Detecting and Diagnosing Atrial Fibrillation (D2AF): study protocol for a cluster randomised controlled trial.

Area of Science:

• Cardiology
• Primary Care Medicine
• Medical Diagnostics

Background:

• Atrial fibrillation (AF) is a major risk factor for stroke, significantly increasing morbidity.
• Early detection and treatment of AF, even asymptomatic or paroxysmal cases, can reduce stroke risk by 60% with anticoagulants.
• Current case-finding methods like pulse palpation are effective, but new technologies may enhance AF detection.

Purpose of the Study:

• To determine the yield of an intensive case-finding strategy for atrial fibrillation in primary care.
• To evaluate the diagnostic accuracy of three different case-finding methods for detecting AF.
• To compare an enhanced AF case-finding protocol with usual care in a primary care setting.

Main Methods:

• A multicenter cluster randomized controlled trial involving 96 general practices.
• Inclusion of primary care patients aged 65 years or older without a prior AF diagnosis.
• Intervention group received an enhanced protocol (pulse palpation, automated device, handheld ECG); control group received usual care. Diagnostic accuracy assessed via 12-lead ECG, Holter monitoring, and patient-used handheld ECG.

Main Results:

• The study is currently recruiting practices; primary outcomes are the difference in new AF detection rates and diagnostic accuracy of index tests.
• The 'Detecting and Diagnosing Atrial Fibrillation' (D2AF) study aims to provide data on the effectiveness of the enhanced protocol.
• Results will quantify the yield of intensive case-finding and the accuracy of novel diagnostic tools.

Conclusions:

• An intensive case-finding strategy may improve the detection of atrial fibrillation in primary care.
• The diagnostic accuracy of new methods like automated devices and handheld ECGs needs further evaluation in real-world primary care settings.
• Effective case-finding for atrial fibrillation has the potential to prevent significant morbidity, such as stroke.