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Quantifying excess deaths among solid organ transplant recipients in the COVID-19 era.

Allan B MassieWilliam A WerbelRobin K AveryTeresa Po-Yu ChiangJon J SnyderDorry L Segev
Published in: American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons (2022)
Estimating the total coronavirus disease 2019 (COVID-19) mortality burden of solid organ transplant recipients (SOTRs), both directly through COVID-19 infection and indirectly through other impacts on the healthcare system and society, is critical for understanding the disease's impact on the SOTR population. Using SRTR data, we modeled expected mortality risk per month pre-COVID (January 2015-February 2020) for kidney/liver/heart/lung SOTRs, and compared monthly COVID-era deaths (March 2020-March 2021) to expected rates, overall and among subgroups. Deaths above expected rates were designated "excess deaths." Between March 2020 and March 2021, there were 3739/827/265/252 excess deaths among kidney/liver/heart/lung SOTRs, respectively, representing a 41.2%/27.4%/18.5%/15.0% increase above expected deaths. 93.0% of excess deaths occurred in patients age≥50. The observed:expected ratio was highest among Hispanic SOTRs (1.82) and lowest among White SOTRs (1.20); 56.0% of excess deaths occurred among Black or Hispanic SOTRs. 64.7% of excess deaths occurred among patients who had survived ≥5 years post-transplant. Excess deaths peaked in January 2021; geographic distribution of excess deaths broadly mirrored COVID-19 incidence. COVID-19 likely caused over 5000 excess deaths among SOTRs in the US in a 13-month period, representing 1 in 75 SOTRs and a substantial proportion of all deaths among SOTRs during this time. SOTRs will remain at elevated mortality risk until the COVID-19 pandemic can be controlled.
Keyphrases
  • coronavirus disease
  • sars cov
  • heart failure
  • type diabetes
  • respiratory syndrome coronavirus
  • chronic kidney disease
  • african american
  • prognostic factors
  • big data
  • electronic health record