Accuracy of methods for diagnosing atrial fibrillation using 12-lead ECG: a systematic review and meta-analysis

Background: Screening for atrial fibrillation (AF) using 12-lead-electrocardiograms (ECGs) has been recommended; however, the best method for interpreting ECGs to diagnose AF is not known. We compared accuracy of methods for diagnosing AF from ECGs. Methods: We searched MEDLINE, EMBASE, CINAHL and LILACS until March 24, 2014. Two reviewers identified eligible studies, extracted data and appraised quality using the QUADAS-2 instrument. Meta-analysis, using the bivariate hierarchical random effects method, determined average operating points for sensitivities, specificities, positive and negative likelihood ratios (PLR, NLR) and enabled construction of Summary Receiver Operating Characteristic (SROC) plots. Results: 10 studies investigated 16 methods for interpreting ECGs (n = 55,376 participant ECGs). The sensitivity and specificity of automated software (8 studies; 9 methods) were 0.89 (95% C.I. 0.82–0.93) and 0.99 (95% C.I. 0.99–0.99), respectively; PLR 96.6 (95% C.I. 64.2–145.6); NLR 0.11 (95% C.I. 0.07–0.18). Indirect comparisons with software found healthcare professionals (5 studies; 7 methods) had similar sensitivity for diagnosing AF but lower specificity [sensitivity 0.92 (95% C.I. 0.81–0.97), specificity 0.93 (95% C.I. 0.76–0.98), PLR 13.9 (95% C.I. 3.5–55.3), NLR 0.09 (95% C.I. 0.03–0.22)]. Sub-group analyses of primary care professionals found greater specificity for GPs than nurses [GPs: sensitivity 0.91 (95% C.I. 0.68–1.00); specificity 0.96 (95% C.I. 0.89–1.00). Nurses: sensitivity 0.88 (95% C.I. 0.63–1.00); specificity 0.85 (95% C.I. 0.83–0.87)]. Conclusions: Automated ECG-interpreting software most accurately excluded AF, although its ability to diagnose this was similar to all healthcare professionals. Within primary care, the specificity of AF diagnosis from ECG was greater for GPs than nurses

Ejection fraction and outcomes in patients with atrial fibrillation and heart failure: the Loire Valley Atrial Fibrillation Project

Heart failure (HF) increases the risk of stroke and thrombo-embolism (TE) in non-valvular atrial fibrillation (NVAF), and is incorporated in stroke risk stratification scores. We aimed to establish the role of ejection fraction (EF) in risk prediction in patients with NVAF and HF. Patients with NVAF, history of HF, and measured EF were included in a retrospective analysis. Patients with HF and preserved ejection fraction (HFPEF) were defined as those with clinical HF and EF epsilon 50 in this study. Among 7156 patients with NVAF, 1276 (17.8) patients with HF and measured EF were included. Of these, 747/1276 (58.5) patients were on vitamin K antagonists. The stroke/TE event rate per 100 person-years was 1.05 [95 confidence interval (CI) 0.871.25]. Patients with HFPEF were more likely to be female (P 0.001), older (P 0.001), and hypertensive (P 0.001), and less likely to have prior vascular disease (P 0.001). There were no differences in rates of stroke (P 0.17) and stroke/TE (P 0.11) between patients with HFPEF and those with HF and reduced EF. There were no significant differences in rates of all-cause mortality when patients were stratified by EF. In multivariate analyses, only previous stroke (hazard ratio 2.36, 95 CI 1.453.86) and vascular disease (1.57, 1.072.30) increased the risk of stroke/TE amongst NVAF patients with HF, but EF 35 did not (0.75, 0.441.30). In NVAF patients with HF, there were no differences in rates of stroke, TE, or death between EF categories. Only previous stroke and vascular disease (and not decreased EF) independently increased risk of stroke/TE in multivariate analyses

Evaluation of risk stratification schemes for ischaemic stroke and bleeding in 182 678 patients with atrial fibrillation: the Swedish Atrial Fibrillation cohort study

The impact of some risk factors for stroke and bleeding, and the value of stroke and bleeding risk scores, in atrial fibrillation (AF), has been debated, as clinical trial cohorts have not adequately tested these. Our objective was to investigate risk factors for stroke and bleeding in AF, and application of the new CHA(2)DS(2)-VASc and HAS-BLED schemes for stroke and bleeding risk assessments, respectively

The risk stratification in atrial fibrillation

Atrial fibrillation (AF) is the most common rhythm disorder and represents a major public health problem because it carries an increased risk of arterial thromboembolism and ischemic stroke. Because the absolute benefit of antithrombotic therapy depends on the underlying risk of stroke, an accurate stratification of patients' risk is needed to choose the appropriate antithrombotic strategy. Over the years, several stroke risk stratification models (RSMs) were developed based on the 'classic' risk factors for stroke such as increasing age, hypertension, diabetes mellitus, and left ventricular dysfunction. Among all RSMs, the CHADS(2) score is the most popular and used one thanks to its simplicity and endorsement in several widely promulgated practice guidelines. Despite its validation in large datasets and specific population of AF patients, it has many limitations, especially due to the non-inclusion of several proven risk factors for stroke and to the classification of a large number of patients in the intermediate risk category, so creating ambiguity over the most appropriate antithrombotic therapy. Thus, the CHA(2)DS(2)-VASc score was introduced and was demonstrated to perform better than the CHADS(2), even in a "real world" population of elderly AF patients. Recently, in view of the availability of new oral anticoagulant drugs, that can overcome the limitations of warfarin and allow a more personalized therapy, many efforts are being made to identify other possibilities to assess the thromboembolic risk in AF patients. It has been demonstrated that an increase in C-reactive protein and interleukin-6 and the presence of G20210A factor II gene polymorphism and hyper-homocysteinemia are independent risk factors for ischemic complications in AF patients. Even the presence of chronic renal disease and the daily AF burden, registered with implantable monitors, are associated with an increase risk of stroke. Finally, the assessment of thromboembolic risk should go hand in hand with the consideration of the risk of bleeding. For this purpose, it has been recently developed a practical bleeding risk score, the HAS-BLED, which was included in the last ESC guidelines for the risk stratification of AF patients before starting anticoagulant therapy