ISSN: 2147-2092
Evaluation of Clinical Laboratory Findings with Computed Tomography Segmentation-Volume Analysis Results in COVID-19 Patients
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Original Investigation
VOLUME: 34 ISSUE: 1
P: 43-48
January 2023

Evaluation of Clinical Laboratory Findings with Computed Tomography Segmentation-Volume Analysis Results in COVID-19 Patients

GMJ 2023;34(1):43-48
DOI: 10.12996/gmj.2023.8
Ahmet Rıfat Balık 1
Cigdem Yucel 1
Erdim Sertoglu 2
Ozlem Yavuz 2
Gurhan Taskin 3
Emrah Akkoyun 4
Kemal Niyazi Arda 5
Taner Ozgurtas 2
1. Health Sciences University Gülhane Training and Research Hospital Department of Medical Biochemistry, Ankara, Turkey
2. University of Health Sciences, Gülhane Training and Research Hospital, Department of Clinical Biochemistry, Ankara, Turkey
3. University of Health Sciences, Gülhane Training and Research Hospital, Department of Internal Medicine, Ankara, Turkey
4. Middle East Technical University, Informatics Institute, Department of Health Informatics, Ankara, Turkey
5. University of Health Sciences, Gülhane Training and Research Hospital, Department of Radiology, Ankara, Turkey
No information available.
No information available
Received Date: 14.02.2022
Accepted Date: 18.05.2022
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ABSTRACT

Objective:

COVID-19 is a disease caused by SARS-COV-2 and early diagnosis and classification of the COVID-19 are critical for the better prognosis. This study aimed to combine laboratory data of COVID-19 patients with Computed Tomography Segmentation-Volume Analysis (CT-SVA). Thus, we hope to contribute to the early diagnosis and classification of the disease.

Methods:

Patients were divided into two groups according to disease severity as mild/moderate (n=41) and severe/critical (n=42). Some laboratory parameters were recorded and evaluated together with CT-SVA.

Results:

The results of the study have shown that sodium, C-reactive protein, D-dimer, ferritin, fibrinogen, interleukin 6, procalcitonin, white blood cells, neutrophil, neutrophil-lymphocyte ratio values were significantly higher at first admission in the severe/critical diseased group (p<0.05), while albumin, lymphocyte, and venous blood pH values were significantly lower (p<0.05). CT-SVA results have shown negative correlation with albumin, while having a positive correlation with C-reactive protein, D-dimer, ferritin, fibrinogen, interleukin 6 and procalcitonin. The results of the performed Receiver Operating Characteristics analysis revealed that CT-SVA has a cut-off value of 15.92 with a sensitivity of 87.1% and a specificity of 80.0% in predicting disease severity. Binary logistic regression model has included CT-SVA, D-dimer, ferritin, interleukin 6, and neutrophil-lymphocyte ratio. The model correctly classified 88.1% of cases. CT-SVA, D-dimer, ferritin, interleukin 6, and neutrophil-lymphocyte ratio were detected to be the independent predictors of disease severity.

Conclusion:

Evaluation of laboratory parameters together with CT-SVA results will help identification of cases with a poor prognosis and accelerate intervention.

Keywords:
COVID-19, computed tomography, laboratory parameters, inflammation, biomarker, risk factor