Prognostic Significance of Hematological Parameters and Ratios in COVID-19 Patients | Abstract

International Journal of Medical Research & Health Sciences (IJMRHS)
ISSN: 2319-5886 Indexed in: ESCI (Thomson Reuters)


Prognostic Significance of Hematological Parameters and Ratios in COVID-19 Patients

Author(s):Anjali Sharma, Mukul Singh, Manju Kumari*, Heena, Sunil Ranga and Jugal Kishore

Background and aim: Coronavirus Disease 2019 (COVID-19) is caused by the virus SARS-CoV-2 and has affected millions of individuals across the world. Various haematological parameters and prognostic factors have been studied in the Chinese population. We here aimed to evaluate these haematological parameters in the Indian population and to search for any early prognostic factors of severe illness. Material and methods: The haematological parameters were assessed in 829 COVID-19 positive patients. The trend of these parameters was studied in the hospitalized patients and these parameters were also compared between survived and expired patients with a two-tailed pair t-test in the SPSS software version. Results: Out of 829, 504 (60.79%) were males and 325 (42.46%) were females. Among these 67 (8.1%) expired. All the haematological parameters were within the normal range but when their trend was studied in repeated samples of hospitalized patients we found that there was a significant difference in platelet count (p=0.000), eosinophil count (p=0.020), and platelet to lymphocyte ratio (p=0.004). Also, the difference of WBC (p=0.000), lymphocyte count (p=0.001), neutrophil count (p=0.001) and NLR (p=0.006) was significant between survived and non-survived patients. The patients who died had higher WBC count (mean=9996/μl) and lymphopenia (25.19%) in comparison to those who survived (mean WBC=7656/μl and Lymphocyte=30.34%). They also had higher neutrophil count and NLR than survived patients. Conclusion: The parameters like WBC count, lymphocyte count, neutrophil count, and NLR are significantly higher in non-survived in COVID 19 positive patients. These parameters can serve as biomarkers in predicting the prognosis and severity of the disease.

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