ObjectiveTo investigate the clinical features of patients with acute-on-chronic liver failure （ACLF）， and to construct a risk scoring table that can accurately predict the prognosis of patients in the early stage. MethodsA retrospective analysis was performed for the clinical data of 502 patients with ACLF who were admitted to Tangdu Hospital， Air Force Medical University， from January 1， 2010 to December 31， 2020 （training set）， and the influencing factors for 28-day mortality rate were identified. The 69 ACLF patients who were admitted to Tangdu Hospital， Air Force Medical University， from January 1 to December 31， 2021 were enrolled as the validation set. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. A univariate Cox regression analysis was used to obtain the early warning indicators associated with the 28-day prognosis of ACLF patients， and variance inflation factors were used to assess multicollinearity among predictors； a multivariate Cox regression analysis was used to construct a risk model for ACLF prognosis （mortality）. A risk scoring table for ACLF prognosis （mortality） was developed based on regression coefficients （β） from the model equation and weight assignments in the nomogram. Internal validation and comparison were performed for the risk model for ACLF prognosis （mortality）， the scoring table for ACLF prognosis （mortality）， and other scoring models （Child-Turcotte-Pugh ［CTP］ score， Model for End-Stage Liver Disease ［MELD］ score， MELD combined with serum sodium concentration ［MELD-Na］ score， and integrated MELD ［iMELD］ score） in the training set， while external validation and comprehensive evaluation of the scoring table and the other scoring models were performed in the validation set. The Nagelkerke’s R² test and the Hosmer-Lemeshow test were used to assess the degree of fitting of the risk model for ACLF prognosis （mortality）， the scoring table for ACLF prognosis （mortality）， and other scoring models， and fitting curves were plotted. C-index was used to assess the discriminatory ability of the scoring table for ACLF prognosis （mortality） and the other scoring models， and the Z-test was used for comparison of C-index between different models. The decision curve analysis was used to compare the clinical benefits of the scoring table for ACLF prognosis （mortality） and the other scoring models. ResultsThe multivariate Cox regression analysis showed that age （hazard ratio ［HR］=1.027， 95% confidence interval ［CI］： 1.015 — 1.039， P<0.001）， hepatic encephalopathy grade （grade 1： HR=2.928， 95%CI： 1.463 — 5.858， P=0.002； grade 2： HR=3.811， 95%CI： 2.078 — 6.988， P<0.001； grade 3： HR=3.916， 95%CI： 1.917 — 8.001， P<0.001； grade 4： HR=6.966， 95%CI： 4.559 — 10.644， P<0.001）， an increase in total bilirubin （TBil） by ≥17.1 μmol/L per day （HR=1.771， 95%CI： 1.248 — 2.513， P=0.001）， creatinine （HR=1.005， 95%CI： 1.004 — 1.006， P<0.001）， neutrophil count （HR=1.092， 95%CI： 1.060 — 1.126， P<0.001）， and international normalized ratio （HR=1.298， 95%CI： 1.187 — 1.418， P<0.001） were independent risk factors associated with the 28-day mortality rate of ACLF patients， and a risk scoring table was constructed for ACLF prognosis （mortality）. The Nagelkerke’s R² test showed that the risk scoring table for ACLF prognosis （mortality） had an R² value of 0.599 in the training set and 0.722 in the validation set， which were higher than the R² values of CTP， MELD， MELD-Na， and iMELD scores. The Hosmer-Lemeshow test showed that the risk scoring table for ACLF prognosis （mortality） had a P value of 0.280 in the training set and 0.788 in the validation set. The C-index analysis showed that the scoring table had a higher C-index than the other scoring models in the validation set （all P<0.001）， as well as a higher C-index than CTP score in the training set （P<0.001）. The decision curve analysis showed that the risk scoring table for ACLF prognosis （mortality） had higher clinical net benefits than the other scoring models. ConclusionCompared with other scoring models currently used in clinical practice， the novel risk scoring table for ACLF prognosis （mortality） constructed based on the six predictive factors of age， hepatic encephalopathy grade， an increase in TBil by ≥17.1 μmol/L per day， creatinine， neutrophil count， and international normalized ratio has a relatively high value in predicting the 28-day prognosis of ACLF patients.

