Objectives: To evaluate the success rates and outcome of the hybrid algorithm for chronic total occlusion (CTO) percutaneous coronary intervention (PCI) by a single operator in two different clinical settings.
Methods: We compared 279 consecutive CTO PCIs performed by a single, high-volume operator using the hybrid algorithm in two different clinical settings. Data were collected through the PROGRESS CTO Registry. We compared 145 interventions performed in a community program (cohort A) with 134 interventions performed in a referral center (cohort B).
Results: Patient in cohort B had more complex lesions with higher J-CTO (3.0 vs. 3.41; p<0.001) and Progress CTO (1.5 vs.1.8, P=0.003) scores, more moderate to severe tortuosity (38% vs. 64%; p<0.001), longer total occlusion length (25 vs. 40mm; p<0.001) and higher prevalence of prior failed CTO PCI attempts (15% vs. 35%; p=0.001). Both technical (95% vs. 91%; p=0.266) and procedural (94% vs. 88%; p=0.088) success rates were similar between the two cohorts despite significantly different lesion complexity. Overall major adverse cardiovascular events were higher in cohort B (1.4% vs. 7.8%; p=0.012) without any significant difference in mortality (0.7% vs. 2.3%, p=0.351).
Conclusions: In spite of higher lesion complexity in the setting of a quaternary-care referral center, use of the hybrid algorithm for CTO PCI enabled similarly high technical and procedural success rates as compared with those previously achieved by the same operator in a community-based program at the expense of a higher rate of MACE.
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http://dx.doi.org/10.1016/j.carrev.2017.02.014 | DOI Listing |
Sci Rep
January 2025
Department of Oncology, The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China.
Exploring the potential of advanced artificial intelligence technology in predicting microsatellite instability (MSI) and Ki-67 expression of endometrial cancer (EC) is highly significant. This study aimed to develop a novel hybrid radiomics approach integrating multiparametric magnetic resonance imaging (MRI), deep learning, and multichannel image analysis for predicting MSI and Ki-67 status. A retrospective study included 156 EC patients who were subsequently categorized into MSI and Ki-67 groups.
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January 2025
College of Information Science and Technology, Hainan Normal University, Haikou, 571158, China.
Breast cancer is one of the most aggressive types of cancer, and its early diagnosis is crucial for reducing mortality rates and ensuring timely treatment. Computer-aided diagnosis systems provide automated mammography image processing, interpretation, and grading. However, since the currently existing methods suffer from such issues as overfitting, lack of adaptability, and dependence on massive annotated datasets, the present work introduces a hybrid approach to enhance breast cancer classification accuracy.
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January 2025
Ministry of Higher Education, Mataria Technical College, Cairo, 11718, Egypt.
The current work introduces the hybrid ensemble framework for the detection and segmentation of colorectal cancer. This framework will incorporate both supervised classification and unsupervised clustering methods to present more understandable and accurate diagnostic results. The method entails several steps with CNN models: ADa-22 and AD-22, transformer networks, and an SVM classifier, all inbuilt.
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January 2025
Faculty of Engineering, Multimedia University-MMU, 63100 Cyberjaya, Cyberjaya, Malaysia.
This study aims to establish a thyristor-controlled series compensator (TCSC) equipped with a proportional integral derivative with filter (PIDF) controller by using a futuristic optimisation technique called evolutionary programming sine cosine algorithm (EPSCA) with multiobjective function (MOF). EPSCA is developed by merging evolutionary programming and the sine cosine algorithm. Three stability indicators, i.
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January 2025
Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Depok 16424, Indonesia.
The Internet of Things (IoT) has emerged as a crucial element in everyday life. The IoT environment is currently facing significant security concerns due to the numerous problems related to its architecture and supporting technology. In order to guarantee the complete security of the IoT, it is important to deal with these challenges.
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