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OpenTrials
Completed

NCT Number: NCT05838781

DeteCtiON and Stroke PreventIon by MoDEl ScRreenING for Atrial Fibrillation

Atrial fibrillation (AF) is the most common clinical arrhythmia and the prevalence increases with age. AF increases the risk of ischaemic stroke fivefold and accounts for almost one-third of all strokes. As AF is often asymptomatic there are many undetected cases. It is important to find patients with AF and additional risk factors for stroke in order to initiate oral anticoagulation treatment, which can reduce the risk of an ischaemic stroke by 60-70%. Screening is recommended in European guidelines, however the most suitable population and the most suitable device for AF detection remain to be defined.

The main objective of this study is to test the hypothesis that AF screening with 14-days continuous ECG monitoring in high-risk individuals identified with a risk prediction model is more effective than routine care in identifying patients with undetected AF.

Effectively detecting AF among patients with risk factors for ischaemic stroke has the potential to decrease mortality and morbidity, stroke burden and costs for the society as a whole.

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Key information

Age range

65 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Karolinska Institutet Danderyd University Hospital, Stockholm, Outside US, Sweden

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About this study

Objective(s): To compare the yield of atrial fibrillation (AF) using 14-days continuous ECG in a population aged ≥ 65 years with an increased risk for AF incidence according to the risk prediction model compared with standard of care in Region Halland.

Study Population: Residents in Region Halland age 65 and above.

Data Collection Methods: Electronic Health Records from Region Halland and 14-days continuous ECG recording using an ECG patch.

Study design:

Step 1:

To calibrate the BMS/Pfizer risk prediction model (RPM), we will extract two cohorts retrospectively: the AF cohort with an AF diagnosis (patients with a record of incident AF diagnosis between January 1, 2016, and December 31, 2019 as an observation period), and the control cohort without any AF diagnosis in their history. We will include patients ≥45 years of age at index date, which is the first date of an AF diagnosis recorded in the observation period and a random pseudo index date during the observation period for the control group, to follow the original study. Specifically, we are looking to calibrate the intercept (α) for the logistic regression where we already have the 13 odd ratios for the 13 risk factors from the original study. Then in the next step for the prospective study, applying the RPM on the RPM cohort, the at-risk group will be extracted for randomization step, using the recommended cut-off value.

Step 2:

The population in Region Halland aged 65 years and above and free from AF will be randomized into two halves, creating a general cohort and an RPM cohort. In the general cohort, 1480 individuals will be further randomized into two arms, general/control and general/intervention. In the RPM cohort, the risk of incident AF will be calculated according to the Pfizer/BMS RPM. Those with a predicted risk for incident AF above a pre-specified threshold will then be randomly extracted into two arms, RPM/control and RPM/intervention (figure 1).

Those randomized to the two intervention arms (general/intervention and RPM/intervention, n=740 each) will be invited to an AF screening intervention of 14-days continuous ECG using a patch device. Those randomized to the control groups (general/control and RPM/control, n=740 each) will not receive any information or intervention.

The primary endpoint will be the difference in yield of newly diagnosed AF between the RPM/intervention and the general/control arms, where the latter will represent standard of care. Participants with newly diagnosed AF in the intervention arms will be offered consultation aiming at AF work-up and initiation of oral anticoagulation treatment.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Alive residents in the Halland region aged 65 or older without a recorded diagnosis of AF

Exclusion criteria

  • Known atrial fibrillation
  • Death
  • No longer resident in Region Halland
  • Pacemaker, implantable cardioverter defibrillator or insertable monitor
  • Dementia
  • Other indication for OAC treatment (such as VTE, mechanical heart valve replacement, VTE prophylaxis post surgery, mitral stenosis, left side intracardial thrombus)

Treatment and study plan

Risk prediction model

Diagnostic Test

A risk prediction model (RPM) based on logistic regression. The RPM uses 13 variables accessible in healthcare registers to identify individuals with high future risk for developing AF. ICD-10 codes will be used.

14-days continuous ECG monitoring

Diagnostic Test

14-days continuous ECG monitoring with an ECG patch.

Primary outcomes

  1. Incident AF

    Time frame: 14 days

    • Incident AF on ECG screening (intervention arms) defined as at least one episode of AF or atrial flutter with a duration of at least 30 seconds on ambulatory ECG recording.
    • Incident AF registered in the Electronic Health Record during follow-up (all four arms).

Secondary outcomes

  1. Yield newly diagnosed AF: RPM/ intervention arm versus RPM/ control arm

    Time frame: 14 days

    To compare the yield of newly diagnosed AF using 14-days continuous ECG in a population aged ≥ 65 years with an increased risk for AF incidence according to the RPM compared with a population with increased risk according to the RPM without intervention.

  2. Yield newly diagnosed AF: general/ intervention arm versus RPM/ control arm

    Time frame: 14 days

    To compare the yield of newly diagnosed AF using 14-days continuous ECG in a general population aged ≥ 65 years compared with a population with increased risk according to the RPM without intervention.

  3. Yield newly diagnosed AF: general/ intervention arm versus general/ control arm

    Time frame: 14 days

    To compare the yield of newly diagnosed AF using 14-days continuous ECG in a general population aged ≥ 65 years compared with a general population without intervention.

Other outcomes

  1. Proportion of patients starting oral anticoagulation treatment

    Time frame: 18 months

    Proportion of patients with AF and treatment with anticoagulation in control and interventions arms in the general and RPM cohorts, respectively, during a 6-, 12- and 18-months period?

  2. Feasibility of self-application of ECG patch

    Time frame: 14 days

    To study uptake and feasibility of self-application of ECG patch.

  3. AF yield during the first 24 and 48 hours

    Time frame: 48 hours

    Proportion of patients diagnosed with AF within the first 24 and 48 hours of ECG patch recording.

  4. Cost-effective analysis

    Time frame: 14 days

    Cost-effectiveness analysis of the risk prediction model together with the ECG patch compared to standard care. The possibility to increase survival as a consequence of avoiding AF-related events will then be compared to increased screening costs as well as cost of treatment.

Sponsors and collaborators

Lead sponsor

Bristol-Myers Squibb

Industry

Collaborators

  • Halmstad University
  • Karolinska Institutet
  • Pfizer
  • Philips Healthcare
  • Region Halland

Registry information

Acronym: CONSIDERING-AF

Important dates

Study start
2023
Primary completion
2024
Study completion
2024
First posted
May 3, 2023
Registry last updated
May 22, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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