ABSTRACT
BACKGROUND: Venous stenosis is a common complication of transvenous lead implantation, but the risk factors for venous stenosis have not been well defined to date. This study was designed to evaluate the incidence of and risk factors for venous stenosis in a large consecutive cohort. METHODS AND RESULTS: A total of 212 consecutive patients (136 male, 76 female; mean age 69 years) with existing pacing or implantable cardioverter-defibrillator systems presented for generator replacement, lead revision, or device upgrade with a mean time since implantation of 6.2 years. Venograms were performed and percentage of stenosis was determined. Variables studied included age, sex, number of leads, lead diameter, implant duration, insulation material, side of implant, and anticoagulant use. Overall, 56 of 212 patients had total occlusion of the subclavian or innominate vein (26%). There was a significant association between the number of leads implanted and percentage of venous stenosis (P=0.012). Lead diameter, as an independent variable, was not a risk factor; however, greater sum of the lead diameters implanted was a predictor of subsequent venous stenosis (P=0.009). Multiple lead implant procedures may be associated with venous stenosis (P=0.057). No other variables approached statistical significance. CONCLUSIONS: A significant association exists between venous stenosis and the number of implanted leads and also the sum of the lead diameters. When combined with multiple implant procedures, the incidence of venous stenosis is increased.
Subject(s)
Brachiocephalic Veins , Defibrillators, Implantable/adverse effects , Pacemaker, Artificial/adverse effects , Prosthesis Implantation/adverse effects , Subclavian Vein , Vascular Diseases/epidemiology , Adult , Aged , Aged, 80 and over , Brachiocephalic Veins/diagnostic imaging , Constriction, Pathologic , Female , Humans , Incidence , Iowa/epidemiology , Male , Middle Aged , Phlebography , Prosthesis Design , Prosthesis Implantation/instrumentation , Risk Assessment , Risk Factors , Severity of Illness Index , Subclavian Vein/diagnostic imaging , Time Factors , Treatment Outcome , Vascular Diseases/diagnosisABSTRACT
A 24-year-old male with Wolff-Parkinson-White syndrome developed systolic cardiomyopathy and severe heart failure following membranous ventricular septal defect repair and tricuspid valve replacement. Following successful catheter ablation of a right anterolateral accessory pathway (AP), complete AV block with junctional escape rhythm was noted. Patient subsequently underwent implantation of a biventricular ICD. Heart failure symptoms significantly improved soon after and left ventricular systolic function normalized 3 months post-procedure. In this case, surgically acquired AV block likely explains development of postoperative cardiomyopathy by facilitating ventricular activation solely via the AP and thereby increasing the degree of ventricular dyssynchrony.
ABSTRACT
Cardiac resynchronization therapy (CRT) using a biventricular pacemaker is an invasive and expensive treatment option for left ventricular mechanical dyssynchrony (LVMD). The CRT candidate selection is a crucial issue due to the unreliability of the current standard CRT indicators. Real-time three-dimensional (3-D) echocardiography (RT3DE) provides four-dimensional (4-D) (3-D+time) information about the LV and is suitable for LVMD assessment. In this article, the complex left ventricle (LV) shape and motion of 50 RT3DE datasets are represented by novel 4-D descriptors - 4-D sphericity, volume and shape, from which novel indices were derived by principal component analysis (PCA) and subsequently analyzed by a support vector machine (SVM) classifier to assess their capability of LVMD characterization and CRT outcome prediction. These novel indices outperformed clinical indices and have promising capabilities in disease characterization and great potential in CRT outcome prediction. To enable efficient quantitative RT3DE analysis, a segmentation method was developed to combine the powers of active shape models and optimal graph search. Various aspects of the method were designed to handle varying RT3DE image quality among datasets and LV segments. An application with graphical user interface was developed to provide the user with simple and intuitive control. The developed method was robust to inter-observer variability and produced very good accuracy - 3.2±1.1 mm absolute surface positioning error, <1 mm mean signed error and <5% mean volume difference. The computer method's classification performance was compared with the independent standard, showing that the 4-D shape modal indices were not only the most capable of all tested options when employed for disease characterization but also the least sensitive to segmentation imperfections.
