Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical practice. It is associated with the risk of developing some adverse cardiovascular events, including cerebral embolism and heart failure [1]. The development of AF depends on a variety of risk factors, including age, sex, race, hypertension, heart failure, coronary artery disease, valvular heart disease, obesity, diabetes, and chronic kidney disease [2]. Among these risk factors, hypertension has been established to be the most important factor [3, 4] In addition, in patients with AF, hypertension is one of the risk factors for the development of cerebral embolism [5]. In this regard, the Japanese guideline on pharmacotherapy of cardiac arrhythmias recommends the use of the CHADS2 score for the risk assessment of thromboembolism in patients with AF, in which “H” indicates hypertension [6]. An early diagnosis and the subsequent initiation of appropriate treatment for AF, including anticoagulation therapy, is strongly required in hypertensive patients. However, the diagnosis of AF is not easy in the clinical setting. Almost 40% of AF patients are asymptomatic [7]. Most of these patients are diagnosed as having AF at annual health check-up examinations [7]. The type of AF that is diagnosed at health check-up examinations is mostly the persistent type. Paroxysmal and asymptomatic AF is difficult to diagnose because there are few chances to detect AF by standard 12-lead electrocardiogram (ECG) [8]. Some of these patients unfortunately develop cerebral embolism before the diagnosis of AF. Although detailed assessment with 24-h Holter ECG is needed to detect AF, the chance of detection is limited [9]. On the other hand, ambulatory blood pressure monitoring (ABPM) is currently considered the most accurate method for diagnosing hypertension [10, 11]. Several institutions have recommended that most or all subjects with suspected hypertension undergo ABPM [12]. Notably, an ABPM device that especially implements an algorithm to automatically detect AF during each blood pressure measurement has been developed in recent years. In fact, Kollias et al. [13] demonstrated the high diagnostic accuracy of detecting AF using 24-h ABPM devices with AF detection algorithms.
In this issue of Hypertension Research, Watanabe et al. [14] reported that a 24-h ABPM device with a new irregular heartbeat (IHB) algorithm may be useful for the comprehensive management of hypertensive patients, including the early detection of AF. Among the 3347 valid reading cases, 843 cases (25%) were considered to indicate IHBs. Among these IHB reading cases, 195 cases (23%) were found to have an AF rhythm by 24-hour Holter ECG. In their comparison of 7 patients in the paroxysmal AF group and 47 patients in the normal group at the time of evaluation by 24-h Holter ECG, the authors observed that the patients with paroxysmal AF had a higher IHB burden and higher maximum number of consecutive IHBs than the patients in the normal group (IHB burden 29.3 ± 15.7% vs. 12.8 ± 10.3%, p = 0.001 and maximum number of consecutive IHBs 3.7 ± 2.3 vs. 1.6 ± 1.1, p = 0.050, respectively). Furthermore, the two optimal IHB parameters for suggesting potential AF were (1) an IHB burden defined as a percentage of IHB-positive measurements in total valid BP measurements >22.5% (84.6% sensitivity, 85.1% specificity) and (2) 2.5 or more consecutive IHBs shown in 24-h ABPM (84.6% sensitivity, 83.0% specificity). Based on these findings, the authors [14] concluded that the risk stratification for AF development using a 24-hour ABPM device with a new IHB algorithm may contribute to the comprehensive management of hypertensive patients with the main goal of preventing cerebrovascular events.
Again, hypertensive patients are prone to AF. Once AF develops, these patients are at high risk for cardiovascular events, including cerebral embolism. Figure 1 shows the graphical summary of the study by Watanabe et al. [14]. As shown, the proposed criteria, i.e., a high IHB burden >22.5% and 2.5 or more consecutive IHBs, resulted in surprisingly high sensitivity and specificity (both >80%) to detect AF. The 24-h ABPM is covered by insurance for patients with hypertension. Hopefully, a more sophisticated algorithm will be developed. The widespread use of the 24-h ABPM device with an excellent IHB algorithm would increase the chance of the early detection and diagnosis of AF, which can reduce the number of patients who unfortunately develop cerebral embolism before the diagnosis of AF.
