1.Progress on the application of porcelain veneers in the restoration of dental fluorosis and its influencing factors
Ming DING ; Yidi JIANG ; Zhu CHEN
Chinese Journal of Endemiology 2023;42(2):169-172
Due to the cloud-like appearance of the dental surface of dental fluorosis, serious tooth defect may occur, thus affecting the overall beauty of the face. The clinical effect of dental fluorosis is not better than that of normal teeth in the application of repair, which brings some difficulties to the clinicians. The application of porcelain veneers in the restoration of dental fluorosis has been widely concerned by clinicians and researchers due to its advantages of high aesthetics, small amount of tooth tissue abrasion, and good biocompatibility. Therefore, this article comprehensively discusses the application effect and influencing factors of porcelain veneers in the restoration of dental fluorosis, in order to provide some reference for clinical application.
2.Clinical features and early warning indicators of patients with acute-on-chronic liver failure and bacterial infection
Zhanhu BI ; Linxu WANG ; Haifeng HU ; Hong DU ; Yidi DING ; Xiaofei YANG ; Jiayi ZHAN ; Fei HU ; Denghui YU ; Hongkai XU ; Jianqi LIAN
Journal of Clinical Hepatology 2024;40(4):760-766
ObjectiveTo investigate the clinical features of patients with acute-on-chronic liver failure (ACLF) and bacterial infection and early warning indicators associated with multidrug-resistant infections. MethodsA retrospective analysis was performed for 130 patients with ACLF and bacterial infection who attended The Second Affiliated Hospital of Air Force Medical University from January 1, 2010 to December 31, 2021, and according to the drug susceptibility results, the patients were divided into multidrug-resistant (MDR) bacterial infection group with 80 patients and non-MDR bacterial infection group with 50 patients. General information and laboratory examination results were compared between the two groups to screen for the early warning indicators associated with MDR bacterial infection. The Student’s t-test was used for comparison of normally distributed continuous data with homogeneity of variance between two groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data or continuous data with heterogeneity of variance between two groups; the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. The binary logistic regression analysis and the receiver operating characteristic (ROC) curve were used to assess the predictive value of early warning indicators. ResultsAmong the 130 patients with ACLF and bacterial infection, sputum (27.7%) was the most common specimen for detection, followed by blood (24.6%), urine (18.5%), and ascites (17.7%). Bacterial infections were dominated by Gram-negative bacteria (58.5%). Of all bacteria, Escherichia coli (18.5%), Klebsiella pneumoniae (14.6%), and Enterococcus faecium (13.8%) were the most common pathogens. Gram-positive bacteria had a high resistance rate to the antibacterial drugs such as erythromycin (72.2%), penicillin (57.4%), ampicillin (55.6%), and ciprofloxacin (53.7%), while Gram-negative bacteria had a high resistance rate to the antibacterial drugs such as ampicillin (73.3%), cefazolin (50.0%), and cefepime (47.4%). The patients with ACLF and bacterial infection had a relatively high rate of MDR bacterial infection (61.5%). Comparison of clinical data between the two groups showed that compared with the patients with non-MDR bacterial infection, the patients with MDR bacterial infection had significantly higher levels of alanine aminotransferase (Z=2.089, P=0.037), aspartate aminotransferase (Z=2.063, P=0.039), white blood cell count (Z=2.207, P=0.027), and monocyte count (Z=4.413, P<0.001). The binary logistic regression analysis showed that monocyte count was an independent risk factor for MDR bacterial infection (odds ratio=7.120, 95% confidence interval [CI]: 2.478 — 20.456,P<0.001) and had an area under the ROC curve of 0.686 (95%CI: 0.597 — 0.776) in predicting ACLF with MDR bacterial infection(P<0.001), with the optimal cut-off value of 0.50×109/L, a sensitivity of 0.725, and a specificity of 0.400. ConclusionACLF combined with bacterial infections is mainly caused by Gram-negative bacteria, with the common pathogens of Escherichia coli and Klebsiella pneumoniae and a relatively high MDR rate in clinical practice. An increase in monocyte count can be used as an early warning indicator to distinguish MDR bacterial infection from non-MDR bacterial infection.