ABSTRACT
BACKGROUND: One million individuals in the USA die from acute myocardial infarction (MI), which currently affects 3 million people globally. The available data about the early and late outcomes of both biodegradable polymer drug-eluting stents (BP-DES) and durable polymer drug-eluting stents exhibit inconsistency. We performed a meta-analysis comparing the safety and efficacy of BP-DES with DP-DES. METHODS: PubMed, Google Scholar, EMBASE, Cochrane, Ovid Medline, and Clinical Trials.gov databases were used to find out studies comparing BP-DES to DP-DES. All the analyses used the random-effects model. RESULTS: A total of 18 studies were incorporated in this meta-analysis that involved 28,874 patients, out of which 11,997 received the BP Stent, and the rest of 16,578 received the DP stent. Thorough analyses revealed that the risk of all-cause death was significantly higher in the BP-DES group (5.4% vs 2.7%) (RR 1.22, p 0.02) for two years or less than two-year follow-up. For studies with more than two years of follow-up, all-cause death was 9.07% (599/6603) in BP-DES and 9.47% (531/5602) in the DP-DES group but failed to achieve statistically significant levels (RR 0.97, p 0.58). CONCLUSIONS: The study revealed no clinically significant (P value was > 0.05) differences in all-cause death, cardiac death, target lesion revascularization (TLR), late stent thrombosis, device-oriented composite endpoint/target lesion failure (DOCE/TLF), myocardial infarction (MI), target vessel MI, target vessel revascularization (TVR), target vessel infarction (TVI) between BP-DES and DP-DES for more than two years of follow-up. Additionally, all-cause death was only outcomes which found to have a statistically significant difference for less than two years of follow-up, while remaining were statistically non-significant.
ABSTRACT
BACKGROUND: Obstructive sleep apnea (OSA) is a chronic sleeping disorder. The analysis of the pharynx and its surrounding tissues can play a vital role in understanding the pathogenesis of OSA. Classification of the pharynx is a crucial step in the analysis of OSA. METHODS: A visual analysis-based classifier is developed to classify the pharynx from MRI datasets. The classification pipeline consists of different stages, including pre-processing to select the initial candidates, extraction of categorical and numerical features to form a multidimensional features space, and a supervised classifier trained by using visual analytics and silhouette coefficient to classify the pharynx. RESULTS: The pharynx is classified automatically and gives an approximately 86% Jaccard coefficient by evaluating the classifier on different MRI datasets. The expert's knowledge can be utilized to select the optimal features and their corresponding weights during the training phase of the classifier. CONCLUSION: The proposed classifier is accurate and more efficient in terms of computational cost. It provides additional insight to better understand the influence of different features individually and collectively. It finds its applications in epidemiological studies where large datasets need to be analyzed.
