{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T13:18:48Z","timestamp":1789996728183,"version":"4.0.1"},"reference-count":44,"publisher":"Wiley","issue":"11","license":[{"start":{"date-parts":[[2010,10,29]],"date-time":"2010-10-29T00:00:00Z","timestamp":1288310400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cardiovasc electrophysiol"],"published-print":{"date-parts":[[2010,11]]},"abstract":"<jats:p><jats:bold>Quantitative ECG Analysis<\/jats:bold>.\u2002<jats:italic>Introduction:<\/jats:italic>Optimal atrial tachyarrhythmia management is facilitated by accurate electrocardiogram interpretation, yet typical atrial flutter (AFl) may present without sawtooth F\u2010waves 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.<\/jats:p><jats:p><jats:italic>Methods and Results:<\/jats:italic>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 \u00b1 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 &lt; 0.01). Economically, we found that these improvements in diagnostic accuracy resulted in an average cost\u2010savings of $1,303 and 0.007 quality\u2010adjusted\u2010life\u2010years per patient.<\/jats:p><jats:p><jats:italic>Conclusions:<\/jats:italic>Typical AFl and AF are frequently misdiagnosed using visual criteria. Quantitative analysis improves diagnostic accuracy and results in improved healthcare costs and patient outcomes.<jats:italic>(J Cardiovasc Electrophysiol, Vol. 21, pp. 1251\u20101259, November 2010)<\/jats:italic><\/jats:p>","DOI":"10.1111\/j.1540-8167.2010.01809.x","type":"journal-article","created":{"date-parts":[[2010,5,28]],"date-time":"2010-05-28T17:20:22Z","timestamp":1275067222000},"page":"1251-1259","source":"Crossref","is-referenced-by-count":20,"title":["Accurate ECG Diagnosis of Atrial Tachyarrhythmias Using Quantitative Analysis: A Prospective Diagnostic and Cost\u2010Effectiveness Study"],"prefix":"10.1111","volume":"21","author":[{"given":"DAVID 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