title: Accuracy of methods for diagnosing atrial fibrillation using 12-lead ECG: A systematic review and meta-analysis.
abstract: 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.
authors.affiliation: University of Nottingham, United Kingdom. Electronic address: Jaspal.taggar@nottingham.ac.uk.
authors.forename: Jaspal S
authors.initials: JS
authors.lastname: Taggar
authors.affiliation: University of Nottingham, United Kingdom.
authors.forename: Tim
authors.initials: T
authors.lastname: Coleman
authors.affiliation: University of Nottingham, United Kingdom.
authors.forename: Sarah
authors.initials: S
authors.lastname: Lewis
authors.affiliation: Universoty of Oxford, United Kingdom.
authors.forename: Carl
authors.initials: C
authors.lastname: Heneghan
authors.affiliation: University of Nottingham, United Kingdom.
authors.forename: Matthew
authors.initials: M
authors.lastname: Jones
mesh_terms: D001281:Atrial Fibrillation / Q000175:diagnosis* / Q000503:physiopathology*; D004562:Electrocardiography / Q000295:instrumentation* / Q000592:standards*; D006801:Humans; D012984:Software / Q000592:standards
keywords: Atrial fibrillation; Diagnostic accuracy; Electrocardiogram