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Associated Biochemical and Hematological Markers in COVID-19 Severity Prediction
Anit Lamichhane1,2, Sushant Pokhrel1, Tika Bahadur Thapa2
1Department of Laboratory Medicine, Manmohan Memorial Institute of Health Sciences, Kathmandu, Nepal.
Insights
Biomarkers like D-dimer, CRP, LDH, and neutrophil count can predict COVID-19 severity. Early analysis of these laboratory parameters aids in predicting disease progression and informing interventions.
Area of Science:
- Clinical Medicine
- Biochemistry
- Hematology
Background:
- The COVID-19 pandemic necessitates research into disease progression and effective interventions.
- Biomarkers are crucial for understanding COVID-19 severity and guiding treatment strategies.
Purpose of the Study:
- To assess correlations between laboratory parameters and COVID-19 severity.
- To identify predictive biomarkers for severe COVID-19 infection.
Main Methods:
- 191 COVID-19 patients were categorized into severe and non-severe groups based on clinical outcomes.
- Laboratory parameters including inflammatory markers (LDH, D-dimer, CRP, ferritin), CBC, LFTs, and RFTs were analyzed.
- Binary logistic regression and ROC curve analysis were used to identify risk factors and assess predictive values.
Main Results:
- Older age and comorbidities (CKD, HTN, DM, COPD, pneumonia) were associated with severe COVID-19.
- Significant independent risk factors for severity included D-dimer, CRP, LDH, SGPT, neutrophil count, and LMR.
- D-dimer showed the highest AUC (0.874) for predicting severity, with specific cut-off values identified for several parameters.
Conclusions:
- Biochemical and hematological parameters, with established cut-off values, can predict COVID-19 severity.
- Biomarkers such as D-dimer, CRP, LDH, ALT, and neutrophil count are valuable for predicting disease severity.
- Timely analysis of these markers enables early prediction of COVID-19 progression.
Background:
The global threat of COVID-19 has created the need for researchers to investigate the disease's progression, especially through the use of biomarkers to inform interventions. This study aims to assess the correlations of laboratory parameters to determine the severity of COVID-19 infection.
Methods:
This study was conducted among 191 COVID-19 patients in Sumeru Hospital, Lalitpur, Nepal. According to their clinical outcomes, these patients were divided into severe and nonsevere groups. Inflammatory markers such as LDH, D-dimer, CRP, ferritin, complete blood cell count, liver function tests, and renal function tests were performed. Binary logistic regression analysis determined relative risk factors associated with severe COVID-19. The area under the curve (AUC) was calculated with ROC curves to assess the potential predictive value of risk factors.
Results:
Out of 191 patients, 38 (19.8%) subjects died due to COVID-19 complications, while 156 (81.7%) survived and were discharged from hospital. The COVID-19 severity was found in patients with older age and comorbidities such as CKD, HTN, DM, COPD, and pneumonia. Parameters such as d-dimer, CRP, LDH, SGPT, neutrophil, lymphocyte count, and LMR were significant independent risk factors for the severity of the disease. The AUC was highest for d-dimer (AUC = 0.874) with a sensitivity of 82.2% and specificity of 81.2%. Similarly, the cut-off values for other factors were age >54.5 years, D-dimer >0.91 ng/ml, CRP >82.4 mg/dl, neutrophil >78.5%, LDH >600 U/L, and SGPT >35.5 U/L, respectively.
Conclusion:
Endorsement of biochemical and hematological parameters with their cut-off values also aids in predicting COVID-19 severity. The biomarkers such as D-dimer, CRP levels, LDH, ALT, and neutrophil count could be used to predict disease severity. So, timely analysis of these markers might allow early prediction of disease progression.
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