Observational studyTranslational stroke research2019
Electrocardiographic RR Interval Dynamic Analysis to Identify Acute Stroke Patients at High Risk for Atrial Fibrillation Episodes During Stroke Unit Admission.
Observational study in Translational stroke research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 23 citations in OpenAlex.
- Is Stroke risk analysis (SRA) a reliable method for predicting atrial fibrillation? A systematic review.PloS one · 2024Pooled it
- Heart rate variability as a predictor of stroke course, functional outcome, and medical complications: A systematic review.Frontiers in physiology · 2023Pooled it
- Heart rate variability in patients with atrial fibrillation of sinus rhythm or atrial fibrillation: chaos or merit?Annals of medicine · 2025Review
- Artificial intelligence for prediction of atrial fibrillation in the stroke unit: a retrospective derivation validation cohort study.EBioMedicine · 2025Article
- Stroke-heart syndrome: current progress and future outlook.Journal of neurology · 2024Review
- Rate of atrial fibrillation by Holter-Stroke Risk Analysis in undetermined TIA/rapidly improving stroke symptoms patients.Frontiers in neurology · 2024Article
- Multimodal Approach for the Prediction of Atrial Fibrillation Detected After Stroke: SAFAS Study.Frontiers in cardiovascular medicine · 2022Article
- Computational Diagnostic Techniques for Electrocardiogram Signal Analysis.Sensors (Basel, Switzerland) · 2020Review
- Software-based analysis of 1-hour Holter ECG to select for prolonged ECG monitoring after stroke.Annals of clinical and translational neurology · 2020Article
- Markers of endothelial pathology to support detection of atrial fibrillation in embolic stroke of undetermined source.Scientific reports · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Patients at short-term risk of paroxysmal atrial fibrillation (PAF) often exhibit increased RR interval variability during sinus rhythm. We studied if RR dynamic analysis, applied in the first hours after stroke unit (SU) admission, identified acute ischemic stroke patients at higher risk for subsequent PAF episodes detected within the SU hospitalization. Acute ischemic stroke patients underwent continuous cardiac monitoring (CCM) using standard bedside monitors immediately after SU admission. The CCM tracks from the first 48 h were analyzed using a telemedicine service (SRA clinic, Apoplex Medical, Germany). Based on the RR dynamics, the stroke risk analysis (SRA) algorithm stratified the risk for PAF as follows: low risk for PAF, high risk for PAF, presence of manifest AF. The subsequent presence/absence of PAF during the whole SU hospitalization was ruled out using all available CCMs, standard ECGs, or 24-h Holter ECGs. Two hundred patients (40% females, mean age 71 ± 16 years) were included. According to the initial SRA analysis, 111 patients (56%) were considered as low risk for PAF, 52 (26%) as high risk while 37 patients (18%) had manifest AF. A low-risk level SRA was associated with a reduced probability for subsequent PAF detection (1/111, 0.9%, 95% CI 0-4.3%) while a high-risk level SRA predicted an increased probability (20/52, 38.5% (95% CI 25-52%). RR dynamic analysis performed in the first hours after ischemic stroke may stratify patients into categories at low or high risk for forthcoming paroxysmal AF episodes detected within the SU hospitalization.
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