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Published on: December 19, 2020
Hematocytological Clues of Peripheral Blood in Different Clinical Presentations of COVID-19
Seyede Fakhri Mohaghagh Zahed1, Shahriar Dabiri1, Abdolreza Javadi2
1Pathology and Stem Cells Research Centers, Pathology Department, Afzalipour Medical School, Kerman Medical Sciences University, Kerman, Iran.
Background:
To gain insight into the pathogenesis and clinical course of COVID-19 from a historical perspective, we reviewed paraclinical diagnostic tools of this disease and prioritized the patients with a more severe form of disease admitted to intensive care units (ICUs). The objective was to better predict the course and severity of the disease by collecting more paraclinical data, specifically by examining the relationship between hematological findings and cytological variation of blood neutrophils and monocytes.
Methods:
This retrospective study was conducted on 112 patients with confirmed COVID-19 admitted to Imam Hossein Hospital (Tehran, Iran) from August to September 2020. Peripheral blood smears of these patients were differentiated according to several cytological variations of neutrophils and monocytes, and the correlation to the severity of the disease was specified.
Results:
The mean percentages of degenerated monocytes, degenerated granulocytes, and spiky biky neutrophils were significantly different among critical and non-critical patients (P<0.05). Degenerated monocytes and granulocytes were higher in critical patients as opposed to spiky biky neutrophils, which were higher among non-critical ones. Comparing the peripheral blood smears of COVID-19 patients (regarding pulmonary involvement in chest computed tomography [CT] scans [subtle, mild, moderate, and severe groups]), the twisted form of neutrophils was significantly higher in the subtle group than in the mild and moderate groups (P=0.003).
Conclusion:
Different cytological morphologies of neutrophils and monocytes, including degenerated monocytes, degenerated granulocytes, and spiky biky and twisted neutrophils, could help to predict the course and severity of the disease.
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