Cardiology Commons^™

Prediction Of Major Adverse Cardiac Events In The Emergency Department Using An Artificial Neural Network With A Systematic Grid Search, Ahmed Raheem Buksh, Nadeem Ullah Khan, Rida Jawed, Shahan Waheed, Musa Karim

Department of Emergency Medicine

Background: The aim of our research was to design and evaluate an Artificial Neural Network (ANN) model using a systemic grid search for the early prediction of major adverse cardiac events (MACE) among patients presenting to the triage of an emergency department.
Methods: This is a single-center, cross-sectional study using electronic health records from January 2017 to December 2020. The research population consists of adults coming to our emergency department triage at Aga Khan University Hospital. The MACE during hospitalization was the main outcome. To enhance the architecture of an ANN using triage data, we used a systematic grid search …

Impact Of Post-Arrest Care Variation On Hospital Performance After Out-Of-Hospital Cardiac Arrest, Ryan Huebinger, Jordan Thomas, Benjamin S Abella, John Waller-Delarosa, Rabab Al-Araji, Richard Witkov, Normandy Villa, Peter Nikonowicz, Taylor Renbarger, Micah Panczyk, Bentley Bobrow

Journal Articles

BACKGROUND: Large variation exists for out-of-hospital-cardiac-arrest (OHCA) prehospital care, but less is known about variations in post-arrest care. We sought to evaluate variation in post-arrest care in Texas as well as factors associated with higher performing hospitals.

METHODS: We analyzed data in Texas Cardiac Arrest Registry to Enhance Survival (TX-CARES), including all adult, non-traumatic OHCAs from 1/1/2014 through 12/31/ 2020 that survived to hospital admission. We first evaluated variability in provisions of post-arrest care and outcomes. We then stratified hospitals into quartiles based on their rate of survival and evaluated the association between improving quartiles and care. Lastly, we evaluated …