STROKESTOP III - Optimized Method for Atrial Fibrillation Screening

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.

Study Overview

• Status: Not yet recruiting
• Conditions: Atrial Fibrillation; Atrial Fibrillation New Onset
• Intervention / Treatment: Behavioral: Screening invitation mode

Detailed Description

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.

• Study Type: Interventional
• Enrollment (Estimated): 2200
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Emma Svennberg, MD PhD; Phone Number: +46739584822; Email: emma.svennberg@regionstockholm.se

Study Locations

• Sweden
  • Stockholm, Sweden, 141 86
    • Karolinska Institutet, Dept Med H
    • Contact: MD PhD
    • Contact: Emma Svennberg, MD PhD; Phone Number: +46739584822; Email: emma.svennberg@regionstockholm.se
  • Värmland, Sweden
    • Region Värmland
    • Contact: Fredrik Carlstedt

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Older Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Individuals aged 75/76 in 2024 (born 1948, 1949)
• Must reside in the region of Värmland
• Must be listed at a primary care facility

Exclusion Criteria:

• Treatment with oral anti coagulation treatment (OAC)
• Contraindications for OAC treatment
• Prior atrial fibrillation
• Unable to provide consent

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Screening
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Other: Systematic screening group; Individuals aged 75/76 randomized to systematic screening are invited through a centralized screening facility to participate in prolonged ECG screening.	Behavioral: Screening invitation mode; Cluster randomized study to compare mode of invitation
Other: Opportunistic screening group; Individuals aged 75/76 randomized to opportunistic screening are invited to participate when they visit their primary care facility to prolonged ECG screening.	Behavioral: Screening invitation mode; Cluster randomized study to compare mode of invitation

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Participation in screening	Proportion of invitees participating in screening in each screening arm. The primary hypothesis is that opportunistic screening will increase participation by 25 % compared to systematic screening	12 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
AF detection in opportunistic compared to systematic screening	Proportion of participants with newly diagnosed AF in the screening groups	12 months
OAC treatment after AF detection	Proportion of participants with AF on OAC treatment after AF detection by manual follow up	12 months
Compliance to OAC treatment 1 year after initiation	Proportion of participants with AF on OAC treatment after AF detection	12 months
Health economy	Health-economic assessment of costs accrued in the systematic screening group compared to the opportunistic screening group	12 months
Composite endpoint of stroke, death and severe bleeding	A combined endpoint of the rate of stroke, all-cause death and severe bleeding leading to hospitalization in the group randomized to systematic screening compared to opportunistic screening	5 years
Reminder strategy effect on participation	The proportional increase in participation after reminder letter is sent out in both groups.	12 months
Comparison of automatic ECG analysis (using AI) for detection of AF in a (by AI algorithm classified) high- compared to a low-risk group	Proportion of new AF detected in the group determined as high risk per AI-algorithm compared to the group marked as low risk by the AI algorithm. An AI-algorithm using a neural network has previously been developed (PMID: 36881777) and will be prospectively tested to determine if individuals classified as high-risk to develop AF by the AI-algorithm on their initial electrocardiogram have an increased risk of screening-detected AF. The ECG reviewers will be blinded to the result of the AI-algorithm.	12 months
Application of the FIND-AF algorithm	An artificial intelligence model developed from electronic health care records in the United Kingdom has shown an increased risk of incident atrial fibrillation. We aim to determine how accurate the pre-specified variables from the FIND-AF algorithm (age, gender, presence of valvular disease, chronic pulmonary disease, chronic renal failure, as well as Chads-Vasc parameters) can predict atrial fibrillation (reported by sensitivity, specificity and area under the curve).	12 months

Collaborators and Investigators

• Sponsor: Danderyd Hospital
• Collaborators: Karolinska Institutet; Landstinget i Värmland
• Investigators: Principal Investigator: Emma Svennberg, MD PhD, Karolinska Institutet

Study record dates

Study Major Dates

• Study Start (Estimated): February 20, 2024
• Primary Completion (Estimated): February 28, 2025
• Study Completion (Estimated): June 30, 2026

Study Registration Dates

• First Submitted: November 6, 2023
• First Submitted That Met QC Criteria: February 16, 2024
• First Posted (Estimated): February 23, 2024

Study Record Updates

• Last Update Posted (Estimated): February 23, 2024
• Last Update Submitted That Met QC Criteria: February 16, 2024
• Last Verified: February 1, 2024

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Pathologic Processes; Heart Diseases; Cardiovascular Diseases; Arrhythmias, Cardiac; Atrial Fibrillation
• Other Study ID Numbers: STROKESTOP III

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No