Automatic detection of paroxysmal atrial fibrillation in patients with ischaemic stroke: better than routine diagnostic workup?

Abstract

Background and purposeProlonged electrocardiogram (ECG) monitoring after ischaemic stroke increases the diagnostic yield of paroxysmal atrial fibrillation (pAF). In order to facilitate the additional workload involved in ECG analysis due to prolonged monitoring times, we investigated the effectiveness of pAF detection with an automated software algorithm (SA) in comparison to the routine staff‐based analysis (RA) during standard stroke‐unit care. Therefore, patients with acute ischaemic stroke or transitory ischaemic attack presenting with sinus rhythmus on the admission ECG and no history of atrial fibrillation were prospectively included.MethodsA 24‐h Holter ECG assessment was performed using either RA based on a computer‐aided evaluation and subsequent review by a cardiologist or a commercially available automated SA. In the case of discordant results concerning the occurrence of pAF between the two methods, the data underwent an independent external rating.ResultsOf 809 prospectively enrolled patients, 580 patients fulfilled the inclusion criteria. pAF was ultimately diagnosed in 3.3% of the cohort (19 patients). SA and RA correctly diagnosed pAF in 17 patients resulting in a comparable diagnostic effectiveness of the analysis methods (sensitivity: SA 89.5% vs. RA 89.5%; specificity: SA 99.3% vs. RA 99.1%; κ, 0.686; P < 0.001; 95% confidence interval, 0.525–0.847). RA revealed clinically relevant ECG abnormalities in an additional seven patients.ConclusionsAlthough it should not completely replace RA, SA‐based evaluation of Holter ECG reaches a high diagnostic effectiveness for the detection of pAF and can be used for a rapid and resource‐saving analysis of ECG data to deal with prolonged monitoring times.

Software‐based analysis of 1‐hour Holter ECG to select for prolonged ECG monitoring after stroke

“…The AA utilized in our study could be used for both evaluation of ECG telemetry recorded during Stroke Unit monitoring 23,31,32 and Holter ECG data. 8 Recently, the same AA was also used in patients with cryptogenic stroke to select those who may benefit from prolonged cardiac monitoring afforded by an implantable device. 32 In a comparable approach, a recent study demonstrated that application of an artificial intelligence algorithm on 12-lead ECG in sinus rhythm was able to select patients at high risk for developing AF and might thereby not only decrease the diagnostic workload of ECG analysis but also increase the diagnostic yield of AF.…”

“…In short, the AA creates a report of whether pAF is detectable, mainly based on the regularity of preceding R-R intervals. 8,18 Patients classified as "AF" within the first hour of ECG recording (n = 12) were excluded from further analysis. We evaluated patients classified as "no risk of AF" in comparison to patients with "risk of AF" with regard to detection of AF within the following 72-hour Holter ECG monitoring, which was started within 12 hours after hospital admission.…”

“…7 However, efforts to increase the detection rates of pAF after ischemic stroke are equally increasing the workload for ECG analysis and interpretation. 8 In order to overcome these obstacles, selection criteria for ª 2020 The Authors.…”

Progress in neurology 2017–2018

“…Stroke remains the most common problem for neurologists to diagnose and treat . Preventative measures, such as control of hypertension, reduction in smoking and treatment of hyperlipidaemia, have made a significant contribution to preventing and delaying stroke onset.…”

Positionspapier zur Detektion von Vorhofflimmern nach ischämischem Schlaganfall

“…Validierung der EKG-Befunde und einer ärztlichen Diagnosestellung[20,21,44]. Neben der Detektion von Vorhofflimmern und Vorhofflattern müssen dabei auch potenziell lebensbedrohliche Arrhythmien beachtet werden.…”