Advanced electrocardiographic predictors of mortality in familial dysautonomia

National Space Biomedical Research Institute, Houston, Texas, USAA.
Autonomic neuroscience: basic & clinical (Impact Factor: 1.56). 11/2008; 144(1-2):76-82. DOI: 10.1016/j.autneu.2008.08.016
Source: PubMed


To identify electrocardiographic predictors of mortality in patients with familial dysautonomia (FD).
Ten-minute resting high-fidelity 12-lead electrocardiograms (ECGs) were obtained from 14 FD patients and 14 age/gender-matched healthy subjects. Multiple conventional and advanced ECG parameters were studied for their ability to predict mortality over a subsequent 4.5-year period, including representative parameters of heart rate variability (HRV), QT variability (QTV), T-wave complexity, signal averaged ECG, and 3-dimensional ECG.
Four of the 14 FD patients died during the follow-up period, three with concomitant pulmonary disorder. Of the ECG parameters studied, increased non-HRV-correlated QTV and decreased HRV were the most predictive of death. Compared to controls as a group, FD patients also had significantly increased ECG voltages, JTc intervals and waveform complexity, suggestive of structural heart disease.
Increased QTV and decreased HRV are markers for increased risk of death in FD patients. When present, both markers may reflect concurrent pathological processes, especially hypoxia due to pulmonary disorders and sleep apnea.

1 Follower
11 Reads
  • Source
    • "While progress towards QTV analysis in clinical applications is being made [5], [14], [15], [16], [17], [18], [19], it is still constrained by insufficient formalisation of the QTV measurement process. This emphasises need for further investigations on the performance and reliability of different QT measurement algorithms [20], [21]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Increased beat-to-beat variability in the QT interval (QTV) of ECG has been associated with increased risk for sudden cardiac death, but its measurement is technically challenging and currently not standardized. The aim of this study was to investigate the performance of commonly used beat-to-beat QT interval measurement algorithms. Three different methods (conventional, template stretching and template time shifting) were subjected to simulated data featuring typical ECG recording issues (broadband noise, baseline wander, amplitude modulation) and real short-term ECG of patients before and after infusion of sotalol, a QT interval prolonging drug. Among the three algorithms, the conventional algorithm was most susceptible to noise whereas the template time shifting algorithm showed superior overall performance on simulated and real ECG. None of the algorithms was able to detect increased beat-to-beat QT interval variability after sotalol infusion despite marked prolongation of the average QT interval. The QTV estimates of all three algorithms were inversely correlated with the amplitude of the T wave. In conclusion, template matching algorithms, in particular the time shifting algorithm, are recommended for beat-to-beat variability measurement of QT interval in body surface ECG. Recording noise, T wave amplitude and the beat-rejection strategy are important factors of QTV measurement and require further investigation.
    PLoS ONE 07/2012; 7(7):e41920. DOI:10.1371/journal.pone.0041920 · 3.23 Impact Factor
  • Source
    • "Several parameters of 256-beat RRV and QTV described in previous publications[17,31,34] were again evaluated via custom software programs[17]. These included the QT variability index (QTVI), but using the means and variances of the RR interval[15] rather than those of the heart rate[14] in the denominator of the QTVI equation, and the "unexplained" part of QTV[31,34]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Resting conventional 12-lead ECG has low sensitivity for detection of coronary artery disease (CAD) and left ventricular hypertrophy (LVH) and low positive predictive value (PPV) for prediction of left ventricular systolic dysfunction (LVSD). We hypothesized that a approximately 5-min resting 12-lead advanced ECG test ("A-ECG") that combined results from both the advanced and conventional ECG could more accurately screen for these conditions than strictly conventional ECG. Results from nearly every conventional and advanced resting ECG parameter known from the literature to have diagnostic or predictive value were first retrospectively evaluated in 418 healthy controls and 290 patients with imaging-proven CAD, LVH and/or LVSD. Each ECG parameter was examined for potential inclusion within multi-parameter A-ECG scores derived from multivariate regression models that were designed to optimally screen for disease in general or LVSD in particular. The performance of the best retrospectively-validated A-ECG scores was then compared against that of optimized pooled criteria from the strictly conventional ECG in a test set of 315 additional individuals. Compared to optimized pooled criteria from the strictly conventional ECG, a 7-parameter A-ECG score validated in the training set increased the sensitivity of resting ECG for identifying disease in the test set from 78% (72-84%) to 92% (88-96%) (P < 0.0001) while also increasing specificity from 85% (77-91%) to 94% (88-98%) (P < 0.05). In diseased patients, another 5-parameter A-ECG score increased the PPV of ECG for LVSD from 53% (41-65%) to 92% (78-98%) (P < 0.0001) without compromising related negative predictive value. Resting 12-lead A-ECG scoring is more accurate than strictly conventional ECG in screening for CAD, LVH and LVSD.
    BMC Cardiovascular Disorders 06/2010; 10(1):28. DOI:10.1186/1471-2261-10-28 · 1.88 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Twelve-lead electrocardiogram (ECG) is used to screen for hypertrophic cardiomyopathy (HCM), but up to 25% of HCM patients do not have distinctly abnormal ECGs, whereas up to 5% to 15% of healthy athletes do. We hypothesized that an approximately 5-minute resting advanced 12-lead ECG test ("A-ECG score") could detect HCM with greater sensitivity than pooled conventional ECG criteria and distinguish healthy athletes from HCM with greater specificity. Five-minute 12-lead ECGs were obtained from 56 HCM patients, 56 age/sex-matched healthy controls, and 69 younger endurance-trained athletes. Electrocardiograms were analyzed using recently suggested pooled conventional ECG criteria and also A-ECG scoring techniques that considered results from multiple advanced and conventional ECG parameters. Compared with pooled criteria from the strictly conventional ECG, an A-ECG logistic score incorporating results from just 3 advanced ECG parameters (spatial QRS-T angle, unexplained portion of QT variability, and T-wave principal component analysis ratio) increased the sensitivity of ECG for identifying HCM from 89% (78%-96%) to 98% (89%-100%; P = .025), while increasing specificity from 90% (83%-94%) to 95% (92%-99%; P = .020). Resting 12-lead A-ECG scores that are simultaneously more sensitive than pooled conventional ECG criteria for detecting HCM and more specific for distinguishing healthy athletes and other healthy controls from HCM can be constructed. Pending further prospective validation, such scores may lead to improved ECG-based screening for HCM.
    Journal of electrocardiology 11/2010; 43(6):713-8. DOI:10.1016/j.jelectrocard.2010.08.010 · 1.36 Impact Factor
Show more