Artikel: Diagnostic Efficacy of Chest Computed Tomography for Coronavirus Disease 2019.
Journal of medical signals and sensors
2023 Band 13, Heft 2, Seite(n) 129–135
Abstract: Background: A significant discrepancy between the results of previous studies is identified regarding the diagnostic efficacy of chest computed tomography (CT) for coronavirus disease 2019 (COVID-19). We aimed to evaluate the diagnostic efficacy of ... ...
Abstract | Background: A significant discrepancy between the results of previous studies is identified regarding the diagnostic efficacy of chest computed tomography (CT) for coronavirus disease 2019 (COVID-19). We aimed to evaluate the diagnostic efficacy of chest CT for COVID-19. Methods: Suspected cases of COVID-19 with fever, cough, dyspnea, and evidence of pneumonia on chest CT scan were enrolled in the study. The accuracy, sensitivity, and specificity of chest CT were determined according to real-time reverse transcriptase-polymerase chain reaction (RT-PCR) results as the gold standard method. Results: The study population comprised 356 suspected cases of COVID-19 (174 men and 182 women; age range 3-96 years; mean age ± standard deviation, 55.21 ± 18.38 years). COVID-19 patients were diagnosed using chest CT with 89.8% sensitivity, 78.1% accuracy, 21.3% specificity, 84.7% positive predictive value, and 30.23% negative predictive value. The odds ratio was 2.39 (95% confidence interval, 1.16-4.91). Typical CT manifestations of COVID-19 were observed in 48 (13.5%) patients with negative RT-PCR results and 30 (8.4%) patients with confirmed positive RT-PCR results had no radiological manifestations. Kappa coefficient of chest CT for diagnosis of COVID-19 was 0.78. Conclusion: The results show that when RT-PCR results are negative, chest CT could be considered as a complementary diagnostic method for the diagnosis of COVID-19 patients. A more comprehensive diagnostic method could be established by combining the chest CT examination, clinical symptoms, and RT-PCR assay. |
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Sprache | Englisch |
Erscheinungsdatum | 2023-05-29 |
Erscheinungsland | India |
Dokumenttyp | Journal Article |
ZDB-ID | 2651622-6 |
ISSN | 2228-7477 |
ISSN | 2228-7477 |
DOI | 10.4103/jmss.jmss_118_21 |
Datenquelle | MEDical Literature Analysis and Retrieval System OnLINE |
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