Heart rate turbulence during acute alcohol withdrawal syndrome.

BACKGROUND: Alcohol withdrawal syndrome is associated with an increased incidence of cardiac arrhythmias and sudden cardiac death. Heart rate turbulence (HRT) parameters were applied during withdrawal to estimate cardiac regulation during treatment with clomethiazole. METHODS: Twenty-two patients suffering from alcohol withdrawal syndrome were included in the study. Heart rate regulation was obtained by means of Holter ECG analyzing time intervals before medication, and 2 and 6h after medication. Slope and onset of HRT were calculated in addition to heart rate variability (HRV) parameters. Furthermore, we calculated the slope and the onset of ectopic beat-like events. RESULTS: Heart rate variability parameters indicated a minor reduction of vagal modulation during withdrawal syndrome. Especially, the fractal scaling exponent BBI alpha1 (4-16) indicated the autonomic shift. In contrast to HRV parameters, no significant changes were observed in the HRT parameters. Significant correlations were observed between severity of withdrawal, as assessed by the AWS scale, and the fractal scaling exponent BBI alpha2 (16-64), and the onset and the slope of HRT of ectopic beat-like activity. CONCLUSION: Increased sympathetic modulation during withdrawal and clomethiazole treatment is not associated with changes of heart rate turbulence parameters predictive of cardiac death after myocardial infarction.

Automatic detection of microemboli during percutaneous coronary interventions.

The objective of this study was to develop an analysis method for the automatic detection of intracoronary microemboli triggered high intensity signals (HITS) during percutaneous coronary interventions (PCI). The recorded ultrasonic Doppler velocity spectra from an intracoronary ultrasonic guide-wire were decomposed into 13 wavelet scales applying the continuous wavelet transform. From 7 wavelet scales which were most suitable for a differentiation between HITS and pulsatile flow, envelopes were calculated and combined to improve the HITS-to-background noise ratio. For different intensity thresholds the resulting number of HITS was automatically counted and compared with the number estimated by experienced observers. In a first validation trial HITS were detected within a simplified in vitro model with a sensitivity of 89.2% and a positive predictive value of 87.6%. In a following clinical study 211 HITS from 18 patients during PCI were counted manually by the observers. With the developed wavelet-based method 189 HITS were correctly detected (sensitivity of 89.6%, positive predictive value of 85.5%). The introduced new method automatically detects intracoronary HITS for the first time with a reliable accuracy. This may support further studies evaluating the incidence and consequences of coronary microembolization during coronary interventions.