Three-Year Outcomes of Biodegradable Polymer-Coated Ultra-Thin (60 µm) Sirolimus-Eluting Stents in Real-World Clinical Practice

INTRODUCTION@#Although drug-eluting stents (DES) have outclassed the use of bare metal stents, the safety and efficacy of DES at long-term follow-up has still been conflicting because of increased occurrence of late or very late restenosis and stent thrombosis after DES implantation. Hence, the present study was aimed to evaluate the 3-year safety and clinical performance of biodegradable polymer-coated ultra-thin (60 µm) sirolimus-eluting stent (SES) in real-world patients with coronary artery disease (CAD).@*MATERIALS AND METHODS@#This was a physician-initiated, retrospective, single-centre, observational study that included 237 consecutive patients who had previously undergone implantation of only Supraflex SES (Sahajanand Medical Technologies Pvt Ltd, Surat, India) for the treatment of CAD. Follow-up was received after 1 year and 3 years of stent implantation. The primary endpoint was major adverse cardiac events (MACE), a composite of cardiac death, myocardial infarction (MI) and target lesion revascularisation (TLR). Stent thrombosis was considered as a safety endpoint.@*RESULTS@#The mean age of patients was 64.1 ± 10.2 years, and 192 (81.0%) patients were male. The average stent length and diameter were 24.4 ± 9.0 mm and 3.1 ± 0.4 mm, respectively. The cumulative MACE rate at 3 years follow-up was 6.5% which included 4 (1.8%) cardiac deaths, 6 (2.8%) MI, and 4 (1.8%) TLR. There were 2 (0.9%) cases of stent thrombosis.@*CONCLUSION@#Treatment of patients with CAD in real-world clinical practice was associated with sustained clinical safety and low rates of restenosis, stent thrombosis and MACE up to 3 years after Supraflex SES implantation.

Optimization of Gaussian Kernel Function in Support Vector Machine aided QSAR studies of C-aryl glucoside SGLT2 inhibitors.

The present investigations include utility of latest statistical algorithm Support Vector Machine (SVM) to identify non-linear structure activity relationship between IC50 values and structures of C-aryl glucoside SGLT2 inhibitors. Training dataset consisted of forty molecules and the remaining six molecules were chosen for test set validation. SVM under Gaussian Kernel Function yielded non-linear QSAR models. Forward selection algorithm was applied after pruning and redundancy check on molecular descriptors. Internal validations of QSAR models have been achieved using R CV (2) (LOO), PRESS, SDEP and Y-Scrambling. SVM aided non-linear models are more efficient when optimization of Gaussian Kernel Function was introduced. Non-linear QSAR studies further identified atomic van der Waals volumes, atomic masses, sum of geometrical distances between O..S and degree of unsaturation as molecular descriptors and crucial structural requirements to model IC50 of C-aryl glucoside derivatives.