The objective of this study is to assess the current status of vaccination against respiratory disease among the elderly aged ≥60 and analyze the factors influencing vaccination rates at both service provider and recipient levels in Zhejiang Province. Using a stratified random sampling method, a questionnaire survey was conducted from September 2022 to January 2023 among elderly people aged ≥60 in 30 townships/streets in Zhejiang Province, as well as immunization planning staff at the provincial, municipal, county/district, and township/street levels. Logistic regression models were used to analyze the factors related to vaccination among elderly people in Zhejiang Province. Based on the Zhejiang Provincial Comprehensive Management Information System for Vaccine and Vaccination, the systematic coverage rates of influenza vaccine and pneumonia vaccine for the elderly were 21.76% and 4.57%, respectively. Multivariate logistic regression analysis indicated that advanced age ( OR=1.74, 95% CI: 1.51-1.99), knowing that influenza is more severe than the common cold ( OR=1.67, 95% CI: 1.37-2.04) and having heard of the influenza vaccine ( OR=9.78, 95% CI: 7.03-13.59) were motivating factors for elderly to receive influenza vaccines. Advanced age ( OR=1.71, 95% CI: 1.43-2.06), knowing the serious consequences of pneumonia in the elderly ( OR=1.93, 95% CI: 1.47-2.55) and knowing that pneumonia vaccines can prevent pneumonia ( OR=6.36, 95% CI: 4.84-8.36) were motivating factors for elderly to receive pneumonia vaccines. Zhejiang Immunization Program staff believed that the main reasons why the elderly aged ≥60 would not be vaccinated against influenza or pneumonia were that they felt they would not get sick (55.52% and 56.35% respectively), it would not be serious if get sick (47.73% and 37.46% respectively), lacking trust in vaccine efficacy and safety (38.31% and 43.69% respectively). Vaccination rates for influenza and pneumonia vaccines among the elderly aged ≥60 in Zhejiang Province are suboptimal. Advanced age, awareness of the severity of respiratory diseases and awareness of vaccines against such diseases are related factors for elderly individuals to receive influenza and pneumonia vaccines.

The objective of this study is to assess the current status of vaccination against respiratory disease among the elderly aged ≥60 and analyze the factors influencing vaccination rates at both service provider and recipient levels in Zhejiang Province. Using a stratified random sampling method, a questionnaire survey was conducted from September 2022 to January 2023 among elderly people aged ≥60 in 30 townships/streets in Zhejiang Province, as well as immunization planning staff at the provincial, municipal, county/district, and township/street levels. Logistic regression models were used to analyze the factors related to vaccination among elderly people in Zhejiang Province. Based on the Zhejiang Provincial Comprehensive Management Information System for Vaccine and Vaccination, the systematic coverage rates of influenza vaccine and pneumonia vaccine for the elderly were 21.76% and 4.57%, respectively. Multivariate logistic regression analysis indicated that advanced age ( OR=1.74, 95% CI: 1.51-1.99), knowing that influenza is more severe than the common cold ( OR=1.67, 95% CI: 1.37-2.04) and having heard of the influenza vaccine ( OR=9.78, 95% CI: 7.03-13.59) were motivating factors for elderly to receive influenza vaccines. Advanced age ( OR=1.71, 95% CI: 1.43-2.06), knowing the serious consequences of pneumonia in the elderly ( OR=1.93, 95% CI: 1.47-2.55) and knowing that pneumonia vaccines can prevent pneumonia ( OR=6.36, 95% CI: 4.84-8.36) were motivating factors for elderly to receive pneumonia vaccines. Zhejiang Immunization Program staff believed that the main reasons why the elderly aged ≥60 would not be vaccinated against influenza or pneumonia were that they felt they would not get sick (55.52% and 56.35% respectively), it would not be serious if get sick (47.73% and 37.46% respectively), lacking trust in vaccine efficacy and safety (38.31% and 43.69% respectively). Vaccination rates for influenza and pneumonia vaccines among the elderly aged ≥60 in Zhejiang Province are suboptimal. Advanced age, awareness of the severity of respiratory diseases and awareness of vaccines against such diseases are related factors for elderly individuals to receive influenza and pneumonia vaccines.

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.

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.