Automatic Holter electrocardiogram analysis in ischaemic stroke patients to detect paroxysmal atrial fibrillation: ready to replace physicians?
cardiac embolism
cerebral infarction
stroke
transient ischaemic attack
Journal
European journal of neurology
ISSN: 1468-1331
Titre abrégé: Eur J Neurol
Pays: England
ID NLM: 9506311
Informations de publication
Date de publication:
07 2020
07 2020
Historique:
received:
10
03
2020
revised:
01
04
2020
accepted:
01
04
2020
pubmed:
13
4
2020
medline:
22
6
2021
entrez:
13
4
2020
Statut:
ppublish
Résumé
The detection of paroxysmal atrial fibrillation (pAF) in patients presenting with ischaemic stroke shifts secondary stroke prevention to oral anticoagulation. In order to deal with the time- and resource-consuming manual analysis of prolonged electrocardiogram (ECG)-monitoring data, we investigated the effectiveness of pAF detection with an automated algorithm (AA) in comparison to a manual analysis with software support within the IDEAS study [study analysis (SA)]. We used the dataset of the prospective IDEAS cohort of patients with acute ischaemic stroke/transient ischaemic attack presenting in sinus rhythm undergoing prolonged 72-h Holter ECG with central adjudication of atrial fibrillation (AF). This adjudicated diagnosis of AF was compared with a commercially available AA. Discordant results with respect to the diagnosis of pAF were resolved by an additional cardiological reference confirmation. Paroxysmal AF was finally diagnosed in 62 patients (5.9%) in the cohort (n = 1043). AA more often diagnosed pAF (n = 60, 5.8%) as compared with SA (n = 47, 4.5%). Due to a high sensitivity (96.8%) and negative predictive value (99.8%), AA was able to identify patients without pAF, whereas abnormal findings in AA required manual review (specificity 96%; positive predictive value 60.6%). SA exhibited a lower sensitivity (75.8%) and negative predictive value (98.5%), and showed a specificity and positive predictive value of 100%. Agreement between the two methods classified by kappa coefficient was moderate (0.591). Automated determination of 'absence of pAF' could be used to reduce the manual review workload associated with review of prolonged Holter ECG recordings.
Sections du résumé
BACKGROUND AND PURPOSE
The detection of paroxysmal atrial fibrillation (pAF) in patients presenting with ischaemic stroke shifts secondary stroke prevention to oral anticoagulation. In order to deal with the time- and resource-consuming manual analysis of prolonged electrocardiogram (ECG)-monitoring data, we investigated the effectiveness of pAF detection with an automated algorithm (AA) in comparison to a manual analysis with software support within the IDEAS study [study analysis (SA)].
METHODS
We used the dataset of the prospective IDEAS cohort of patients with acute ischaemic stroke/transient ischaemic attack presenting in sinus rhythm undergoing prolonged 72-h Holter ECG with central adjudication of atrial fibrillation (AF). This adjudicated diagnosis of AF was compared with a commercially available AA. Discordant results with respect to the diagnosis of pAF were resolved by an additional cardiological reference confirmation.
RESULTS
Paroxysmal AF was finally diagnosed in 62 patients (5.9%) in the cohort (n = 1043). AA more often diagnosed pAF (n = 60, 5.8%) as compared with SA (n = 47, 4.5%). Due to a high sensitivity (96.8%) and negative predictive value (99.8%), AA was able to identify patients without pAF, whereas abnormal findings in AA required manual review (specificity 96%; positive predictive value 60.6%). SA exhibited a lower sensitivity (75.8%) and negative predictive value (98.5%), and showed a specificity and positive predictive value of 100%. Agreement between the two methods classified by kappa coefficient was moderate (0.591).
CONCLUSION
Automated determination of 'absence of pAF' could be used to reduce the manual review workload associated with review of prolonged Holter ECG recordings.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1272-1278Informations de copyright
© 2020 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.
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