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Hematological parameters and their predictive value for assessing disease severity in laboratory-confirmed COVID-19
Mezgebu Alemayehu Awoke1, Ayinshet Adane1, Belete Assefa1
1Department of Internal Medicine, School of Medicine, College of Medicine and Health Sciences, University of Gondar Gondar, Ethiopia.
Insights
High neutrophil-to-lymphocyte ratio (NLR) and absolute neutrophil count (ANC) can predict COVID-19 severity. These hematological parameters aid in early risk stratification and improving patient outcomes in Ethiopia.
Area of Science:
- Hematology
- Infectious Diseases
- Public Health
Background:
- COVID-19 has caused significant global mortality and morbidity.
- Early detection of severe COVID-19 cases is crucial for timely intervention.
- Current methods for predicting COVID-19 severity using hematological parameters are limited.
Purpose of the Study:
- To determine hematological parameters in COVID-19 patients.
- To assess the predictive value of these parameters for COVID-19 disease severity.
- To aid in early risk stratification of COVID-19 patients in Northwest Ethiopia.
Main Methods:
- A retrospective cross-sectional study of 253 COVID-19 patients admitted between March 2021 and February 2022.
- Hematological parameters were analyzed, with data processed using Epi-data and SPSS.
- Receiver-operating curve (ROC) analysis was employed to determine the predictive value of hematological parameters.
Main Results:
- Severe COVID-19 cases accounted for 43.87% of patients, with a 26.9% mortality rate.
- Optimal cutoff values for predicting severity were identified for ANC, lymphocyte, NLR, PLR, platelets, and WBCs.
- NLR (AUC=0.679) and ANC (AUC=0.631) demonstrated high predictive value for COVID-19 severity.
Conclusions:
- Elevated NLR and ANC are significant prognostic indicators for COVID-19 severity.
- Incorporating NLR and ANC assessment in COVID-19 patient triage can help prevent complications.
- These hematological markers can improve patient outcomes and management strategies.
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.
