Development and validation of a sepsis risk index supporting early identification of ICU-acquired sepsis: an observational study.

Autor: Pappada SM; Department of Anesthesiology, The University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA; Department of Bioengineering, The University of Toledo, Toledo, OH 43606, USA; Department of Electrical Engineering and Computer Science, The University of Toledo, Toledo, OH 43606, USA., Owais MH; Department of Electrical Engineering and Computer Science, The University of Toledo, Toledo, OH 43606, USA., Feeney JJ; Aptima, Inc., Fairborn, OH, 45324, USA., Salinas J; United States Army Institute of Surgical Research, Fort Sam Houston, San Antonio, TX 78234, USA., Chaney B; Department of Anesthesiology, The University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA., Duggan J; Department of Medicine, University of Toledo College of Medicine and Life Science, Toledo, OH 43614, USA., Sparkle T; Department of Anesthesiology, The University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA., Aouthmany S; Department of Emergency Medicine, University of Toledo College of Medicine and Life Science, Toledo, OH 43614, USA., Hinch B; Department of Medicine, University of Toledo College of Medicine and Life Science, Toledo, OH 43614, USA., Papadimos TJ; Department of Anesthesiology, The University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA; Department of Surgery, University of Toledo College of Medicine and Life Science, Toledo, OH 43614, USA. Electronic address: Thomas.Papadimos@utoledo.edu.

Publikováno v: Anaesthesia, critical care & pain medicine [Anaesth Crit Care Pain Med] 2024 Dec; Vol. 43 (6), pp. 101430. Date of Electronic Publication: 2024 Oct 02.

Increasing patient safety with neonates via handoff communication during delivery: a call for interprofessional health care team training across GME and CME

Autor: Vanderbilt AA, Pappada SM, Stein H, Harper D, Papadimos TJ

Publikováno v: Advances in Medical Education and Practice, Vol Volume 8, Pp 365-367 (2017)

Allison A Vanderbilt,1 Scott M Pappada,2 Howard Stein,3 David Harper,4 Thomas J Papadimos5 1Department of Family Medicine, 2Department of Anesthesiology, College of Medicine and Life Sciences, University of Toledo, 3Department of Pediatrics, ProMedic

Externí odkaz: https://doaj.org/article/30b78eb046734ad1bad3b21eaa359232

Contributing Factors to Operating Room Delays Identified from an Electronic Health Record: A Retrospective Study.

Autor: Pappada SM; University of Toledo College of Medicine and Life Sciences, Department of Anesthesiology, Toledo, OH, USA.; University of Toledo College of Medicine and Life Sciences, Toledo, OH, USA.; University of Toledo College of Engineering, Department of Bioengineering, Toledo, OH, USA., Papadimos TJ; University of Toledo College of Medicine and Life Sciences, Department of Anesthesiology, Toledo, OH, USA., Khuder S; University of Toledo College of Medicine and Life Sciences, Department of Medicine, Toledo, OH, USA., Mack ST; University of Toledo College of Medicine and Life Sciences, Toledo, OH, USA., Beachy PZ; University of Toledo College of Medicine and Life Sciences, Toledo, OH, USA., Casabianca AB; University of Toledo College of Medicine and Life Sciences, Department of Anesthesiology, Toledo, OH, USA.

Publikováno v: Anesthesiology research and practice [Anesthesiol Res Pract] 2022 Sep 13; Vol. 2022, pp. 8635454. Date of Electronic Publication: 2022 Sep 13 (Print Publication: 2022).

NASA Task Load Index Scale to Evaluate the Cognitive Workload during Cardiac Anesthesia Based Simulation Scenarios

Autor: Bhandary SP, Lipps J, Winfield SR, Abdel-Rasoul M, Stoicea N, Pappada SM, Papadimos TJ

Simulation-based education is an important tool for anesthesiology educators given the work hour restrictions and limited exposure of anesthesiology residents to high acuity cardiac cases. Cognitive load is key to learning, performance, and resilienc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______2659::230e65221caee9ac92851aad500decec
https://zenodo.org/record/580438

An Artificial Neural Network-based Predictive Model to Support Optimization of Inpatient Glycemic Control.

Autor: Pappada SM; Department of Anesthesiology, University of Toledo, College of Medicine and Life Sciences, Toledo, Ohio.; Department of Bioengineering, University of Toledo, College of Engineering, Toledo, Ohio.; Department of Anesthesiology, The Ohio State University, College of Medicine, Columbus, Ohio., Owais MH; Department of Electrical Engineering and Computer Science, University of Toledo, College of Engineering, Toledo, Ohio., Cameron BD; Department of Bioengineering, University of Toledo, College of Engineering, Toledo, Ohio., Jaume JC; Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, University of Toledo, College of Medicine and Life Sciences, Toledo, Ohio., Mavarez-Martinez A; Department of Anesthesiology, The Ohio State University, College of Medicine, Columbus, Ohio., Tripathi RS; Department of Anesthesiology, The Ohio State University, College of Medicine, Columbus, Ohio., Papadimos TJ; Department of Anesthesiology, University of Toledo, College of Medicine and Life Sciences, Toledo, Ohio.; Department of Anesthesiology, The Ohio State University, College of Medicine, Columbus, Ohio.

Publikováno v: Diabetes technology & therapeutics [Diabetes Technol Ther] 2020 May; Vol. 22 (5), pp. 383-394. Date of Electronic Publication: 2020 Feb 06.