Two automatic QT algorithms compared with manual measurement in identification of long QT syndrome

Diamant, Ulla-Britt; Winbo, Annika; Stattin, Eva-Lena; Rydberg, Annika; Kesek, Milos; Jensen, Steen M.

doi:10.1016/j.jelectrocard.2009.09.008

« Previous Next »Journal of Electrocardiology
Volume 43, Issue 1 , Pages 25-30, January 2010

Two automatic QT algorithms compared with manual measurement in identification of long QT syndrome

Ulla-Britt Diamant, MSc
- Heart Centre Clinical Physiology, Umeå University Hospital, Umeå, Sweden
- Department of Surgical and Perioperative Sciences, Umeå University Hospital, Umeå, Sweden
Annika Winbo, MD
- Division of Pediatric, Department of Clinical Sciences, Umeå University Hospital, Umeå, Sweden
Eva-Lena Stattin, MD, PhD
- Department of Medical Biosciences, Medical and Clinical Genetics, Umeå University Hospital, Umeå, Sweden
Annika Rydberg, MD, PhD
- Division of Pediatric, Department of Clinical Sciences, Umeå University Hospital, Umeå, Sweden
Milos Kesek, MD, PhD
- Heart Centre Cardiology, Umeå University Hospital, Umeå, Sweden
- Department of Public Health and Clinical Medicine, Umeå University Hospital, Umeå, Sweden
Steen M. Jensen, MD, PhD, FESC
- Heart Centre Cardiology, Umeå University Hospital, Umeå, Sweden
- Department of Public Health and Clinical Medicine, Umeå University Hospital, Umeå, Sweden
- Corresponding author. Department of Cardiology, Heart Centre, Umeå University Hospital, 901 85 Umeå, Sweden.

Received 6 February 2009

Abstract

Background

Long QT syndrome (LQTS) is an inherited disorder that increases the risk of syncope and malignant ventricular arrhythmias, which may result in sudden death.

Methods

We compared manual measurement by 4 observers (QT_manual) and 3 computerized measurements for QT interval accuracy in the diagnosis of LQTS:

1.QT measured from the vector magnitude calculated from the 3 averaged orthogonal leads X, Y, and Z (QT_VCG) and classified using the same predefined QTc cut-points for classification of QT prolongation as in manual measurements;

2.QT measured by a 12-lead electrocardiogram (ECG) program (QT_ECG) and subsequently classified using the same cut-points as in (1) above;

3.The same QT value as in (2) above, automatically classified by a 12-lead ECG program with thresholds for QT prolongation adjusted for age and sex (QT_interpret).

The population consisted of 94 genetically confirmed carriers of KCNQ1 (LQT1) and KCNH2 (LQT2) mutations and a combined control group of 28 genetically confirmed noncarriers and 66 unrelated healthy volunteers.

Results

QT_VCG provided the best combination of sensitivity (89%) and specificity (90%) in diagnosing LQTS, with 0.948 as the area under the receiver operating characteristic curve. The evaluation of QT measurement by the 4 observers revealed a high interreader variability, and only 1 of 4 observers showed acceptable level of agreement in LQTS mutation carrier identification (κ coefficient >0.75).

Conclusion

Automatic QT measurement by the Mida1000/CoroNet system (Ortivus AB, Danderyd, Sweden) is an accurate, efficient, and easily applied method for initial screening for LQTS.

Keywords: Long QT syndrome, QT interval, Automatic measurement, Vectorcardiography, Mutation analysis