Publications by authors named "Tatiana Hamakarim"
Background: Machine learning (ML) models have been proposed to predict risk related to transvenous lead extraction (TLE).
Objective: The purpose of this study was to test whether integrating imaging data into an existing ML model increases its ability to predict major adverse events (MAEs; procedure-related major complications and procedure-related deaths) and lengthy procedures (≥100 minutes).
Methods: We hypothesized certain features-(1) lead angulation, (2) coil percentage inside the superior vena cava (SVC), and (3) number of overlapping leads in the SVC-detected from a pre-TLE plain anteroposterior chest radiograph (CXR) would improve prediction of MAE and long procedural times.
Aims: Female sex is a recognized risk factor for procedure-related major complications including in-hospital mortality following transvenous lead extraction (TLE). Long-term outcomes following TLE stratified by sex are unclear. The purpose of this study was to evaluate factors influencing long-term survival in patients undergoing TLE according to sex.
View Article and Find Full Text PDFObjective: Advances in endovascular technologies have allowed the treatment of common femoral artery (CFA) steno-occlusive disease by minimally invasive means; however, the proportion of lesions treated with common femoral artery endarterectomy (CFAE) which would be amenable to endovascular treatment is unknown. This observational study aimed to describe the morphology and composition of CFA lesions treated with CFAE and report the proportion that would be amenable to endovascular treatment with modern technologies.
Methods: Patients presenting with symptomatic peripheral artery disease who underwent CFAE from January 2014 to December 2018 in two tertiary NHS hospitals were included.