This study compared spontaneous baroreflex sensitivity (BRS) estimates obtained from an identical set of data by 11 European centers using different methods and procedures. Noninvasive blood pressure (BP) and ECG recordings were obtained in 21 subjects, including 2 subjects with established baroreflex failure. Twenty-one estimates of BRS were obtained by methods including the two main techniques of BRS estimates, i.e., the spectral analysis (11 procedures) and the sequence method (7 procedures) but also one trigonometric regressive spectral analysis method (TRS), one exogenous model with autoregressive input method (X-AR), and one Z method. With subjects in a supine position, BRS estimates obtained with calculations of alpha-coefficient or gain of the transfer function in both the low-frequency band or high-frequency band, TRS, and sequence methods gave strongly related results. Conversely, weighted gain, X-AR, and Z exhibited lower agreement with all the other techniques. In addition, the use of mean BP instead of systolic BP in the sequence method decreased the relationships with the other estimates. Some procedures were unable to provide results when BRS estimates were expected to be very low in data sets (in patients with established baroreflex failure). The failure to provide BRS values was due to setting of algorithmic parameters too strictly. The discrepancies between procedures show that the choice of parameters and data handling should be considered before BRS estimation. These data are available on the web site (http://www.cbi.polimi.it/glossary/eurobavar.html) to allow the comparison of new techniques with this set of results.

Background-Congenital heart disease represents the most common severe birth defect, affecting 0.7% to 1% of all neonates, among whom 5% to 7% display transposition of the great arteries (TGA). TGA represents a septation defect of the common outflow tract of the heart, manifesting around the fifth week during embryonic development. Despite its high prevalence, very little is known about the pathogenesis of this disease. Methods and Results-Using a positional cloning approach, we isolated a novel gene, PROSIT240 (also termed THRAP2), that is interrupted in a patient with a chromosomal translocation and who displays TGA and mental retardation. High expression of PROSIT240 within the heart (aorta) and brain (cerebellum) was well correlated with the malformations observed in the patient and prompted further analyses. PROSIT240 shows significant homology to the nuclear receptor coactivator TRAP240, suggesting it to be a new component of the thyroid hormone receptor-associated protein (TRAP) complex. Interestingly, several TRAP components have been previously shown to be important in early embryonic development in various organisms, making PROSIT240 an excellent candidate gene to be correlated to the patient's phenotype. Subsequent mutational screening of 97 patients with isolated dextro-looped TGA revealed 3 missense mutations in PROSIT240, which were not detected in 400 control chromosomes. Conclusions-Together, these genetic data suggest that PROSIT240 is involved in early heart and brain development.

Spectral analysis of heart rate variability (HRV) is a valuable tool for the assessment of cardiovascular autonomic function. Fast Fourier transform and autoregressive based spectral analysis are two most commonly used approaches for HRV analysis, while new techniques such as trigonometric regressive spectral (TRS) and wavelet transform have been developed. Short-term (on ECG of several minutes) and long-term (typically on ECG of 1–24 h) HRV analyses have different advantages and disadvantages. This article reviews the characteristics of spectral HRV studies using different lengths of time windows. Short-term HRV analysis is a convenient method for the estimation of autonomic status, and can track dynamic changes of cardiac autonomic function within minutes. Long-term HRV analysis is a stable tool for assessing autonomic function, describe the autonomic function change over hours or even longer time spans, and can reliably predict prognosis. The choice of appropriate time window is essential for research of autonomic function using spectral HRV analysis.

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