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J Cardiovasc Electrophysiol. 2010 Nov;21(11):1251-9. doi: 10.1111/j.1540-8167.2010.01809.x.

Accurate ECG diagnosis of atrial tachyarrhythmias using quantitative analysis: a prospective diagnostic and cost-effectiveness study.

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1
University of California San Diego, San Diego, California, USA. dkrummen@ucsd.edu

Abstract

Quantitative ECG Analysis.

INTRODUCTION:

Optimal atrial tachyarrhythmia management is facilitated by accurate electrocardiogram interpretation, yet typical atrial flutter (AFl) may present without sawtooth F-waves or RR regularity, and atrial fibrillation (AF) may be difficult to separate from atypical AFl or rapid focal atrial tachycardia (AT). We analyzed whether improved diagnostic accuracy using a validated analysis tool significantly impacts costs and patient care.

METHODS AND RESULTS:

We performed a prospective, blinded, multicenter study using a novel quantitative computerized algorithm to identify atrial tachyarrhythmia mechanism from the surface ECG in patients referred for electrophysiology study (EPS). In 122 consecutive patients (age 60 ± 12 years) referred for EPS, 91 sustained atrial tachyarrhythmias were studied. ECGs were also interpreted by 9 physicians from 3 specialties for comparison and to allow healthcare system modeling. Diagnostic accuracy was compared to the diagnosis at EPS. A Markov model was used to estimate the impact of improved arrhythmia diagnosis. We found 13% of typical AFl ECGs had neither sawtooth flutter waves nor RR regularity, and were misdiagnosed by the majority of clinicians (0/6 correctly diagnosed by consensus visual interpretation) but correctly by quantitative analysis in 83% (5/6, P = 0.03). AF diagnosis was also improved through use of the algorithm (92%) versus visual interpretation (primary care: 76%, P < 0.01). Economically, we found that these improvements in diagnostic accuracy resulted in an average cost-savings of $1,303 and 0.007 quality-adjusted-life-years per patient.

CONCLUSIONS:

Typical AFl and AF are frequently misdiagnosed using visual criteria. Quantitative analysis improves diagnostic accuracy and results in improved healthcare costs and patient outcomes.

PMID:
20522152
PMCID:
PMC2970682
DOI:
10.1111/j.1540-8167.2010.01809.x
[Indexed for MEDLINE]
Free PMC Article
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