STROKESTOP III - Optimized Method for Atrial Fibrillation Screening

Overview

Atrial fibrillation is the most common sustained cardiac arrhythmia affecting more than 3% of the adult population. The symptoms of atrial fibrillation can range from asymptomatic to debilitating. It can be permanent in its nature, but also paroxysmal with only short bursts of atrial fibrillation randomly occurring and can therefore remain unnoticed. Atrial fibrillation increases the risk of stroke five fold if left untreated. Screening for atrial fibrillation in elderly populations above age 65 years can result in detection of new atrial fibrillation cases ranging from 0,5% new AF with a single time-point ECG, up to 30% AF if an implantable loop recorder is inserted for 3 years. Currently opportunistic screening using pulse palpation, or a single time-point ECG is recommended by the European Society of Cardiology guidelines. Systematic screening in individuals aged 75 or above, or at a high stroke risk should be considered. Overall, participation in systematic atrial fibrillation screening trials has been shown to be relatively low with almost 50% non-participants. Participants are generally healthier, with higher socioeconomic status, hence the ones who would potentially benefit the most remain absent. Opportunistic screening has shown promising results with higher participation rates and the possibility of better outreach. There is a lack of data from randomized trials on the difference in participation rates in systematic and opportunistic screening approaches when screening with prolonged ECG monitoring.

Plans and methods; Primary care facilities in the region of Värmland with at least 200 75-76 year-old listed will be randomized to either: 1. Systematic screening. All 75/76 year old belonging to a primary care facility randomized to systematic screening will receive a letter with an invitation to screening through the Clinical Physiology department at Karlstad Central Hospital. 2. Opportunistic screening. All 75/76 year old attending their primary care facility for any health related reason will be invited to screening at the primary care facility. A complete list of all listed individuals will be drawn from each primary care facility list of patients for both screening arms at the beginning of the study. Inclusion criteria: All individuals aged 75/76 residing in the region of Värmland, listed at a primary care facility with \> 200 individuals aged 75/76 Exclusion criteria: Individuals with ongoing oral anti coagulation treatment (OAC), contraindication for OAC treatment and/or known and treated atrial fibrillation will be excluded from participation. Individuals not being able to consent will be excluded from participation. All participants will be asked to fill out a health declaration. A hand-held single-lead ECG (Zenicor One) will be sent to the participant via mail. The device will be used to measure ECGs on a regular basis three times a day, and during symptoms. ECGs are transferred for interpretation through the mobile network. All ECGs will be manually interpreted by specifically trained physiologists. All positive findings are communicated to primary care by the physiologists for initiation of OAC treatment. All negative findings are communicated to the participant via mail. Participation status, and new AF diagnosis will be assessed immediately after study closure. Secondary endpoints will be assessed at one year through Swedish national patients' registries. In a sub-study an artificial intelligence model will be scoring all individuals' risk of developing AF based on the initial ECG (unless there is substantial noise, then second ECG will be used). The AI analysis will be blinded to the interpreter of the ECGs. All participants will be stratified into a low-risk and a high-risk group of developing AF during screening based on the AI analysis. At the end of the screening period the outcome of the AI model will be compared with the results of the screening. In a sub study the investigators will use artificial intelligence as a means of assessment support when interpreting ECGs. The artificial intelligence model has been used to determine a cut-off for high and low risk individuals and will be prospectively evaluated to determine if it can be used to identify individuals that will benefit most from AF screening.