Impaired T-amplitude adaptation to heart rate changes identifies IKr inhibition in the congenital and acquired form of the long QT syndrome

Impaired T-amplitude adaptation to heart rate changes identifies IKr inhibition in the congenital and acquired form of the long QT syndrome

Available online at www.sciencedirect.com Journal of Electrocardiology 40 (2007) S129 – S135 www.jecgonline.com Abstracts Poster Session 3 Impaired ...

99KB Sizes 0 Downloads 4 Views

Available online at www.sciencedirect.com

Journal of Electrocardiology 40 (2007) S129 – S135 www.jecgonline.com

Abstracts Poster Session 3 Impaired T-amplitude adaptation to heart rate changes identifies IKr inhibition in the congenital and acquired form of the long QT syndrome Jean-Philippe Couderc,a Martino Vaglio,a Xiajuan Xia,a Scott McNitt,a Pierre Wicker,b Nenad Sarapa,c Arthur J Moss,a Wojciech Zarebaa a Heart Research Follow-up Program, Cardiology Department, University of Rochester Medical Center, NY, USA b Pfizer Inc., Global Research and Development, CT, USA c Daiichi Sankyo Pharma Development, NJ, USA Background: The QTc interval prolongation is not a perfect surrogate marker of the presence of an increased risk for arrhythmic events. In the congenital form of the long QT syndrome (LQTS), 10% to 15% of patients carrying a HERG mutation do not have a prolongation of the QT interval. In the acquired form of the LQTS, polymorphic ventricular tachycardia is documented in individuals with Ikr-blocking drugs but without strong QT prolongation. Thus, we investigated the role of repolarization adaptation to heart rate changes for identifying the presence of abnormal Ikr kinetics in the congenital and acquired form of the LQTS. Method: Our investigation is based on 5 study groups: genotyped LQT1 patients (n = 49, 35♀), genotyped LQT2 (n = 25, 19♀), healthy individuals (n = 37, 11♀) on and off sotalol including a single dose (SD; 160 mg; n = 37) and a double dose (DD; 320 mg, n = 21). Twelve-lead digital Holter recordings were acquired in LQTS patients and during periods on and off drug in the healthy groups. Median beat analysis was performed in all leads during the diurnal period. We investigated various repolarization parameters and their heart rate dependency including QT interval and T-wave amplitude. Results: The results from lead II reveal a loss of heart rate dependency of the amplitude of the T wave as a common feature in individuals with decreased Ikr kinetics (LQT2 and subjects under sotalol).The Table provides the values of T amplitude/RR and QT/RR slopes in all groups. Conclusion: Impaired adaptation of T-wave amplitude has been evidenced as common electrocardiographic feature associated with HERG mutation and Ikr-blocking drug sotalol. This electrocardiogram marker may play an important role in the future of assessment of both the penetrance of HERG mutation and the Ikr-related cardiotoxicity of drugs.

Using the European Society of cardiology ST database to compare 2 automated methods for ST episode measurement Dirk Feild Advanced Algorithm Research Center, Philips Medical Systems, Thousand Oaks CA Background: An effective way to evaluate ST measurements and episodes is critically needed. One solution is the European Society of Cardiology's (ESC)

a b

Algorithm method

Episode Se (%)

Episode +P (%)

Duration Se (%)

Duration +P (%)

Post averaging Pre averaging

96 98

91 92-96 a

91 94

85 83

a

≥Both.

Conclusions: The ESC ST database was an effective tool in showing the superiority of smoothing before measuring the baseline corrected ECG in this application.

doi:10.1016/j.jelectrocard.2007.08.043

QT/RR T amplitude/RR (μV/ms)

ST Database. As supplied, this database fails to fully meet the evaluator's needs. There are multiple reasons for this mismatch. With supplemental processing, however, the database can be turned into an effective evaluation tool. The limitations of the database include (1) a method for establishing a baseline that fails to match practical use models, (2) sparse ST measurements, (3) fixed episode criteria, (4) shortness of records, and (5) atypically clean records. Of all these issues, only the first is critical. The database defines ST episodes relative to a baseline measurement typically taken from the first beat of the record. No practical computer algorithm would take this approach. ST measurements are inherently sensitive to numerous sources of artifact. Baseline wander, muscle artifact, electrode noise, and positional changes particularly affect measurements significantly. Various filtering methods are used in a practical system to overcome these issues. Clinical algorithms will therefore invariably measure a filtered ST baseline value distant from the first beat. Differences in this one measurement will then apply to all other measurements, effectively destroying episode evaluation. Methods: To overcome this “one measurement/use model” problem, a DC offset is applied to each channel of each record in the database. This correction is fixed throughout all measurements and all episodes in that record. The DC offset is chosen to minimize the total nonoverlap time of the reference and test episodes, effectively canceling the impact of the initial reference measurement. In this work, we compare 2 methods of automated ST-interval measurement implemented in the Philips Holter application: (1) measure the raw baseline wander corrected electrocardiogram (ECG) and then smooth the measurements, and (2) average the beats (baseline wander corrected ECG) then measure the result. In each case, the ESC database is used to independently evaluate performance. Results: Combined channels Gross measurements (as if 1 record):

doi:10.1016/j.jelectrocard.2007.08.044 Automated determination of spatial QT interval distribution in cardiac magnetic field mapping reveals repolarization inhomogeneities in highrisk patients Robert Fischer,a Vinzenz von Tscharner,b Andrej Gapelyuk,a Udo Zacharzowsky,a Henry Schutt,a Alexander Schirdewana

Healthy (n = 39)

LQT1 (n = 49)

LQT2 (n = 25)

SD sotalol (n = 37)

DD sotalol (n = 21)

0.12 ± 0.04 0.55 ± 0.29

0.17 ± 0.10 a 0.62 ± 0.40

0.22 ± 0.16 a 0.31 ± 0.27a,b

0.15 ± 0.05 a 0.26 ± 0.19a,b

0.14 ± 0.06 0.21 ± 0.14a,b

P b .05 in reference to healthy. P b .05 in reference to LQT1.

0022-0736/$ – see front matter doi:10.1016/j.jelectrocard.2007.08.042