Results, barriers and enablers in atrial fibrillation case finding: barriers in opportunistic atrial fibrillation case finding-a cross-sectional study

Evidence Gaps and Lessons in the Early Detection of Atrial Fibrillation: A Prospective Study in a Primary Care Setting (PREFATE Study)

Background/Objectives: In Europe, the prevalence of AF is expected to increase 2.5-fold over the next 50 years with a lifetime risk of 1 in 3-5 individuals after the age of 55 years and a 34% rise in AF-related strokes. The PREFATE project investigates evidence gaps in the early detection of atrial fibrillation in high-risk populations within primary care. This study aims to estimate the prevalence of device-detected atrial fibrillation (DDAF) and assess the feasibility and impact of systematic screening in routine primary care. Methods: The prospective cohort study (NCT05772806) included 149 patients aged 65-85 years, identified as high-risk for AF. Participants underwent 14 days of cardiac rhythm monitoring using the Fibricheck® app (CE certificate number BE16/819942412), alongside evaluations with standard ECG and transthoracic echocardiography. The primary endpoint was a new AF diagnosis confirmed by ECG or Holter monitoring. Statistical analyses examined relationships between AF and clinical, echocardiographic, and biomarker variables. Results: A total of 18 cases (12.08%) were identified as positive for possible DDAF using FibriCheck® and 13 new cases of AF were diagnosed during follow-up, with a 71.4-fold higher probability of confirming AF in FibriCheck®-positive individuals than in FibriCheck®-negative individuals, resulting in a post-test odds of 87.7%. Significant echocardiographic markers of AF included reduced left atrial strain (<26%) and left atrial ejection fraction (<50%). MVP ECG risk scores ≥ 4 strongly predicted new AF diagnoses. However, inconsistencies in monitoring outcomes and limitations in current guidelines, particularly regarding AF burden, were observed. Conclusions: The study underscores the feasibility and utility of AF screening in primary care but identifies critical gaps in diagnostic criteria, anticoagulation thresholds, and guideline recommendations.

[MVP Risk score and new atrial fibrillation diagnosis: Prospective cohort PREFATE study]

OBJECTIVE

To assess the association between electrocardiogram (ECG) patterns according to the MVP ECG risk score (morphology-voltage-P-wave duration) and a diagnosis of Atrial Fibrillation (AF).

DESIGN

Prospective observational cohort study (1/01/2023-31/12/2024). SITE: Primary care.

PARTICIPANTS

Randomized sample of 150 patients aged 65-85 years without prior diagnosis of AF, stroke, or current anticoagulant treatment; high risk of future AF; CHA2DS2-VASc ≥2; and ability to use the FibricheckR application (App).

MEASUREMENTS

At baseline, a standard ECG, MVP risk score assessment, and cardiac rhythm monitoring for 15 days using the FibricheckR App were performed. The dependent variables were the presence of P-wave patterns on the electrocardiogram according to MVP risk score and a new diagnosis of AF.

RESULTS

The diagnosis of AF was confirmed in 14 cases (9.3%, 95% CI 5.6-15.1), 3 men and 11 women. In 3 cases, the arrhythmia was diagnosed on the baseline ECG, and in 11 cases by Holter after being reported as possible AF by the FibricheckR App. A higher prevalence of atypical advanced interatrial block (A-AIB) (p 0.007) was detected among participants with AF, as well as the prevalence of P-wave <0.1mV. (p=0.006). All new diagnoses of AF were made at scores ≥4 in the MVP risk score.

CONCLUSIONS

Using scales for identifying ECG patterns in high-risk subjects in primary care can facilitate the diagnosis of unknown AF.

