ObjectiveTo clarify the independent and synergistic effects of dyslipidemia in the progression of hepatic steatosis in metabolic dysfunction-associated fatty liver disease （MAFLD）. MethodsA total of 7 697 participants who underwent physical examination in Beijing Friendship Hospital， Capital Medical University， from January 2022 to December 2024 were enrolled， and finally 2 177 patients with MAFLD were enrolled as subjects. Transient elastography was used to quantify the severity of hepatic steatosis （grades S1-S3）. The multivariable ordinal Logistic regression analysis was used to investigate the independent and synergistic associations of serum triglyceride （TG）， high-density lipoprotein cholesterol （HDL-C）， and low-density lipoprotein cholesterol （LDL-C） with the severity of hepatic steatosis， and their interactions and potential nonlinear relationships with metabolic factors were also examined. One-way analysis of variance or Kruskal-Wallis H test was used for comparison of continuous data between groups， and chi-square test was used for comparison of categorical data between groups. ResultsAn increase in TG （odds ratio ［OR］=1.77， 95% confidence interval ［CI］： 1.48 — 2.10， P<0.001） and a reduction in HDL-C （OR=1.35， 95%CI： 1.11 — 1.65， P=0.003） were independently associated with a greater severity of hepatic steatosis， with the strongest association when both abnormalities coexisted （OR=2.40， 95%CI： 1.87 — 3.07， P<0.001）. The dose-response relationship analysis further revealed a nonlinear threshold effect of TG on hepatic steatosis at the threshold of 1.51 mmol/L （P_nonlinearity=0.001）， below which the severity of steatosis increased more rapidly with the increase in TG concentration （P=0.001）. The subgroup analysis showed that the association between the reduction in HDL-C and the severity of steatosis was observed only in males， young adults （aged <45 years）， and metabolically healthier subgroups （without diabetes， obesity， hyperuricemia or hypertension）. Significant interactions were observed between the presence or absence of obesity and the abnormal levels of TG and HDL‑C （both P_interaction<0.05）. The association of the increase in LDL-C with steatosis was confined to specific subgroups （without obesity or hyperuricemia）. ConclusionThe increase in TG and the reduction in HDL-C are independently associated with the severity of hepatic steatosis in MAFLD. The synergistic effect of blood lipids and their interactions with metabolic factors may further refine risk stratification， so as to provide a basis for precise management of MAFLD.

BACKGROUND:The causal relationship between modifiable factors such as lifestyle,metabolic characteristics,and nutritional intake and joint sports injuries has been increasingly recognized in clinical studies.However,the exact causal relationship between these modifiable factors and joint sports injuries remains unclear. OBJECTIVE:To investigate the causal relationship between modifiable factors and joint sports injuries using Mendelian randomization to provide a basis for sports injury prevention. METHODS:The GWAS dataset of intervening factors and joint sports injuries was obtained from publicly available data.The causal relationships between lifestyle,metabolic characteristics,nutritional intake,and joint sports injuries were explored using the inverse variance weighting method,the MR-Egger method,and the weighted median method.For sensitivity analyses,Cochran's Q test,MR-Egger regression,leave-one-out method,and MR-PRESSO were used to verify the stability and reliability of the results. RESULTS AND CONCLUSION:(1)In terms of lifestyle,coffee(OR=0.29,95%CI:0.10-0.79,P=0.016),and tea consumption(OR=0.41,95%CI=0.19-0.85,P=0.017)were associated with a decreased risk of ankle and foot joint sports injuries,and coffee consumption(OR=3.31,95%CI=1.02-10.73,P=0.046)was potentially causally associated with an increased risk of shoulder joint sports injuries;and never smoking(OR=0.78,95%CI=0.70-0.87,P=1.49×10-5)was significantly causally associated with a decreased risk of ankle and foot joint sports injuries.(2)In terms of metabolic characteristics,calcium levels(OR=0.88,95%CI=0.79-0.98,P=0.017)were potentially causally associated with a decreased risk of wrist and hand joint sports injuries.(3)In terms of nutritional intake,vitamin A intake(OR=1.08,95%CI:1.02-1.13,P=0.007)was potentially causally associated with increased risk of knee joint sports injury.(4)For the sensitivity analysis,Cochran's Q test showed the existence of heterogeneity(P<0.05),so the random effect model was used for the analysis.MR-Egger regression and MR-PRESSO test did not find evidence of pleiotropy(P>0.05),and the leave-one-out method showed that the results were stable after eliminating single nucleotide polymorphisms one by one.(5)This study preliminarily reveals the effects of modifiable factors,such as lifestyle,metabolic characteristics,and nutritional intake,on the risk of joint sports injuries.It provides valuable research evidence and guidance for the prevention of joint sports injuries.

