Atrial fibrillation
Conditions
Interventions
Sponsors
Eligibility
Inclusion criteria
Inclusion criteria: 1. Age of 65 years or older 2. No previously documented AF
Exclusion criteria
Exclusion criteria: 1. Having a pacemaker. 2. Legal incompetence or unable to give informed consent. 3. Suffering from terminal illness. 4. Unable to come to the practice to participate in the diagnostic process, for instance a patient who is chronically bedridden. Patients who cannot visit the practice due to a temporary situation (such as the flu) are not excluded.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| (1) The difference between intervention and control practices in the number of patients with newly found AF during one year. (2) Sensitivity, specificity and other diagnostic parameters of pulse palpation, eBPM-AF and hand-ECG, respectively, using the 12-lead ECG and/or 2 week Holter monitoring as reference standard. | — |
Secondary
| Measure | Time frame |
|---|---|
| - Diagnostic test characteristics of the hand-ECG for home monitoring using the two week Holter monitoring as reference standard. - The number of patients with all index tests negative (a regular pulse with palpation and with eBPM-AF and hand-ECG not showing AF) in whom the Holter shows (paroxysmal) AF. - Description of the ‘usual care’ in the diagnostic work-up for AF (process evaluation of control practices), disclosing divergence from current guidelines. - Prevalence and incidence of (paroxysmal) AF in general practices in the Dutch general practice. - Diagnostic informativeness of patient profiles of newly detected patients with AF, including patient profiles of newly detected patients with ‘silent’ paroxysmal AF. - Comparison of the prevalence and incidence of AF between patients of Caucasian and non-Caucasian origin. - The cost effectiveness of optimized case finding (overall, and for each of the index tests separately) compared to usual care. The outcome of the analysis will be incremental costs per life year gained and per quality adjusted life year gained. - Prediction model for finding (different types of) AF. | — |
Contacts
Maastricht University