References
Benjamin EJ, Wolf PA, D’Agostino RB, Silbershatz H, Kannel WB, Levy D. Impact of atrial fibrillation on the risk of death: The Framingham Heart Study. Circulation. 1998;98:946–52.
Schnabel RB, Sullivan LM, Levy D, Pencina MJ, Massaro JM, D’Agostino RB, et al. Development of a risk score for atrial fibrillation (Framingham Heart Study): a community-based cohort study. Lancet. 2009;373:739–45.
Inoue H, Fujiki A, Origasa H, Ogawa S, Okumura K, Kubota I, et al. Prevalence of atrial fibrillation in the general population of Japan: an analysis based on periodic health examination. Int J Cardiol. 2009;137:102–7.
Kokubo Y, Watanabe M, Higashiyama A, Nakao YM, Kusano K, Miyamoto Y. Development of a basic risk score for incident atrial fibrillation in a Japanese general population: the Suita Study. Circ J. 2017;81:1580–8.
Gage BF, Waterman AD, Shannon W, Boechler M, Rich MW, Radford MJ. Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation. JAMA. 2001;285:2864–70.
Ono K, Iwasaki YK, Akao M, Ikeda T, Ishii K, Inden Y, et al. JCS/JHRS 2020 guideline on pharmacotherapy of cardiac arrhythmias. Circ J. 2022. https://doi.org/10.1253/circj.CJ-20-1212
Senoo K, Suzuki S, Sagara K, Otsuka T, Matsuno S, Funada R, et al. Distribution of ⦸first-detected atrial fibrillation patients without structural heart diseases in symptom classifications. Circ J. 2012;76:1020–3.
Kirchhof P, Bax J, Blomstrom-Lundquist C, Calkins H, Camm AJ, Cappato R, et al. Early and comprehensive management of atrial fibrillation: Proceedings from the 2nd AFNET/EHRA consensus conference on atrial fibrillation entitled ʻresearch perspectives in atrial fibrillationʼ. Europace. 2009;11:860–85.
Steinberg JS, Varma N, Cygankiewicz I, Aziz P, Balsam P, Baranchuk A, et al. 2017 ISHNE-HRS expert consensus statement on ambulatory ECG and external cardiac monitoring/telemetry. Heart Rhythm. 2017;14:e55–e96.
Mancia G, Fagard R, Narkiewicz K, Redón J, Zanchetti A, Böhm M, et al. Task Force Members. 2013 ESH/ESC Guidelines for the management of arterial hypertension: the Task Force for the management of arterial hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). J Hypertens. 2013;31:1281–357.
O’Brien E, Parati G, Stergiou G, Asmar R, Beilin L, Bilo G, et al. European Society of Hypertension Working Group on Blood Pressure Monitoring. European Society of Hypertension position paper on ambulatory blood pressure monitoring. J Hypertens. 2013;31:1731–68.
Whelton PK, Carey RM, Aronow WS, Casey DE Jr, Collins KJ, Dennison Himmelfarb C, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension. 2018;71:1269–324.
Kollias A, Destounis A, Kalogeropoulos P, Kyriakoulis KG, Ntineri A, Stergiou GS. Atrial fibrillation detection during 24-hour ambulatory blood pressure monitoring: comparison with 24-hour electrocardiography. Hypertension. 2018;72:110–5.
Watanabe T, Tomitani N, Yasui N, Kario K. Validation of an ambulatory blood pressure monitoring device employing a novel method to detect atrial fibrillation. Hypertens Res. 2022. https://doi.org/10.1038/s41440-022-00925-0.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interests
The authors declare no competing interests.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Shinohara, T., Takahashi, N. Irregular heart rhythm algorithm: a novel strategy to accurately detect atrial fibrillation by ambulatory monitoring of blood pressure. Hypertens Res 45, 1398–1399 (2022). https://doi.org/10.1038/s41440-022-00943-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41440-022-00943-y