Simple Parameters from Complete Blood Count Predict In-Hospital Mortality in COVID-19

Dis Markers. 2021 May 13:2021:8863053. doi: 10.1155/2021/8863053. eCollection 2021.

Abstract

Introduction: The clinical course of Coronavirus Disease 2019 (COVID-19) is highly heterogenous, ranging from asymptomatic to fatal forms. The identification of clinical and laboratory predictors of poor prognosis may assist clinicians in monitoring strategies and therapeutic decisions.

Materials and methods: In this study, we retrospectively assessed the prognostic value of a simple tool, the complete blood count, on a cohort of 664 patients (F 260; 39%, median age 70 (56-81) years) hospitalized for COVID-19 in Northern Italy. We collected demographic data along with complete blood cell count; moreover, the outcome of the hospital in-stay was recorded.

Results: At data cut-off, 221/664 patients (33.3%) had died and 453/664 (66.7%) had been discharged. Red cell distribution width (RDW) (χ 2 10.4; p < 0.001), neutrophil-to-lymphocyte (NL) ratio (χ 2 7.6; p = 0.006), and platelet count (χ 2 5.39; p = 0.02), along with age (χ 2 87.6; p < 0.001) and gender (χ 2 17.3; p < 0.001), accurately predicted in-hospital mortality. Hemoglobin levels were not associated with mortality. We also identified the best cut-off for mortality prediction: a NL ratio > 4.68 was characterized by an odds ratio for in-hospital mortality (OR) = 3.40 (2.40-4.82), while the OR for a RDW > 13.7% was 4.09 (2.87-5.83); a platelet count > 166,000/μL was, conversely, protective (OR: 0.45 (0.32-0.63)).

Conclusion: Our findings arise the opportunity of stratifying COVID-19 severity according to simple lab parameters, which may drive clinical decisions about monitoring and treatment.

Publication types

  • Observational Study

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Blood Cell Count*
  • COVID-19 / blood*
  • COVID-19 / diagnosis
  • COVID-19 / mortality*
  • Clinical Decision Rules*
  • Female
  • Hospital Mortality*
  • Humans
  • Italy / epidemiology
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Prognosis
  • Retrospective Studies
  • Severity of Illness Index*