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. 2022 Apr 21:14:751-763.
doi: 10.2147/NSS.S359468. eCollection 2022.

Detection of Common Arrhythmias by the Watch-PAT: Expression of Electrical Arrhythmias by Pulse Recording

Giora Pillar  1 , Murray Berall  2 , Richard B Berry  3 , Tamar Etzioni  1 , Yaakov Henkin  4 , Dennis Hwang  5 , Ibrahim Marai  6   7 , Faheem Shehadeh  6 , Prasanth Manthena  8 , Anil Rama  9 , Rebecca Spiegel  10 , Thomas Penzel  11 , Riva Tauman  12
Affiliations

Detection of Common Arrhythmias by the Watch-PAT: Expression of Electrical Arrhythmias by Pulse Recording

Giora Pillar et al. Nat Sci Sleep. .

Abstract

Background: The WatchPAT (WP) device was shown to be accurate for the diagnosis of sleep apnea and is widely used worldwide as an ambulatory diagnostic tool. While it records peripheral arterial tone (PAT) and not electrocardiogram (ECG), the ability of it to detect arrhythmias is unknown and was not studied previously. Common arrhythmias such as atrial fibrillation (AF) or premature beats may be uniquely presented while recording PAT/pulse wave.

Purpose: To examine the potential detection of common arrhythmias by analyzing the PAT amplitude and pulse rate/volume changes.

Patients and methods: Patients with suspected sleep disordered breathing (SDB) were recruited with preference for patients with previously diagnosed AF or congestive heart failure (CHF). They underwent simultaneous WP and PSG studies in 11 sleep centers. A novel algorithm was developed to detect arrhythmias while measuring PAT and was tested on these patients. Manual scoring of ECG channel (recorded as part of the PSG) was blinded to the automatically analyzed WP data.

Results: A total of 84 patients aged 57±16 (54 males) participated in this study. Their BMI was 30±5.7Kg/m2. Of them, 41 had heart failure (49%) and 17 (20%) had AF. The sensitivity and specificity of the WP to detect AF segments (of at least 60 seconds) were 0.77 and 0.99, respectively. The correlation between the WP derived detection of premature beats (events/min) to that of the PSG one was 0.98 (p<0.001).

Conclusion: The novel automatic algorithm of the WP can reasonably detect AF and premature beats. We suggest that when the algorithm raises a flag for arrhythmia, the patients should shortly undergo ECG and/or Holter ECG study.

Keywords: WatchPAT; arrhythmia; atrial fibrillation; home sleep apnea test; obstructive sleep apnea.

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Conflict of interest statement

Giora Pillar is a consultant to Itamar-Medical, and has current research funding from DayZz, KeepMed and InnoBev and has received speaker fees from TEVA, Pfizer and Sanofi. Richard Berry has current research funding from Philips Respironics and Res Med. Thomas Penzel has received unrestricted grants from &gesund, Itamar, Löwenstein Medical, Philips/Respironics, Resmed and speaker fees from Inspire, Heel Pharma, Philips, and UCB; reports grants from Cidelec, personal fees from Bayer Healthcare, personal fees from Jazz Pharma, personal fees from Cerebra, personal fees from National Sleep Foundation, grants, personal fees from Löwenstein Medical, grants from Novartis, Shareholder from Advanced Sleep Research, Shareholder from The Siestagroup GmbH, Shareholder from Nukute, outside the submitted work. The authors report no other conflicts of interest in this work.

Figures

Figure 1
Figure 1
Normal sinus rhythm. The PAT signal (A) and the derived RR periods (B) in a window of 60 seconds, with histograms of the RR periods (C) and the first and second derivatives sequences (D and E), demonstrate the distribution of RR periods with typical heart rate variability.
Figure 2
Figure 2
Atrial fibrillation. The PAT signal (A) and the chaotic pattern of heartbeats demonstrated in the RR sequence (B) is reflected in the wide, unimodal, and relatively flat distributions of RR periods and their derivatives (C–E).
Figure 3
Figure 3
Sympathetic activation. The PAT signal (A) and the derived RR periods (B) in a window of 60 seconds. The increased pulse rate accompanied by reduced PAT amplitude is typical to sympathetic activation, for instance, during arousal that follows an obstructive sleep apnoea event. The distribution of RR periods in such event (C) might resemble the one of atrial fibrillation, but the distributions of the first and second derivative sequences (D and E) are much narrower, and aid in the distinction between the phenomena.
Figure 4
Figure 4
Premature beats. The PAT signal (A) and the derived RR periods (B) in a window of 60 seconds. The premature beats are associated with shorter RR periods compared to the surrounding beats (B). This leads to sparse histograms with isolated bins (C). As the density of premature beats increases, a pattern of multimodal distribution emerges (D and E). (A) Premature might produce lower amplitudes in the PAT signal, as in the beats marked (f). In some cases, the amplitude is unchanged (g), and in other cases, the pulse is hardly observable (h).
Figure 5
Figure 5
Scatterplot of average number of premature beats per minute detected by each system produced by WP200U and ECG. The scattered line represents the identity line y=x. The solid line represents the actual results, with a correlation of 0.982 between the two methods.
Figure 6
Figure 6
Scatterplot of maximal premature beats rate detected by each system produced by WP200U and ECG. The scattered line represents the identity line y=x. The solid line represents the actual results, with a correlation of 0.946 between the two methods.
See this image and copyright information in PMC

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