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ORIGINAL ARTICLE
Year : 2022  |  Volume : 6  |  Issue : 2  |  Page : 115-118

Neutrophil and Platelet Count Upon Hospital Admission as Predictors of Severe COVID-19 Infection: An Observational Study


Department of Internal Medicine, Faculty of Medicine, Udayana University, Bali, Indonesia

Correspondence Address:
I Gde Raka Widiana
Department of Internal Medicine, Faculty of Medicine, Udayana University, Jl. PB Sudirman Denpasar 80232, Bali
Indonesia
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/bjoa.bjoa_48_22

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Background: The severity of COVID-19 infection may depend on severe inflammation and hypercoagulability mechanisms. These processes may be rapidly identified in peripheral blood tests. This study aims to determine whether components of complete blood counts are able to predict the severity of COVID-19 infection. Materials and Methods: This is a prospective, observational analytical study carried out in the Indonesian population. We included all patients admitted to our hospital for COVID-19 during a 3-month period. We obtained blood samples for complete blood count examinations upon hospital admission. Confirmation of COVID-19 infection was based on a polymerase chain reaction test. Severe COVID-19 infection was determined if the patients had a Severe Community-Acquired Pneumonia (SCAP) score of >10. We collected blood samples upon hospital admission for leukocyte, neutrophil, lymphocyte, platelet, and monocyte counts. Results: We included 131 patients consisting of 77 (58.8%) males and 54 (41.2%) females. There were significant associations between neutrophil count and SCAP score (r = 0.28; P = 0.001) and platelet count (r = 0.023; P = 0.007). Upon regression analysis, we found that every 1,000 declines in platelet count was associated with increased risk (0.8%) of severe COVID-19, whereas every 1,000 declines in the neutrophil count was associated with decreased risk (18%) of severe COVID-19. Conclusion: There is a significant, weak positive correlation between neutrophil and platelet counts and the severity of COVID-19 infection as expressed by the SCAP score.


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