Differentiation between LQT1 and LQT2 patients and unaffected subjects using 24-hour electrocardiographic recordings

M Viitasalo, L Oikarinen, H Väänänen, H Swan… - The American journal of …, 2002 - Elsevier
M Viitasalo, L Oikarinen, H Väänänen, H Swan, K Piippo, K Kontula, HV Barron, L Toivonen…
The American journal of cardiology, 2002Elsevier
This study assesses the use of 24-hour ambulatory electrocardiographic recordings in
distinguishing patients with long-QT1 syndrome (LQT1) from those with LQT2, and for
distinguishing affected from unaffected patients. The diagnoses of the congenital LQT
syndrome and its most common types LQT1 and LQT2 are made difficult because of the
limitations of the electrocardiogram as a diagnostic tool. With an automated computerized
program, Holter recordings from 15 LQT1 and 15 LQT2 patients and 43 healthy subjects …
This study assesses the use of 24-hour ambulatory electrocardiographic recordings in distinguishing patients with long-QT1 syndrome (LQT1) from those with LQT2, and for distinguishing affected from unaffected patients. The diagnoses of the congenital LQT syndrome and its most common types LQT1 and LQT2 are made difficult because of the limitations of the electrocardiogram as a diagnostic tool. With an automated computerized program, Holter recordings from 15 LQT1 and 15 LQT2 patients and 43 healthy subjects (training set) were reviewed to select the best criteria using QT duration and rate dependence as well as the difference between QT end and QT apex to separate the 3 groups. Fixed criteria were then applied in blinded fashion to separate a different group of 32 genotyped patients and 16 unaffected subjects (test set). In the training set, the RR interval (100 ms), a slope value for median QT/RR curves of −0.016 separated 25 of 30 (83%) and a minimal QT end − QT apex value of 80 ms, separated 26 of 30 (87%) LQT1 patients from LQT2 patients. When all selected criteria were applied to differentiate LQT1 from LQT2 versus unaffected genotypes in the test set, 38 of 48 cases (79%) were correctly identified, whereas using the electrocardiogram alone, 60% of patients were correctly classified into 3 genotypes (p = 0.03). Combining measures for QT duration, rate dependence, and QT end − QT apex interval, derived from Holter recordings, complements the clinical differentiation between LQT1 versus LQT2 patients and between affected and unaffected persons for genotype screening purposes.
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