Parameters of the complete blood count predict in hospital mortality

Zvi Shimoni, Paul Froom, Jochanan Benbassat

Research output: Contribution to journalArticlepeer-review

Abstract

Introduction: Mortality rates are used to evaluate the quality of hospital care after adjusting for disease severity and, commonly also, for age, comorbidity, and laboratory data with only few parameters of the complete blood count (CBC). Objective: To identify the parameters of the CBC that predict independently in-hospital mortality of acutely admitted patients. Population: All patients were admitted to internal medicine, cardiology, and intensive care departments at the Laniado Hospital in Israel in 2018 and 2019. VARIABLES: Independent variables were patients' age, sex, and parameters of the CBC. The outcome variable was in-hospital mortality. Analysis: Logistic regression. In 2018, we identified the variables that were associated with in-hospital mortality and validated this association in the 2019 cohort. Results: In the validation cohort, a model consisting of nine parameters that are commonly available in modern analyzers had a c-statistics (area under the receiver operator curve) of 0.86 and a 10%-90% risk gradient of 0%-21.4%. After including the proportions of large unstained cells, hypochromic, and macrocytic red cells, the c-statistic increased to 0.89, and the risk gradient to 0.1%-29.5%. Conclusion: The commonly available parameters of the CBC predict in-hospital mortality. Addition of the proportions of hypochromic red cells, macrocytic red cells, and large unstained cells may improve the predictive value of the CBC.

Original languageEnglish
Pages (from-to)88-95
Number of pages8
JournalInternational Journal of Laboratory Hematology
Volume44
Issue number1
DOIs
StatePublished - Feb 2022

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