Scharf, Gregor and Meiler, Stefanie and Zeman, Florian and Schaible, Jan and Poschenrieder, Florian and Knobloch, Charlotte and Kleine, Henning and Scharf, Sophie Elisabeth and Dinkel, Julien and Stroszczynski, Christian and Zorger, Niels and Hamer, Okka Wilkea (2022) Combined Model of Quantitative Evaluation of Chest Computed Tomography and Laboratory Values for Assessing the Prognosis of Coronavirus Disease 2019. ROFO-FORTSCHRITTE AUF DEM GEBIET DER RONTGENSTRAHLEN UND DER BILDGEBENDEN VERFAHREN, 194 (07). pp. 737-746. ISSN 1438-9029, 1438-9010
Full text not available from this repository. (Request a copy)Abstract
Purpose To assess the prognostic power of quantitative analysis of chest CT, laboratory values, and their combination in COVID-19 pneumonia. Materials and Methods Retrospective analysis of patients with PCR-confirmed COVID-19 pneumonia and chest CT performed between March 07 and November 13, 2020. Volume and percentage (PO) of lung opacifications and mean HU of the whole lung were quantified using prototype software. 13 laboratory values were collected. Negative outcome was defined as death, ICU admittance, mechanical ventilation, or extracorporeal membrane oxygenation. Positive outcome was defined as care in the regular ward or discharge. Logistic regression was performed to evaluate the prognostic value of CT parameters and laboratory values. Independent predictors were combined to establish a scoring system for prediction of prognosis. This score was validated on a separate validation cohort. Results 89 patients were included for model development between March 07 and April 27, 2020 (mean age: 60.3 years). 38 patients experienced a negative outcome. In univariate regression analysis, all quantitative CT parameters as well as C-reactive protein (CRP), relative lymphocyte count (RLC), troponin, and LDH were associated with a negative outcome. In a multivariate regression analysis. PO, CRP, and RLC were independent predictors of a negative outcome. Combination of these three values showed a strong predictive value with a C-index of 0.87. A scoring system was established which categorized patients into 4 groups with a risk of 7 %, 30 %, 67%, or 100% for a negative outcome. The validation cohort consisted of 28 patients between May 5 and November 13, 2020. A negative outcome occurred in 6 % of patients with a score of 0, 50% with a score of 1, and 100 % with a score of 2 or 3. Conclusion The combination of PO, CRP, and RLC showed a high predictive value for a negative outcome. A 4-point scoring system based on these findings allows easy risk stratification in the clinical routine and performed exceptionally in the validation cohort.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | COVID-19; CT; PNEUMONIA; COHORT; COVID-19; computed X-Ray tomography; pneumonia; artificial intelligence; lung volume measurements; laboratory tests |
| Subjects: | 600 Technology > 610 Medical sciences Medicine |
| Divisions: | Medicine > Lehrstuhl für Röntgendiagnostik Medicine > Zentren des Universitätsklinikums Regensburg > Zentrum für Klinische Studien |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 05 Dec 2023 14:46 |
| Last Modified: | 05 Dec 2023 14:46 |
| URI: | https://pred.uni-regensburg.de/id/eprint/56934 |
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