Diagnostic accuracy of digital technologies compared with 12-lead ECG in the diagnosis of atrial fibrillation in adults: A protocol for a systematic review.

BACKGROUND: Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia in the world. AF increases the risk of stroke 5-fold, though the risk can be reduced with appropriate treatment. Therefore, early diagnosis is imperative but remains a global challenge. In low-and middle-income countries (LMICs), a lack of diagnostic equipment and under-resourced healthcare systems generate further barriers. The rapid development of digital technologies that are capable of diagnosing AF remotely and cost-effectively could prove beneficial for LMICs. However, evidence is lacking on what digital technologies exist and how they compare in regards to diagnostic accuracy. We aim to systematically review the diagnostic accuracy of all digital technologies capable of AF diagnosis. METHODS: MEDLINE, Embase and Web of Science will be searched for eligible studies. Free text terms will be combined with corresponding index terms where available and searches will not be limited by language nor time of publication. Cohort or cross-sectional studies comprising adult (≥18 years) participants will be included. Only studies that use a 12-lead ECG as the reference test (comparator) and report outcomes of sensitivity, specificity, the diagnostic odds ratio (DOR) or the positive and negative predictive value (PPV and NPV) will be included (or if they provide sufficient data to calculate these outcomes). Two reviewers will independently assess articles for inclusion, extract data using a piloted tool and assess risk of bias using the QUADAS-2 tool. The feasibility of a meta-analysis will be determined by assessing heterogeneity across the studies, grouped by index device, diagnostic threshold and setting. If a meta-analysis is feasible for any index device, pooled sensitivity and specificity will be calculated using a random effect model and presented in forest plots. DISCUSSION: The findings of our review will provide a comprehensive synthesis of the diagnostic accuracy of available digital technologies capable for diagnosing AF. Thus, this review will aid in the identification of which devices could be further trialed and implemented, particularly in a LMIC setting, to improve the early diagnosis of AF. TRIAL REGISTRATION: Systematic review registration: PROSPERO registration number is CRD42021290542. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021290542.

Early rhythm control on diabetes-related complications and mortality in patients with type 2 diabetes mellitus and atrial fibrillation.

AIMS: We evaluated the impact of early rhythm control (ERC) on diabetes-related complications and mortality in subjects with type 2 diabetes mellitus (T2DM) and atrial fibrillation (AF). METHODS: This observational cohort study based on the Korean National Health Insurance Service claims database from 2009 to 2016, divided newly diagnosed AF patients with T2DM into ERC or usual care groups based on receiving rhythm control treatment within 1 year of AF diagnosis. The primary outcome was ischemic stroke, and the secondary outcomes were macro/microvascular complications, and all-cause death. RESULTS: Among 47,509 subjects (mean age 66.7 ± 10.5 years; 61.8 % men; mean CHA2DS2-VASc score 4.6 ± 1.8; mean follow-up 4.3 ± 2.3 years; mean DM duration 5.6 ± 4.7 years), 23.1 % received ERC, and 76.9 % did not (usual care group). ERC was associated with lower risks of ischemic stroke, macrovascular and microvascular complications, and all-cause death compared to usual care (adjusted hazard ratios [95 % confidence interval]: 0.77 [0.70-0.85], 0.79 [0.73-0.86], 0.86 [0.82-0.90], and 0.92 [0.87-0.98], p < 0.001, <0.001, <0.001, and 0.012, respectively). CONCLUSIONS: Early rhythm control was associated with reduced risks of diabetes-related complications and mortality in subjects with T2DM and AF. Rhythm control within 1 year of AF diagnosis with proper anticoagulation should be considered to prevent adverse outcomes.

Phenotypes and outcomes in non-anticoagulated patients with atrial fibrillation: An unsupervised cluster analysis.

BACKGROUND: Patients with atrial fibrillation are characterized by great clinical heterogeneity and complexity. The usual classifications may not adequately characterize this population. Data-driven cluster analysis reveals different possible patient classifications. AIMS: To identify different clusters of patients with atrial fibrillation who share similar clinical phenotypes, and to evaluate the association between identified clusters and clinical outcomes, using cluster analysis. METHODS: An agglomerative hierarchical cluster analysis was performed in non-anticoagulated patients from the Loire Valley Atrial Fibrillation cohort. Associations between clusters and a composite outcome comprising stroke/systemic embolism/death and all-cause death, stroke and major bleeding were evaluated using Cox regression analyses. RESULTS: The study included 3434 non-anticoagulated patients with atrial fibrillation (mean age 70.3±17 years; 42.8% female). Three clusters were identified: cluster 1 was composed of younger patients, with a low prevalence of co-morbidities; cluster 2 included old patients with permanent atrial fibrillation, cardiac pathologies and a high burden of cardiovascular co-morbidities; cluster 3 identified old female patients with a high burden of cardiovascular co-morbidities. Compared with cluster 1, clusters 2 and 3 were independently associated with an increased risk of the composite outcome (hazard ratio 2.85, 95% confidence interval 1.32-6.16 and hazard ratio 1.52, 95% confidence interval 1.09-2.11, respectively) and all-cause death (hazard ratio 3.54, 95% confidence interval 1.49-8.43 and hazard ratio 1.88, 95% confidence interval 1.26-2.79, respectively). Cluster 3 was independently associated with an increased risk of major bleeding (hazard ratio 1.72, 95% confidence interval 1.06-2.78). CONCLUSION: Cluster analysis identified three statistically driven groups of patients with atrial fibrillation, with distinct phenotype characteristics and associated with different risks for major clinical adverse events.