Hematological parameters and their predictive value for assessing disease severity in laboratory-confirmed COVID-19 patients: a retrospective study

Mezgebu Alemayehu Awoke; Ayinshet Adane; Belete Assefa; Solomon Getawa; Gebrehiwot Lema Legese; Mekonen Yimer

Hematological parameters and their predictive value for assessing disease severity in laboratory-confirmed COVID-19 patients: a retrospective study

Am J Blood Res. 2023 Aug 15;13(4):117-129. eCollection 2023.

Authors

Mezgebu Alemayehu Awoke¹, Ayinshet Adane¹, Belete Assefa¹, Solomon Getawa², Gebrehiwot Lema Legese¹, Mekonen Yimer¹

Affiliations

¹ Department of Internal Medicine, School of Medicine, College of Medicine and Health Sciences, University of Gondar Gondar, Ethiopia.
² Department of Hematology and Immunohematology, School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences, University of Gondar Gondar, Ethiopia.

PMID: 37736538
PMCID: PMC10509465

Abstract

Background: The coronavirus disease 19 (COVID-19) infection has spread globally and caused a substantial amount of mortality and morbidity. Early detection of severe infections will improve care and reduce deaths. The use of hematological parameters in predicting COVID-19 disease severity, patient outcomes, and early risk stratification is limited. Therefore, the study was aimed at determining hematological parameters and their predictive value for assessing disease severity in laboratory-confirmed COVID-19 patients in Northwest Ethiopia.

Methods: A retrospective cross-sectional study was conducted at the University of Gondar comprehensive specialized hospital and Tibebe Ghion comprehensive specialized referral hospital on 253 patients diagnosed with COVID-19 and admitted between March 2021 and February 2022. Data were extracted, and entered into Epi-data 4.2.0.0, and analyzed using SPSS version 25 software. Hematological parameters were provided as the median and interquartile range (IQR). Categorical variables were represented by their frequency, and the χ² test was applied to compare observed results with expected results. The receiver-operating curve (ROC) was used to establish the predictive value of hematological parameters for COVID-19 severity. A p-value < 0.05 was considered statistically significant.

Results: On a total of 253 patients, there were 43.87% severe cases, with a mortality rate of 26.9%. The ROC analysis showed the optimal cutoff values for hematological parameters were ANC (3370), lymphocyte (680), NLR (9.34), PLR (290.77), platelets (332,000), and WBCs (4390.65). The area under the curve (AUC) values for NLR (0.679) and ANC (0.631) were high, with the highest sensitivity and specificity, and could potentially be used to predict COVID-19 severity.

Conclusion: This study proved that high NLR and high ANC have prognostic value for assessing disease severity in COVID-19. Thus, assessing and considering these hematological parameters when triaging COVID-19 patients may prevent complications and improve the patient's outcome.

Keywords: COVID-19; disease’s severity; hematological parameters; prognostic value.