Automated Quantification of QT-Intervals by an Algorithm: A Validation Study in Patients with Chronic Obstructive Pulmonary Disease

Abstract

Dario Kohlbrenner,1,2 Maya Bisang,1 Sayaka S Aeschbacher,1 Emanuel Heusser,1 Silvia Ulrich,1,2 Konrad E Bloch,1,2 Michael Furian1,3 1Department of Pulmonology, University Hospital Zurich, Zurich, Switzerland; 2Faculty of Medicine, University of Zurich, Zurich, Switzerland; 3Swiss University of Traditional Chinese Medicine, Bad Zurzach, SwitzerlandCorrespondence: Michael Furian, Department of Pulmonology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland, Email [email protected] Objectives: To assess the diagnostic accuracy of a purpose-designed QTc-scoring algorithm versus the established hand-scoring in patients with chronic obstructive pulmonary disease (COPD) undergoing sleep studies.Methods: We collected 62 overnight electrocardiogram (ECG) recordings in 28 COPD patients. QT-intervals corrected for heart rate (QTc, Bazett) were averaged over 1-min periods and quantified, both by the algorithm and by cursor-assisted hand-scoring. Hand-scoring was done blinded to the algorithm-derived results. Bland-Altman statistics and confusion matrixes for three thresholds (460, 480, and 500ms) were calculated.Results: A total of 32944 1-min periods and corresponding mean QTc-intervals were analysed manually and by computer. Mean difference between manual and algorithm-based QTc-intervals was − 1ms, with limits of agreement of − 18 to 16ms. Overall, 2587 (8%), 357 (1%), and 0 QTc-intervals exceeding the threshold 460, 480, and 500ms, respectively, were identified by hand-scoring. Of these, 2516, 357, and 0 were consistently identified by the algorithm. This resulted in a diagnostic classification accuracy of 0.98 (95% CI 0.98/0.98), 1.00 (1.00/1.00), and 1.00 (1.00/1.00) for 460, 480, and 500ms, respectively. Sensitivity was 0.97, 1.00, and NA for 460, 480, and 500ms, respectively. Specificity was 0.98, 1.00, and 1.00 for 460, 480, and 500ms, respectively.Conclusion: Overall, 8% of nocturnal 1-min periods showed clinically relevant QTc prolongations in patients with stable COPD. The automated QTc-algorithm accurately identified clinically relevant QTc-prolongations with a very high sensitivity and specificity. Using this tool, hospital sleep laboratories may identify asymptomatic patients with QTc-prolongations at risk for malignant arrhythmia, allowing them to consult a cardiologist before an eventual cardiac event.Keywords: QTc, long-QT syndrome, COPD, algorithm, validity, ECG

Keywords

• qtc
• long-qt syndrome
• copd
• algorithm
• validity
• ecg