Atrial Fibrillation, Cardiovascular Diseases, Heart Diseases
Conditions
Keywords
Computation, Data Science, Atrial fibrillation, Stroke
Brief summary
The purpose of this study is to trial a new intervention - risk-guided AF screening using an EHR-based risk score and remote ECG monitoring process - and to characterise individuals at elevated predicted AF risk.
Detailed description
This pilot study will use a post-market device within its intended purpose and involve a change in standard care - that is the offer of ECG monitoring for individuals at risk of AF to understand whether this leads to an increase in detection rates of AF, and follow-through prescription of oral anticoagulation. Starting with the population that are eligible for oral anticoagulation (men with a CHA2DS2VASC ≥ 2 and women with a CHA2DS2VASC ≥ 3), but without AF, this pilot study will use FIND-AF within its intended purpose to predict the absolute risk of AF diagnosis for individuals within the next 6 months. It will be observed whether systematic AF screening leads to higher detection rates of AF in individuals at higher risk for AF than individuals at lower risk for AF. This will give pilot data for whether systematic screening for AF in individuals at higher AF risk results in an incrementally higher yield of AF detection compared with screening approaches that have been targeted by age and risk of AF-related stroke. If the pilot shows that detection rates for AF are higher in the group at higher AF risk, then it would be suitable to plan a randomised controlled trial to determine whether systematic AF screening guided by AF risk increases detection rates of AF compared with routine care, and whether this is associated with a lower rate of stroke. The detection rates during systematic AF screening in this pilot study for individuals at higher and lower risk can establish power calculations required for a full-scale study and whether the numeric score at which a clinician would implement the intervention can be optimised. In addition, this pilot study will establish the technical, logistic and administrative feasibility of a full-scale remote AF screening study including issues of recruitment and protocol adherence. It will also inform as to whether individuals diagnosed with AF by systematic AF screening in the community will receive oral anticoagulation interventions in primary care, and thus whether treatment of screen-detected AF in a full-scale study should be implemented in primary care or in secondary care under cardiology. Finally this study will offer participants at higher AF risk the opportunity to attend a research clinic to determine whether these individuals have risk factors and comorbidities that could be identified and treated to reduce their subsequent risk of AF and other adverse events. This will establish whether individuals at risk of AF will attend for review, and their burden of modifiable risk factors for AF. This will establish power calculations that would be required for a full-scale study to test the hypothesis that primary prevention of AF is possible through interventions aimed at individuals at risk of AF.
Interventions
Prospective verification of a developed algorithm to predict the risk of a new onset Atrial Fibrillation
Sponsors
British Heart Foundation
Daiichi Sankyo
The Leeds Teaching Hospitals NHS Trust
University of Leeds
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
30 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Age at enrolment ≥30 years * Men with CHA2DS2VASC ≥ 2 and women with a CHA2DS2VASC ≥ 3
Exclusion criteria
* Known diagnosis of AF * On anticoagulation therapy * On the palliative care register * Unable to give written informed consent for participation in the study * Unable to adhere to the study requirements
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| To determine whether detection rates of AF during ECG monitoring are higher amongst participants identified as higher risk of AF, compared with those identified as lower risk | 6 months | Rate ratio of AF detection rates during ECG monitoring in participants identified as higher risk by FIND-AF compared with participants identified as lower risk |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| To determine, of participants who are detected as having AF during ECG monitoring, the proportion who subsequently receive oral anticoagulation prescription | 6 months | Number (%) of participants who receive an oral anticoagulant prescription after diagnoses of AF during ECG monitoring diagnosed |
Other
| Measure | Time frame | Description |
|---|---|---|
| To determine how diagnostic yield, C statistic/AUROC, NPV, PPV, sensitivity and specificity, varies at different cut off points of the FIND-AF risk score | 6 months | Diagnostic yield, PPV, NPV, sensitivity and specificity amongst participants who receive ECG monitoring, to understand whether the numeric score at which a clinician implements ECG monitoring can be optimised |
| To determine the C statistic/AUROC, NPV, PPV, sensitivity and specificity for alternative approaches to guide systematic AF screening in participants who receive ECG monitoring: | 6 months | Diagnostic yield, C statistic/AUROC, PPV, NPV, sensitivity and specificity in patients who are : CHA2DS2VASC≥3 in men and CHA2DS2VASC≥4 in women, age ≥70 years and age 75 and 76 years |
| To determine if yield from ECG monitoring varies across age groups (≥75 years and ≤75 years) and sex (men and women) | 6 months | AF detection rates and risks comparing higher and lower risk participants stratified by subgroup |
| To determine recruitment rates, overall study. | Up to 24 months | Number (%) of people who consent to participate compared to number of people who are invited |
| To determine withdrawal rates | Up to 24 months | Number (%) of people who consent to participate but subsequently withdraw consent / decline ECG monitoring |
| To determine if there are differences between those who participate and those that do not participate | Up to 24 months | Characteristics of those who consent to participate and do not consent to participate |
| To determine if there are differences between those who participate and those that withdraw | Up to 24 months | Characteristics of those who participate and those that withdraw |
| To determine the adherence of ECG recordings amongst participants | Up to 24 months | Mean number of recordings compared to the maximum stipulated Number (%) of participants who record less than 50% of stipulated amount of ECG recordings |
| To determine the number of ECG recordings that need to be reviewed for possible AF detection | Up to 24 months | Number (%) of ECG recordings flagged as abnormal by the algorithm within ECG recorder software that require manual review to assess for potential AF diagnosis |
| To determine the burden of other arrhythmias that are diagnosed through ECG monitoring in participants identified as higher risk and lower risk | Up to 24 months | Number (%) of participants who are diagnosed with other arrhythmias ( (atrial tachycardia, supraventricular tachycardia, 2nd degree AV block, high grade AV block or 3rd degree heart block, pause/asystole, ventricular tachycardia, ventricular fibrillation) during ECG monitoring in participants |
| To determine the burden of non-diagnostic rhythm reports from ECG monitoring | Up to 24 months | Number (%) of participants who have an ECG monitoring period with consistent poor quality which precludes a diagnostic result |
| To determine recruitment rates - research clinic appointment | Up to 24 months | Number (%) of people who consent to attend a research clinic appointment compared to number of people who are invited |
| To determine what other conditions and cardiovascular risk factors are identified amongst participants classified as higher risk for AF at research clinic | End of recruitment | Descriptive statistics of demographics, morbidities, medications, and cardiac ultrasound findings |
| To observe the clinical outcomes of participants that participate in the study, and whether there is a difference between participants identified as higher and lower risk? | 5 years from completion of recruitment | Number (%) of participants who experience at 5 years: * AF * Ischaemic stroke * Haemorrhagic stroke * Systemic embolism * Gastrointestinal or intracranial bleeding * Death * Chronic obstructive pulmonary disease * Chronic kidney disease * Heart failure * Diabetes mellitus * Myocardial infarction * Peripheral vascular disease * Valvular heart disease |
| To determine the AF detection rates amongst participants who are identified as higher risk and lower risk, including in the periods outside of ECG monitoring to determine the incremental yield that is achieved by ECG monitoring over routine care | 6 months | Risk of recorded AF diagnosis in EHR between individuals identified at higher and lower risk at six months after enrolment |
Countries
United Kingdom
Outcome results
None listed