Frontiers in Medicine (Jul 2021)

Routine Hematological Parameters May Be Predictors of COVID-19 Severity

  • Paulina B. Szklanna,
  • Paulina B. Szklanna,
  • Haidar Altaie,
  • Shane P. Comer,
  • Shane P. Comer,
  • Sarah Cullivan,
  • Sarah Kelliher,
  • Luisa Weiss,
  • Luisa Weiss,
  • John Curran,
  • Emmet Dowling,
  • Katherine M. A. O'Reilly,
  • Katherine M. A. O'Reilly,
  • Aoife G. Cotter,
  • Aoife G. Cotter,
  • Aoife G. Cotter,
  • Brian Marsh,
  • Brian Marsh,
  • Sean Gaine,
  • Sean Gaine,
  • Nick Power,
  • Nick Power,
  • Áine Lennon,
  • Brian McCullagh,
  • Brian McCullagh,
  • Fionnuala Ní Áinle,
  • Fionnuala Ní Áinle,
  • Fionnuala Ní Áinle,
  • Fionnuala Ní Áinle,
  • Barry Kevane,
  • Barry Kevane,
  • Barry Kevane,
  • Patricia B. Maguire,
  • Patricia B. Maguire,
  • Patricia B. Maguire

DOI
https://doi.org/10.3389/fmed.2021.682843
Journal volume & issue
Vol. 8

Abstract

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To date, coronavirus disease 2019 (COVID-19) has affected over 100 million people globally. COVID-19 can present with a variety of different symptoms leading to manifestation of disease ranging from mild cases to a life-threatening condition requiring critical care-level support. At present, a rapid prediction of disease severity and critical care requirement in COVID-19 patients, in early stages of disease, remains an unmet challenge. Therefore, we assessed whether parameters from a routine clinical hematology workup, at the time of hospital admission, can be valuable predictors of COVID-19 severity and the requirement for critical care. Hematological data from the day of hospital admission (day of positive COVID-19 test) for patients with severe COVID-19 disease (requiring critical care during illness) and patients with non-severe disease (not requiring critical care) were acquired. The data were amalgamated and cleaned and modeling was performed. Using a decision tree model, we demonstrated that routine clinical hematology parameters are important predictors of COVID-19 severity. This proof-of-concept study shows that a combination of activated partial thromboplastin time, white cell count-to-neutrophil ratio, and platelet count can predict subsequent severity of COVID-19 with high sensitivity and specificity (area under ROC 0.9956) at the time of the patient's hospital admission. These data, pending further validation, indicate that a decision tree model with hematological parameters could potentially form the basis for a rapid risk stratification tool that predicts COVID-19 severity in hospitalized patients.

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