Stroke risk analysis(SRA): a novel method to detect paroxysmal atrial fibrillation in primary care and post-stroke patients unknown with AF.

Facts: Atrial fibrillation (AF) is the most common, serious cardiac rhythm disorder in clinical practice. AF increases the risk of stroke more than 5 times to an average yearly risk of 4.2%. A stroke has a large negative impact on the quality of life and the autonomy of patients. Strokes due to AF are largely preventable with anticoagulant therapy(64% reduction in the risk of stroke and 25% reduction in mortality).If we can detect AF before a stroke occurs and start anticoagulant therapy when appropriate,we may be able to prevent up to 18% of all strokes. Especially screening of elderly is worthwhile since the prevalence of AF increases with age, from 5% in people over 65 years old to 10% in patients of 80 years and over. It is to be expected that the prevalence will grow in the near future with ageing of the population. In patients who have already suffered a stroke or TIA detecting AF is important for treatment implications. Challenges: Detection of AF is complicated by two factors: AF is often asymptomatic and AF frequently presents itself as a paroxysmal disorder. Screening tools mainly target on patients with persistent AF. Because the screening is performed at a random moment the chance of missing paroxysmal AF (pAF) is large. The detection of pAF is important in two patient categories: 1.in the elderly patient as part of screening, 2. in patients after a stroke or TIA. To detect pAF ambulatory rhythm recording is needed. A study in post-stroke patients showed that a 30 day period of automatically triggered event recording increased the detection rate of pAF fivefold compared to a 24 hour Holter. No large studies have been published in which the effectiveness of ambulatory rhythm recording with respect to detection of AF in primary care is evaluated. This is acknowledged as a major evidence gap. A major disadvantage of ambulatory rhythm recording is that it is time-consuming, costly and burdensome for the patient. Solution: Stroke risk analysis (SRA)analyses 1-hour recordings of a Holter ECG. In screening patients for pAF or evaluating patients for AF after stroke only one or two hours of continuous Holter recording would be needed, instead of 14 or 30 days. First studies testing SRA showed promising results suggesting that the method can identify patients at high risk for pAF who need additional longer lasting Holter monitoring and patients at low risk who don’t need further work-up. Study proposal: A diagnostic validation study to evaluate the diagnostic test characteristics of the SRA-method for diagnosing AF with two weeks Holter monitoring as reference standard in primary care patients of 65 years and over and post-stroke patients of 55 years and over unknown with AF. We include primary care patients who are already included in the intervention arm of the D2AF-study (ZonMw 80-83910-98-13014, NTR 4914), an opportunistic AF screening study performed in primary care. We ask patients with a negative 12-lead ECG (no AF) to participate in the second part of the study, detecting pAF using a two weeks Holter device. We also include consecutive patients with TIA or ischaemic stroke who are admitted to the stroke unit of the Academic Medical Centre(AMC). Patients with no AF on the admission ECG and no AF on continuous stroke unit ECG monitoring (CEM) during 24 hours receive Holter monitoring for two weeks. Indextest: The first 24 hours of the Holter recording are snipped in 1-hour recordings. The SRA software analyses the anonymised recordings. Results are categorized in high probability of normal sinus rhythm, risk of pAF and presence of manifest AF. Reference test: Two weeks Holter monitoring. The primary outcome measure is the sensitivity and specificity of the SRA of the first 1,2,6,12 and 24 hours of the Holter monitoring with two weeks Holter monitoring as reference standard in primary care patients and post-stroke patients, respectively. Sample size: In the primary care sample we expect about 1000 patients to participate. In the post-stroke sample we include 500 patients based on the number needed to perform a multivariate regression analysis. Collaboration: This project is a collaboration of the departments of General practice of the University of Maastricht and the University of Amsterdam (AMC) and builds on previous collaboration in the AMUSE-projects (DVT and pulmonary embolism) and the D2AF-study. Moreover we will collaborate with the departments of cardiology and neurology of the AMC.