Objective:To retrospectively analyze the characteristics and influencing factors of liver function changes in 111 elderly patients with COVID-19 pneumonia.Methods:111 elderly patients with COVID-19 admitted to the Department of Infectious Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology from February 5 to March 3, 2020 were enrolled. According to the severity of disease and liver function condition, they were divided into severe group ( n=40), normal group ( n=71), abnormal liver function group ( n=86) and normal liver function group ( n=25). The indexes related to liver function changes [total bilirubin (TBil), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP) and γ-glutamyl transferase (GGT)] and related influencing factors were analyzed. Results:Among 111 cases, 86 (77.5%) had abnormal liver function of varying degrees, and 28 (25.2%) had liver injury. The abnormal rates of TBil, AST, ALP and GGT were significantly higher in the severe group than normal group ( P<0.05). There were no significant differences in age, ribavirin, glucocorticoid and the application of lopinavir-ritonavir tablets between the abnormal liver function and the normal group ( P>0.05). The proportion of male was significantly higher in the abnormal liver function than normal liver function group ( P<0.05). Conclusion:Elderly COVID-19 patients have a higher proportion of abnormal liver function, and patients in the severe group are more likely to have higher level of TB, AST, ALP and GGT. The abnormal liver function may be related to the direct viral infection of the liver and the inflammatory immune response of the body after infection in elderly patients.

Background::Dual-energy computed tomography (DECT) is purported to accurately distinguish uric acid stones from non-uric acid stones. However, whether DECT can accurately discriminate ammonium urate stones from uric acid stones remains unknown. Therefore, we aimed to explore whether they can be accurately identified by DECT and to develop a radiomics model to assist in distinguishing them.Methods::This research included two steps. For the first purpose to evaluate the accuracy of DECT in the diagnosis of uric acid stones, 178 urolithiasis patients who underwent preoperative DECT between September 2016 and December 2019 were enrolled. For model construction, 93, 40, and 109 eligible urolithiasis patients treated between February 2013 and October 2022 were assigned to the training, internal validation, and external validation sets, respectively. Radiomics features were extracted from non-contrast CT images, and the least absolute shrinkage and selection operator (LASSO) algorithm was used to develop a radiomics signature. Then, a radiomics model incorporating the radiomics signature and clinical predictors was constructed. The performance of the model (discrimination, calibration, and clinical usefulness) was evaluated.Results::When patients with ammonium urate stones were included in the analysis, the accuracy of DECT in the diagnosis of uric acid stones was significantly decreased. Sixty-two percent of ammonium urate stones were mistakenly diagnosed as uric acid stones by DECT. A radiomics model incorporating the radiomics signature, urine pH value, and urine white blood cell count was constructed. The model achieved good calibration and discrimination {area under the receiver operating characteristic curve (AUC; 95% confidence interval [CI]), 0.944 (0.899–0.989)}, which was internally and externally validated with AUCs of 0.895 (95% CI, 0.796–0.995) and 0.870 (95% CI, 0.769–0.972), respectively. Decision curve analysis revealed the clinical usefulness of the model.Conclusions::DECT cannot accurately differentiate ammonium urate stones from uric acid stones. Our proposed radiomics model can serve as a complementary diagnostic tool for distinguishing them in vivo.