Early Diagnosis of Atrial Fibrillation and Stroke Incidence in Primary Care: Translating Measurements into Actions-A Retrospective Cohort Study

(1) Background: AF-related strokes will triple by 2060, are associated with an increased risk of cognitive decline, and alone or in combination, will be one of the main health and economic burdens on the European population. The main goal of this paper is to describe the incidence of new AF associated with stroke, cognitive decline and mortality among people at high risk for AF. (2) Methods: Multicenter, observational, retrospective, community-based studies were conducted from 1 January 2015 to 31 December 2021. The setting was primary care centers. A total of 40,297 people aged ≥65 years without previous AF or stroke were stratified by AFrisk at 5 years. The main measurements were the overall incidence density/1000 person-years (CI95%) of AF and stroke, prevalence of cognitive decline, and Kaplan-Meier curve. (3) Results: In total, 46.4% women, 77.65 ± 8.46 years old on average showed anAF incidence of 9.9/103/year (CI95% 9.5-10.3), associated with a four-fold higher risk of stroke (CI95% 3.4-4.7), cognitive impairment(OR 1.34 (CI95% 1.1-1.5)), and all-cause mortality (OR 1.14 (CI95% 1.0-1.2)), but there was no significant difference in ischemic heart disease, chronic kidney disease, or peripheral arteriopathy. Unknown AF was diagnosed in 9.4% and of these patients, 21.1% were diagnosed with new stroke. (4) Conclusions: The patients at high AF risk (Q4th) already had an increased cardiovascular risk before they were diagnosed with AF.

Risk of Atrial Fibrillation, Ischemic Stroke and Cognitive Impairment: Study of a Population Cohort ≥65 Years of Age

PURPOSE

To evaluate a model for calculating the risk of AF and its relationship with the incidence of ischemic stroke and prevalence of cognitive decline.

MATERIALS AND METHODS

It was a multicenter, observational, retrospective, community-based study of a cohort of general population ≥6ct 35 years, between 01/01/2016 and 31/12/2018. Setting: Primary Care. Participants: 46,706 people ≥65 years with an active medical history in any of the primary care teams of the territory, information accessible through shared history and without previous known AF. Interventions: The model to stratify the risk of AF (PI) has been previously published and included the variables sex, age, mean heart rate, mean weight and CHA2DS2VASc score. Main measurements: For each risk group, the incidence density/1000 person/years of AF and stroke, number of cases required to detect a new AF, the prevalence of cognitive decline, Kendall correlation, and ROC curve were calculated.

RESULTS

The prognostic index was obtained in 37,731 cases (80.8%) from lowest (Q1) to highest risk (Q4). A total of 1244 new AFs and 234 stroke episodes were diagnosed. Q3-4 included 53.8% of all AF and 69.5% of strokes in men; 84.2% of all AF and 85.4% of strokes in women; and 77.4% of cases of cognitive impairment. There was a significant linear correlation between the risk-AF score and the Rankin score (p < 0.001), the Pfeiffer score (p < 0.001), but not NIHSS score (p 0.150). The overall NNS was 1/19.

CONCLUSION

Risk stratification allows identifying high-risk individuals in whom to intervene on modifiable risk factors, prioritizing the diagnosis of AF and investigating cognitive status.

Incidence and Risk Assessment for Atrial Fibrillation at 5 Years: Hypertensive Diabetic Retrospective Cohort

(1) Background: The link between diabetes and hypertension is mutual and reciprocal, increasing the risks for the development of atrial fibrillation (AF). The main objective was to develop a prediction model for AF in a population with both diabetes and hypertension at five years of follow-up. (2) Methods: A multicenter and community-based cohort study was undertaken of 8237 hypertensive diabetic patients without AF between 1 January 2103 and 31 December 2017. Multivariate Cox proportional-hazards regression models were used to identify predictors AF and to stratify risk scores by quartiles. (3) Results: AF incidence was 10.5/1000 people/years (95% confidence interval (CI) 9.5-11.5), higher in men. The independent prognostic factors identified: age (hazard ratio (HR) 1.07 95% CI 1.05-1.09, p < 0.001), weight (HR 1.03 95% CI 1.02-1.04, p < 0.001), CHA2DS2VASc score (HR 1.57 95% CI 1.16-2.13, p = 0.003) and female gender (HR 0.55 95% CI 0.37-0.82, p = 0.004). Q4 (highest-risk group for AF) had the highest AF incidence, stroke and mortality, and the smallest number needed to screen to detect one case of AF. (4) Conclusions: Risk-based screening for AF should be used in high cardiovascular risk patients as the hypertensive diabetics, for treatment of modifiable cardiovascular risk, and monitoring AF detection.