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http://dx.doi.org/10.1016/j.jacc.2020.03.021 | DOI Listing |
JTCVS Open
December 2024
Division of Cardiothoracic Surgery, Department of Surgery, Medical University of South Carolina, Charleston, SC.
Objective: Machine learning (ML) may allow for improved discernment of hemodynamics and oxygen delivery compared to standard invasive monitoring. We hypothesized that an ML algorithm could predict impaired delivery of oxygen (IDO) with comparable discrimination to invasive mixed venous oxygen saturation (SvO) measurement.
Methods: A total of 230 patients not on mechanical circulatory support (MCS) managed with a pulmonary artery catheter (PAC) were identified from 1012 patients admitted to a single cardiovascular intensive care unit (CVICU) between April 2021 and January 2022.
Acta Cardiol Sin
January 2025
Department of Biomedical Engineering, National Taiwan University, Taipei.
Background: Prompt primary percutaneous coronary intervention (pPCI) is crucial for the prognosis and reduction of myocardial damage in ST-segment elevation myocardial infarction (STEMI) patients. The Coronavirus Disease 2019 (COVID-19) pandemic had multifaceted impacts on healthcare. This study assessed the effects of the pandemic on pPCI procedures and clinical outcomes in emergency STEMI patients.
View Article and Find Full Text PDFActa Cardiol Sin
January 2025
Department of Cardiology, Gebze State Hospital, Gebze.
Commun Med (Lond)
January 2025
Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA.
Background: The ability to non-invasively measure left atrial pressure would facilitate the identification of patients at risk of pulmonary congestion and guide proactive heart failure care. Wearable cardiac monitors, which record single-lead electrocardiogram data, provide information that can be leveraged to infer left atrial pressures.
Methods: We developed a deep neural network using single-lead electrocardiogram data to determine when the left atrial pressure is elevated.
Am J Vet Res
January 2025
Department of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, MO.
Objective: To document differences in the microbiota of healthy cats versus cats with urethral obstruction (UO); compare the urinary microbiota with the oral, preputial, and rectal microbiota; and demonstrate that 16S rRNA gene sequencing will reveal rich and diverse urinary microbiota.
Methods: 15 client-owned cats with UO and 15 age-matched healthy cats were included from July 2020 through April 2021. Exclusion criteria were evidence of urinary tract infection, urolithiasis, antimicrobial administration, urinary catheterization in the past 30 days, or a comorbidity.
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