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- W3148248054 abstract "BACKGROUND: In Russia, a semi-quantitative CT 04 scoring system is used in the analysis of thoracic computed tomography (CT) scans of COVID-19 patients to grade the severity of lung lesions. Despite the widespread use of this approach, the scoring systems diagnostic accuracy for identification hospitalizations for patients with the disease is currently unknown.
 AIM: To evaluate the sensitivity, specificity, positive (PPV) and negative (NPV) predictive value of the CT 04 system for the triage of COVID-19 patients.
 MATERIALS AND METHODS: This retrospective study enrolled 575 patients of Moscow clinics with laboratory-verified COVID-19, aged 57.213.9 years, 55% females. All patients were examined with four consecutive chest CT scans, and the disease severity was assessed using the CT 04 scoring system. Sensitivity and specificity were calculated as conditional probabilities that a patient would experience clinical improvement or deterioration, depending on the preceding CT examination results. For the calculation of the NPV and PPV, we estimated the COVID-19 prevalence in Moscow. The data on total cases of COVID-19 from March 6 to November 28, 2020, were taken from the Rospotrebnadzor website. We used several ARIMA and EST models with different parameters to fit the data and forecast the incidence.
 RESULTS: The median specificity of the CT 04 scoring system was 69% (95% CI 32%, 100%), and the sensitivity was 92% (95% CI 74%, 100%). The best statistical model describing the epidemiological situation in Moscow was ARIMA (0,2,1). According to our calculations, with the predicted point prevalence of 9.6%, the values of PPV and NPV were 56% and 97%, correspondingly.
 CONCLUSION: The maximum Youdens index was observed for the period between the first and the second chest CT examinations when the majority of the included patients experienced clinical deterioration. The CT 04 scoring system makes it possible to safely exclude the development of pathological changes in patients with mild and moderate disease (categories CT-0 and CT-1), thereby optimizing the burden on hospitals in an unfavorable epidemic situation." @default.
- W3148248054 created "2021-04-13" @default.
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- W3148248054 date "2021-04-30" @default.
- W3148248054 modified "2023-09-27" @default.
- W3148248054 title "Diagnostic accuracy of computed tomography for identifying hospitalizations for patients with COVID-19" @default.
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- W3148248054 doi "https://doi.org/10.17816/dd46818" @default.
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