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Objective:To establish a model C-GALAD for detecting hepatocellular carcinoma (HCC) from the chronic liver disease and healthy people based on the serum markers.Methods:A clinical cohort including 229 hepatocellular carcinoma patients, 2 317 patients with chronic liver disease and 982 healthy people, was retrospectively collected from eight hospitals or physical examination institutions from April 2018 to October 2020. The data were divided into a training set and a testing set by stratified sampling with a 6∶4 ratio. A predictive model was established on the training set using a logistic backward regression method and validated on the testing set. In addition, clinical data from March to July 2021 in Beijing You′ an Hospital affiliated to Capital Medical University, including 84 patients with liver cancer and 204 patients with chronic liver disease collected were used for external independent validation of the model. The receiver operating characteristic curve (ROC) area under curve (AUC), the sensitivity and the specificity were used to evaluate the effectiveness of the model.Results:Through the logistic backward regression method, the seven signatures including age, gender, alpha-fetoprotein (AFP), alpha-fetoprotein alloplasm-3 ratio (AFP-L3%), des-gamma-carboxyprothrombin(DCP), platelet (PLT) and total bilirubin (TBIL) were selected as risk factors in the detection model. The area under the ROC curve (AUC) of the model on the testing set was 0.954, with an 88.04% sensitivity and a 94.85% specificity, and the AUC of model on the external independent validation set was 0.943, with an 89.29% sensitivity and a 90.2% specificity, which were better than other published models.Conclusion:The C-GALAD Ⅱ model can accurately predict the risk of hepatocellular carcinoma occurrence, and thus provide a trustworthy diagnosis method of hepatocellular carcinoma.
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Objective To investigate the epidemiological characteristics of metabolic syndrome in the elderly, and to develop scientific prevention and control measures. Methods Physical examination personnel in Xianyang district from January 2017 to January 2020 were selected by random sampling method. The prevalence and epidemiological characteristics of the patients with metabolic syndrome were calculated according to the diagnostic criteria of metabolic syndrome. Intervention measures were implemented for patients with metabolic syndrome, and changes in survival and body quality were compared before and after intervention. SPSS 20.0 software was used for T test, rank sum test and Spearman rank correlation analysis, and the test level was α=0.05. Results There were 587 cases of metabolic syndrome in Xianyang area, and the overall prevalence rate was 13.81%. Complete clinical data of 566 elderly patients with metabolic syndrome were obtained. Age of 60~69 years old, overweight, obesity, activity time 1). After the intervention, scores of diet management, exercise management and cognition management in all age groups were higher than those before the intervention (P<0.05). In addition, values of triglyceride, high-density lipoprotein and BMI were better than those before the intervention (P<0.05). Conclusion Age of 60~69 years old, overweight, obesity, activity time <3 hours per day, sitting time ≥8 hours per day, smoking and alcohol consumption are the risk factors for the occurrence of metabolic syndrome in the elderly. Targeted interventions are of vital importance in helping patients to establish suitable self-management and executive ability.
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Autoimmune disease is a kind of immune dysfunction disease caused by gene and environmental factors. At present, there are some difficulties in early diagnosis, prognosis evaluation and curative effect evaluation. More and more autoantibodies have been found and confirmed to be closely related to the occurrence and development of autoimmune diseases with the deepening of related research. Accurate autoantibody detection is helpful to improve the diagnostic efficiency, therapeutic effect and quality of life of patients with autoimmune diseases.
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Among the theories supporting the increase of incidence of allergy during the last several decades is the concept that environmental pollutants may play a vital role. The present review reported the effect of different types of pollutants on the development, modulation and persistence of allergic reactions. It analyzed how pollutants including ozone, nitrogen dioxide and particulate materials contribute to allergy directly and indirectly. It reviewed several possible mechanisms involved in the enhancement of allergic inflammation by air pollutants. Finally, it made a delineation of many factors affecting allergy, which could provide useful information on the prevention of allergy.