3 research outputs found
Detection of myocardial injury during transvenous implantation of automatic cardioverter-defibrillators
AbstractOBJECTIVESThe present study was designed to assess the extent of myocardial injury in patients undergoing transvenous implantation of an automatic implantable cardioverter-defibrillator (ICD) using cardiac troponin I (cTNI), which is a highly specific marker of structural cardiac injury.BACKGROUNDDuring ICD implantation, repetitive induction and termination of ventricular fibrillation (VF) via endocardial direct current shocks is required to demonstrate the correct function of the device. Transthoracic electrical shocks can cause myocardial cell injury.METHODSMeasurements of total creatine kinase (CK), CK-MB, myoglobin, cardiac troponin T (cTNT) and cTNI were obtained before and after ICD implantation in 49 consecutive patients. Blood samples were drawn before and 2, 4, 8, and 24 h after implantation.RESULTSElevations of CK, CK-MB, myoglobin, cTNT and cTNI above cut-off level were found in 25%, 6%, 76%, 37% and 14% of patients, respectively, with peak cTNI concentrations ranging from 1.7 to 5.5 ng/ml. Cumulative defibrillation energy (DFE), mean DFE, cumulative VF time, number of shocks as well as prior myocardial infarction (MI) were found to be significantly related to a rise of cTNI. Mean DFE ≥ 18 J and a recent MI were identified as strong risk factors for cTNI rise.CONCLUSIONSDuring transvenous ICD implantation myocardial injury as assessed by cTNI rise occurs in about 14% of the patients. Peak cTNI concentrations are only minimally elevated reflecting subtle myocardial cell damage. Patients with a recent MI and a mean DFE ≥ 18 J seem to be prone to cTNI rise
Influence of Surface Topography on ICESat/GLAS Forest Height Estimation and Waveform Shape
This study explores ICESat/GLAS waveform data in Thuringian Forest, a low mountain range located in central Germany. Lidar remote sensing has been proven to directly derive tree height as a key variable of forest structure. The GLAS signal is, however, very sensitive to surface topography because of the large footprint size. This study therefore focuses on forests in a mountainous area to assess the potential of GLAS data to derive terrain elevation and tree height. The work enhances the empirical knowledge about the interaction between GLAS waveform and landscape structure regarding a special temperate forest site with a complex terrain. An algorithm to retrieve tree height directly from GLA01 waveform data is proposed and compared to an approach using GLA14 Gaussian parameters. The results revealed that GLAS height estimates were accurate for areas with a slope up to 10° whereas waveforms of areas above 15° were problematic. Slopes between 10–15° have been found to be a critical crossover. Further, different waveform shape types and landscape structure classes were developed as a new possibility to explore the waveform in its whole structure. Based on the detailed analysis of some waveform examples, it could be demonstrated that the waveform shape can be regarded as a product of the complex interaction between surface and canopy structure. Consequently, there is a great variety of waveform shapes which in turn considerably hampers GLAS tree height extraction in areas with steep slopes and complex forest conditions