AIMC Topic: Percutaneous Coronary Intervention

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Choosing Clinical Variables for Risk Stratification Post-Acute Coronary Syndrome.

Scientific reports Oct 10, 2019
Most risk stratification methods use expert opinion to identify a fixed number of clinical variables that have prognostic significance. In this study our goal was to develop improved metrics that utilize a variable number of input parameters. We firs...
Female Risk Factors Aged Male Humans Machine Learning Prognosis Follow-Up Studies Registries Percutaneous Coronary Intervention Patient Selection Acute Coronary Syndrome Middle Aged Risk Assessment Cohort Studies Logistic Models
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Deep Learning in Personalization of Cardiovascular Stents.

Journal of cardiovascular pharmacology and therapeutics Sep 25, 2019
Deep learning (DL) application has demonstrated its enormous potential in accomplishing biomedical tasks, such as vessel segmentation, brain visualization, and speech recognition. This review article has mainly covered recent advances in the principl...
Stents Software Clinical Decision-Making Coronary Artery Disease Computer-Aided Design Humans Predictive Value of Tests Prosthesis Design Deep Learning Percutaneous Coronary Intervention Patient Selection
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Cath Lab Robotics: Paradigm Change in Interventional Cardiology?

Current cardiology reports Aug 31, 2019
PURPOSE OF REVIEW: To review the contemporary evidence for robotic-assisted percutaneous coronary and vascular interventions, discussing its current capabilities, limitations, and potential future applications.
Coronary Artery Disease Therapy, Computer-Assisted Radiation Injuries Radiation Exposure Treatment Outcome Robotics Coronary Angiography Percutaneous Coronary Intervention Cardiology Humans
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Network latency and long-distance robotic telestenting: Exploring the potential impact of network delays on telestenting performance.

Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions Aug 13, 2019
OBJECTIVE: This study evaluated the impact of network latency on telestenting performance.
Time Factors Robotics Percutaneous Coronary Intervention Coronary Artery Disease Feasibility Studies Humans Female Animals Sus scrofa Manikins Stents Computer Communication Networks Remote Consultation Models, Animal Therapy, Computer-Assisted
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Comparison of Machine Learning Methods With National Cardiovascular Data Registry Models for Prediction of Risk of Bleeding After Percutaneous Coronary Intervention.

JAMA network open Jul 3, 2019
IMPORTANCE: Better prediction of major bleeding after percutaneous coronary intervention (PCI) may improve clinical decisions aimed to reduce bleeding risk. Machine learning techniques, bolstered by better selection of variables, hold promise for enh...
Risk Adjustment Comparative Effectiveness Research Clinical Decision Rules Postoperative Hemorrhage Registries Percutaneous Coronary Intervention Coronary Artery Disease Male Risk Assessment United States Models, Statistical Machine Learning Female Aged Humans
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Enhancement of Risk Prediction With Machine Learning: Rise of the Machines.

JAMA network open Jul 3, 2019
Humans Registries Percutaneous Coronary Intervention Machine Learning Support Vector Machine
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Leveraging Machine Learning Techniques to Forecast Patient Prognosis After Percutaneous Coronary Intervention.

JACC. Cardiovascular interventions Jun 26, 2019
OBJECTIVES: This study sought to determine whether machine learning can be used to better identify patients at risk for death or congestive heart failure (CHF) rehospitalization after percutaneous coronary intervention (PCI).
Humans Machine Learning Decision Support Techniques Reproducibility of Results Risk Factors Aged Clinical Decision-Making Female Percutaneous Coronary Intervention Hospital Mortality Coronary Artery Disease Male Treatment Outcome Heart Failure Middle Aged Minnesota Predictive Value of Tests Patient Readmission Risk Assessment Registries Time Factors
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Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study.

PLoS medicine Nov 27, 2018
BACKGROUND: The current acute kidney injury (AKI) risk prediction model for patients undergoing percutaneous coronary intervention (PCI) from the American College of Cardiology (ACC) National Cardiovascular Data Registry (NCDR) employed regression te...
Risk Assessment Humans Risk Factors Percutaneous Coronary Intervention Time Factors Clinical Decision-Making Machine Learning Retrospective Studies Data Mining Aged Treatment Outcome Female Decision Support Techniques Acute Kidney Injury Protective Factors Male Registries Reproducibility of Results Middle Aged
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Complex robotic compared to manual coronary interventions: 6- and 12-month outcomes.

Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions Nov 19, 2018
OBJECTIVES: To assess the long-term safety and efficacy of robotic percutaneous coronary revascularization for use in complex coronary lesions.
Therapy, Computer-Assisted Percutaneous Coronary Intervention Coronary Artery Disease Stroke Female Myocardial Infarction Risk Factors Time Factors Aged Humans Male Treatment Outcome Middle Aged Robotics Registries
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Drug eluting stents are superior to bare metal stents to reduce clinical outcome and stent-related complications in CKD patients, a systematic review, meta-analysis and network meta-analysis.

Journal of interventional cardiology Dec 28, 2017
Aims To compare clinical outcome in Chronic kidney disease (CKD) patients receiving coronary stents according to stent type BMS versus DES and 1st generation versus 2nd generation DES. Methods and Results PubMed, Cinhal, Cochrane, Embase, and Web of ...
Self Expandable Metallic Stents Percutaneous Coronary Intervention Humans Risk Network Meta-Analysis Drug-Eluting Stents Renal Insufficiency, Chronic Coronary Occlusion Treatment Outcome
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