detection of paroxysmal atrial fibrillation (AF) using a wearable device with built-in PPG. The objective of this study is to develop an algorithm to immediately diagnose atrial fibrillation by wearing an Apple Watch equipped with a photoplethysmography (PPG) sensor on patients undergoing cardiac surgery and using machine learning of the pulse data output from the device. METHODS A total of 80 subjects who underwent cardiac surgery at a single institution between June 2020 and March 2021 were monitored for postoperative atrial fibrillation using telemetry monitored ECG and Apple Watch. Atrial fibrillation was diagnosed by qualified physicians from telemetry-monitored ECGs and 12-lead ECGs; a diagnostic algorithm was developed using machine learning on pulse rate data output from the Apple Watch. RESULTS One of the 80 patients was excluded from the analysis due to redness of the Apple Watch wearer. 27 (34.2%) of the 79 patients developed AF, and 199 events of AF, including brief AF, were observed. 18 events of AF lasting longer than 1 hour were observed, and Cross-correlation analysis (CCF) showed that pulse rate measured by Apple Watch was strongly correlated (CCF 0.6-0.8) with 8 events and very strongly correlated (CCF >0.8) with 3 events. The diagnostic accuracy by machine learning was 0.7952 (sensitivity 0.6312, specificity 0.8605 at the point closest to the top-left) for the AUC of the ROC curve. CONCLUSIONS We were able to safely monitor pulse rate in patients after cardiac surgery by wearing an Apple Watch. Although the pulse rate from the PPG sensor does not follow the heart rate of the telemetry monitoring ECG in some parts, which may reduce the accuracy of the diagnosis of atrial fibrillation by machine learning, we have shown the possibility of clinical application of early detection of atrial fibrillation using only the pulse rate collected by the PPG sensor. CLINICALTRIAL The use of wristband type continuous pulse measurement device with artificial intelligence for early detection of paroxysmal atrial fibrillation Clinical Research Protocol No. jRCTs032200032 https://jrct.niph.go.jp/latest-detail/jRCTs032200032


2014 ◽  
Vol 9 (9-10) ◽  
pp. 360-360
Author(s):  
Dario Gulin ◽  
Jozica Sikic ◽  
Sanja Sarta ◽  
Damira Pevec Matic

2021 ◽  
Vol 9 (C) ◽  
pp. 170-173
Author(s):  
Idaliya Rakhimova ◽  
Talgat Khaibullin ◽  
Yerbol Smail ◽  
Zhanar Urazalina ◽  
Vitalii Koval`chuk ◽  
...  

BACKGROUND: Patients with heart failure (HF) and implanted heart devices constitute a vulnerable category during the coronavirus disease –2019 (COVID-19) pandemic. The remote monitoring function allows the physician to detect atrial fibrillation (AF) in these patients and to prevent thromboembolic complications by prescribing anticoagulants. Under quarantine conditions, such patients can receive fully remote consultation and treatment, which will protect them from the risk of infection, and also reduce the burden on medical institutions. CASE REPORT: A 56-year-old man presented to the clinic with shortness of breath when climbing the second floor, moderate non-specific fatigue, general weakness, and a decrease in exercise tolerance. The patient received standard treatment for HF for at least 3 months (ACEI, beta blockers, MR antagonists, and loop diuretics) in individually selected adequate doses. ECG on admission showed a QRS of 150 ms, left bundle branch block (LBBB). Echo showed dilatation of all heart chambers, diffuse hypokinesis of the walls with akinesis of the apical, middle anterior LV segments, as well as hypokinesis of the basal, middle apical, and anterior septal segment of the LV. The ejection fraction was reduced to 35%. RV function is reduced. After a detailed discussion with the team, it was decided to do implantation of a cardioverter-defibrillator with resynchronization function, equipped with remote monitoring (Biotronik, and Home monitoring). Date of implantation is June 19, 2014. Due to the fact that the patient was connected to the remote monitoring system, May 5, 2020, he was diagnosed with asymptomatic AF. The episode lasted 1 min 22 s. On the following days of monitoring, episodes of AF were also recorded. The duration of the episodes ranged from a few seconds to 12 h/day. The patient received a doctor’s consultation through phone call, his risk of stroke was four when assessed using the CHA2DS2VASc scale. In treatment, it was recommended to add antiarrhythmic drugs (amiodarone 600 mg a day) and oral anticoagulants (rivaroxaban 20 mg × 1 time/day). Later, periodic IEGM showed absence of AF. CONCLUSION: In the context of the COVID-19 pandemic, health-care providers should rethink their approach to managing patients with implanted heart devices. Modern cardiovascular implantable electronic devices allow the physician to monitor the status of patients and immediately respond to situations requiring a change in treatment. Consultations can be carried out completely online.


2016 ◽  
Vol 11 (1) ◽  
pp. 501-505
Author(s):  
Yoshinobu Matsuda ◽  
Yoshito Yoshikawa ◽  
Sachiko Okayama ◽  
Rie Hiyoshi ◽  
Kaori Tohno ◽  
...  

2001 ◽  
Vol 78 (2) ◽  
pp. 183-184 ◽  
Author(s):  
Dariusz A. Kosior ◽  
Krzysztof J. Filipiak ◽  
Przemyslaw Stolarz ◽  
Grzegorz Opolski

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