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Impella versus Non-Impella for Non-emergent High-Risk Percutaneous Coronary Intervention: Impella vs. Non-Impella for HR-PCI.
Am J Cardiol
January 2025
Section of Interventional Cardiology, MedStar Washington Hospital Center, Washington, DC, USA. Electronic address:
Background: The benefit of mechanical circulatory support (MCS) with Impella (Abiomed, Inc, Danvers, MA) for patients undergoing non-emergent, high-risk percutaneous coronary intervention (HR-PCI) is unclear and currently the subject of a large randomized clinical trial (RCT), PROTECT IV. While contemporary registry data from PROTECT III demonstrated improvement of outcomes with Impella when compared with historical data (PROTECT II), there is lack of direct comparison to the HR-PCI cohort that did not receive Impella support.
Methods: We retrospectively identified patients from our institution meeting PROTECT III inclusion criteria (left ventricular ejection fraction [LVEF] <35% with unprotected left main or last remaining vessel or LVEF <30% undergoing multivessel PCI), and compared this group (NonIMP) to the published outcomes data from the PROTECT III registry (IMP).
Differential expression of vascular endothelial growth factor A (VEGFA) and M1 macrophage marker nitric oxide synthase 2 (NOS2) in lymph node granulomas of BCG-vaccinated and non-vaccinated cattle infected with Mycobacterium bovis.
Tuberculosis (Edinb)
January 2025
Infectious Bacterial Diseases Research Unit, National Animal Disease Center, Agricultural Research Service, United States Department of Agriculture, Ames, Iowa, USA.
Bovine tuberculosis is mainly caused by Mycobacterium bovis. Bacillus Calmette-Guérin (BCG) is an attenuated strain of M. bovis which provides variable disease protection.
View Article and Find Full Text PDFSUMO-Specific Peptidase 5 Promotes Oesophageal Squamous Cell Carcinoma Growth through the NF-κB- Axis.
Front Biosci (Landmark Ed)
January 2025
Department of Cardiothoracic Surgery, The Affiliated Jiangyin Hospital of Nantong University, 214400 Jiangyin, Jiangsu, China.
Background: This study investigates the role of small ubiquitin-like modifier (SUMO)-specific peptidase 5 (SENP5), a key regulator of SUMOylation, in esophageal squamous cell carcinoma (ESCC), a lethal disease, and its underlying molecular mechanisms.
Methods: Differentially expressed genes between ESCC mouse oesophageal cancer tissues and normal tissues were analysed via RNA-seq; among them, SENP5 expression was upregulated, and this gene was selected for further analysis. Immunohistochemistry and western blotting were then used to validate the increased protein level of SENP5 in both mouse and human ESCC samples.
Design and early progress of the Comparison of Anticoagulation and anti-Platelet Therapies for Intracranial Vascular Atherostenosis (CAPTIVA) trial.
Int J Stroke
January 2025
Medical University of South Carolina, Charleston, SC, USA.
Background: The usual antithrombotic treatment for symptomatic intracranial atherosclerotic stenosis (ICAS) consists of dual treatment with clopidogrel and aspirin for 90 days followed by aspirin alone but the risk of recurrent stroke remains high up to 12 months. The Comparison of Anticoagulation and anti-Platelet Therapies for Intracranial Vascular Atherostenosis (CAPTIVA) trial was designed to determine whether other combinations of dual antithrombotic therapy are superior to clopidogrel and aspirin.
Methods: CAPTIVA is an ongoing, prospective, double-blinded, three-arm clinical trial at over 100 sites in the United States and Canada that will randomize 1683 high-risk subjects with a symptomatic infarct attributed to 70-99% stenosis of a major intracranial artery to 12 months of treatment with (1) ticagrelor (180 mg loading dose, then 90 mg twice daily), (2) low-dose rivaroxaban (2.
Prioritizing Patient Selection in Clinical Trials: A Machine Learning Algorithm for Dynamic Prediction of In-Hospital Mortality for ICU Admitted Patients Using Repeated Measurement Data.
J Clin Med
January 2025
Clinical Trial and Biostatistics, Research and Innovation Unit, University Hospital of Ferrara, 44124 Ferrara, Italy.
A machine learning prognostic mortality scoring system was developed to address challenges in patient selection for clinical trials within the Intensive Care Unit (ICU) environment. The algorithm incorporates Red blood cell Distribution Width (RDW) data and other demographic characteristics to predict ICU mortality alongside existing ICU mortality scoring systems like Simplified Acute Physiology Score (SAPS). The developed algorithm, defined as a Mixed-effects logistic Random Forest for binary data (MixRFb), integrates a Random Forest (RF) classification with a mixed-effects model for binary outcomes, accounting for repeated measurement data.
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