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Are Lymphocytes and Eosinophils Associated with the COVID-19 Severity: A Large, Retrospective Study
Dildar Duman1, Zuhal Karakurt2, Nagihan Durmuş Koçak1
1Department of Pulmonology, University of Health Sciences, Süreyyapaşa Chest Diseases and Thoracic Surgery Training and Research Hospital, İstanbul, Turkey.
Insights
Low lymphocyte counts and percentages in COVID-19 patients predict severe disease and intensive care unit admission. These biomarkers can help physicians manage coronavirus disease 2019 earlier.
Area of Science:
- Hematology
- Infectious Diseases
- Critical Care Medicine
Background:
- Coronavirus disease 2019 (COVID-19) presents a significant global health challenge with high morbidity and mortality.
- Understanding predictors of COVID-19 severity is crucial for timely and effective patient management.
Purpose of the Study:
- To investigate the association between demographic factors, lymphocyte levels, and eosinophil levels with COVID-19 severity at hospital admission.
- To identify reliable biomarkers for predicting the need for intensive care unit (ICU) admission in COVID-19 patients.
Main Methods:
- A retrospective, observational study included 5828 COVID-19 patients, categorized by severity (outpatient, inpatient, critically ill).
- Demographic data and hemogram values (lymphocyte and eosinophil counts/percentages) were analyzed.
- Receiver operating characteristic (ROC) curves and logistic regression were used to assess predictive values for severity and ICU demand.
Main Results:
- Lymphocyte count and percentage were significantly different across severity groups, unlike eosinophil levels.
- Specific cutoff values for lymphocytes (count <1.0 × 10^9/L, percentage <22%) and eosinophils (percentage <0.08%) were identified as high-risk indicators for ICU admission.
- COVID-19 patients over 55 with low lymphocyte counts/percentages and low eosinophil percentages faced a doubled risk of requiring ICU management.
Conclusions:
- Lymphocyte counts and percentages serve as rapid and dependable biomarkers for predicting COVID-19 severity.
- These hematological markers can assist clinicians in earlier and more appropriate management strategies for COVID-19 patients.
Objective:
Coronavirus disease 2019 is an ongoing disease with high morbidity and mortality. We aimed to investigate the relationship between demographics, lymphocytes, eosinophils, and the coronavirus disease 2019 severity at hospital admission.
Material And Methods:
A retrospective, observational cross-sectional study was carried out with 5828 coronavirus disease 2019 patients between March 11, 2020, and November 30, 2020. Patients were divided into 3 groups according to where they were followed up as an indicator of disease severity, namely outpatients, inpatients, and critically ill patients. The patients' demographics and hemogram values on admission were recorded. The predictive accuracies of lymphocyte count, lymphocyte percentage, eosinophil count, and eosinophil percentage for predicting severity were determined using receiver operating characteristic curves. Logistic regression analysis was used to predict intensive care unit demand according to lymphocyte and eosinophil values.
Results:
Of the 5828 coronavirus disease 2019 patients, 4050 were followed up as outpatients, 1581 were hospitalized in a ward, and 197 were hospitalized in the intensive care unit. Lymphocyte count and lymphocyte percentage were significantly different between the groups, but the difference for eosinophil count and eosinophil percentage was not significant as it was for lymphocytes. Cutoff values for lymphocyte count (1.0 × 109 /L), lymphocyte percentage (22%), eosinophil count (0.052 × 109 /L), and eosinophil percentage (0.08%) were found to indicate a high risk for intensive care unit admission. Coronavirus disease 2019 patients >55 years of age, with a lymphocyte count <1.0 × 109 /L, a lymphocyte percentage <22%, and an eosinophil percentage <0.08% had a 2-fold higher risk of requiring intensive care unit management.
Conclusion:
Lymphocyte counts and percentages are quick and reliable biomarkers for predicting coronavirus disease 2019 severity and may guide physicians for proper management earlier.
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