Early trends in ECMO mortality during the first quarters of 2019 and 2020: Could we have predicted the onset of the pandemic?

Author:

Awori Hayanga J.W.1ORCID,Kakuturu Jahnavi1,Toker Alper1,Asad Fatima1,Siler Anthony1ORCID,Hayanga Heather1,Badhwar Vinay1

Affiliation:

1. Department of Cardiovascular and Thoracic Surgery, WVU Heart and Vascular Institute, West Virginia University, Morgantown, WV, USA

Abstract

Objective To compare mortality trends in patients requiring Extracorporeal Membrane Oxygenation (ECMO) support between the first quarters of 2019 and 2020 and determine whether these trends might have predicted the severe acute respiratory syndrome coronavirus-2 (SARS)-Cov-2 pandemic in the United States. Methods We analyzed 5% Medicare claims data at aggregate, state, hospital, and encounter levels using MS-DRG (Medicare Severity-Diagnosis Related Group) codes for ECMO, combining state-level data with national census data. Necessity and sufficiency relations associated with change in mortality between the 2 years were modeled using qualitative comparative analysis (QCA). Multilevel, generalized linear modeling was used to evaluate mortality trends. Results Based on state-level data, there was a 3.36% increase in mortality between 2019 and 2020. Necessity and sufficiency evaluation of aggregate data at state and institutional levels did not identify any association or combinations of risk factors associated with this increase in mortality. However, multilevel and generalized linear models using disaggregated patient-level data to evaluate institution mortality and patient death, identified statistically significant differences between the first ( p = .019) and second ( p = .02) months of the 2 years, the first and second quarters ( p < .001 and p = .042, respectively), and the first 6 months ( p < .001) of 2019 and 2020. Conclusion Mortality in ECMO patients increased significantly during the first quarter of 2020 and may have served as an early warning of the SARS-Cov-2 pandemic. Granular data shared in real-time may be used to better predict public health threats.

Publisher

SAGE Publications

Subject

Advanced and Specialized Nursing,Cardiology and Cardiovascular Medicine,Safety Research,Radiology, Nuclear Medicine and imaging,General Medicine

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