Reduction in risk of death among patients admitted with COVID-19 between first and second epidemic waves in New York City
MD Anthony Bowen, MD Jason Zucker, Yanhan Shen, Simian Huang, Qiheng Yan, Medini K Annavajhala, Anne-Catrin Uhlemann, Louise Kuhn, Magdalena Sobieszczyk, Delivette Castor
doi:10.1093/ofid/ofac436/6675651
Background: Many regions have experienced successive epidemic waves of COVID-19 since the emergence of SARS-CoV-2 with heterogeneous differences in mortality. Elucidating factors differentially associated with mortality between epidemic waves may inform clinical and public health strategies. Methods: We examined clinical and demographic data among patients admitted with COVID-19 during the first (March-August 2020) and second (August 2020-March 2021) epidemic waves at an academic medical center in New York City. Results: Hospitalized patients (N=4631) had lower overall and 30-day in-hospital mortality, defined as death or discharge to hospice, during the second wave (14% and 11%) than the first (22% and 21%). The wave 2 in-hospital mortality decrease persisted after adjusting for several potential confounders. Adjusting for the volume of COVID-19 admissions, a measure of health system strain, accounted for the mortality difference between waves. Several demographic and clinical patient factors were associated with an increased risk of mortality independent of wave; SARS-CoV-2 cycle threshold, Do-Not-Intubate status, oxygen requirement, and intensive care unit admission.
Conclusions: This work suggests that increased in-hospital mortality rates observed during the first epidemic wave were partly due to strain on hospital resources. Preparations for future epidemics should prioritize evidence-based patient risks, treatment paradigms, and approaches to augment hospital capacity.
may help prepare for future epidemic waves by improving the accuracy of COVID-19 projections and informing public health policy decisions. Furthermore, plans to address future potential pandemics may benefit from prioritizing rapid, systematic methods of studying and developing treatment standards and plans to rapidly adjust hospital capacity and scale up necessary resources.
Potential conflicts of interest All authors declare no conflicts of interest potentially related to this work.
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