机构地区:[1]Essos Hospital Center, Yaoundé, Cameroon [2]Health Ebene consulting, Research Department, Yaoundé, Cameroon [3]Higher Institute of Medical Technology, Yaoundé, Cameroon [4]Ministry of Public Health, Yaoundé, Cameroon [5]Faculty of Medicine and Biomedical Sciences, Yaoundé, Cameroon [6]African Population and Health Research Center, Yaoundé, Cameroon
出 处:《Advances in Infectious Diseases》2023年第1期12-20,共9页传染病进展(英文)
摘 要:Objective: To evaluate the lung CT scan as a possible predictive diagnostic method for COVID-19 in the Cameroonian context. Methods: We designed a cross sectional study. Suspected cases of COVID-19 during the first wave at the national social insurance fund (NSIF) hospital were screened with both COVID-19 with lung CT scan and a PCR test. Univariate analysis was performed for sample description and multivariate analysis to assess the correlation between positive results for the PCR and other parameters. We estimated the optimum threshold of sensitivity/specificity, and area under curve using the empirical method and package. Results: A total of 62 suspected COVID-19 cases were recorded, predominantly males (Sex Ratio = 2.2) with a median age of 58.5 (IQR = 19.7). Among our 62 patients, 29 (46.8%) were confirmed COVID-19 cases with positive PCR results. All the patients had a thorax CT scan with a median impairment of 40% (IQR = 20%). The optimum threshold estimate for CT scan for COVID-19 infection diagnosis was 60% (95% CI = 25% - 80%). Overall, the sensitivity and specificity estimates were 0.30 (95% CI = 0.15 - 0.49) and 0.87 (95% CI = 0.70 - 0.96), respectively, leading to an Area Under Curve (AUC) estimate of 0.59 (95% CI = 0.46, 0.71). Conclusion: In this setting, lung CT scan was neither sensitive nor specific to predict COVID-19 disease.Objective: To evaluate the lung CT scan as a possible predictive diagnostic method for COVID-19 in the Cameroonian context. Methods: We designed a cross sectional study. Suspected cases of COVID-19 during the first wave at the national social insurance fund (NSIF) hospital were screened with both COVID-19 with lung CT scan and a PCR test. Univariate analysis was performed for sample description and multivariate analysis to assess the correlation between positive results for the PCR and other parameters. We estimated the optimum threshold of sensitivity/specificity, and area under curve using the empirical method and package. Results: A total of 62 suspected COVID-19 cases were recorded, predominantly males (Sex Ratio = 2.2) with a median age of 58.5 (IQR = 19.7). Among our 62 patients, 29 (46.8%) were confirmed COVID-19 cases with positive PCR results. All the patients had a thorax CT scan with a median impairment of 40% (IQR = 20%). The optimum threshold estimate for CT scan for COVID-19 infection diagnosis was 60% (95% CI = 25% - 80%). Overall, the sensitivity and specificity estimates were 0.30 (95% CI = 0.15 - 0.49) and 0.87 (95% CI = 0.70 - 0.96), respectively, leading to an Area Under Curve (AUC) estimate of 0.59 (95% CI = 0.46, 0.71). Conclusion: In this setting, lung CT scan was neither sensitive nor specific to predict COVID-19 disease.
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