Objective: To analyze the occupational health literacy (OHL) level and its influencing factors among key populations in the tertiary industry in Lu'an City, Anhui Province, so as to provide a basis for developing targeted health interventions and improving regional occupational health policies. Methods: A stratified cluster random sampling method was employed to select five categories of key populations from the tertiary industry in Lu'an City as study subjects from August to September 2024. Data on gender, age, education level, and OHL were collected through the National OHL Monitoring Questionnaire for Key Populations. The OHL levels were analyzed, and influencing factors of OHL levels among key populations were analyzed using a multivariable logistic regression model. Results: A total of 1 243 individuals were surveyed, comprising 700 (56.32%) males and 543 (43.68%) females. The median age was 42.00 (interquartile range, 17.00) years. There were 609 individuals with OHL, and the OHL level was 48.99%. The OHL levels in fundamental knowledge of occupational health protection, healthy work styles and behaviors, knowledge of occupational health laws, and basic skills for occupational health protection were 84.71%, 60.34%, 43.93%, and 37.09%, respectively. Multivariable logistic regression analysis showed that educational level (primary school and below, OR=0.149, 95%CI: 0.064-0.344; junior high school, OR=0.340, 95%CI: 0.184-0.629; high school, OR=0.408, 95%CI: 0.230-0.723), average monthly personal income (3 000-<5 000 yuan, OR=1.655, 95%CI: 1.092-2.508; 5 000-<7 000 yuan, OR=2.195, 95%CI: 1.302-3.699; ≥7 000 yuan, OR=2.062, 95%CI: 1.016-4.183), employer nature (private enterprises, OR=2.992, 95%CI: 1.569-5.443), and industry category (education, OR=3.423, 95%CI: 1.407-8.327; courier / food delivery services, OR=0.459, 95%CI: 0.268-0.787; healthcare, OR=7.539, 95%CI: 3.255-17.461) were statistically associated with the OHL level among key population. Conclusion The OHL level among key population in the tertiary industry of Lu'an City can be further enhanced, with educational level, average monthly personal income, employer nature, and industry category identified as the primary influencing factors.

BACKGROUND: Chronic liver disease (CLD), mainly non-alcoholic fatty liver disease (NAFLD), is a significant public health concern worldwide. This study aims to quantify the burden of NAFLD in CLD globally and within China, using data from the Global Burden of Disease (GBD) Study 2021, providing crucial insights for global and local health policies. METHODS: The study used comprehensive data from the GBD study 2021. It included estimates of prevalence, incidence, mortality, and disability-adjusted life years (DALYs). Age-standardized rates and average annual percent change (AAPC) from 2011 to 2021 were reported. A meticulous decomposition analysis was conducted. RESULTS: In 2021, there were 1582.5 million prevalent cases, 47.6 million incident cases, 1.4 million deaths, and 44.4 million DALYs attributable to CLD, globally. Among these, NAFLD has emerged as the predominant cause, accounting for 78.0% of all prevalent CLD cases (1234.7 million) and 87.2% of incident cases (41.5 million). Correspondingly, NAFLD had the highest age-standardized prevalence (15,017.5 per 100,000 population) and incidence (876.5 per 100,000 population) rates among CLDs. In addition, China's CLD age-standardized prevalence rate was 21,659.5 per 100,000 population, and the age-standardized incidence rate was 752.6 per 100,000 population, higher than the global average. From 2011 to 2021, the global prevalence rate of CLD increased slowly (AAPC = 0.17), consistent with the trend in China (AAPC = 0.23). Furthermore, the prevalence rate of NAFLD rose significantly in China (AAPC = 1.30) compared with the global average (AAPC = 0.91). Decomposition analysis also showed the worldwide increase in deaths and DALYs for NAFLD, which were primarily attributable to population growth and aging. CONCLUSIONS The burden of CLD and NAFLD remains substantial globally and within China in terms of high prevalence and incidence. As such, this underscores the need for targeted prevention and treatment strategies. These findings emphasize the importance of continued surveillance and research to mitigate the growing impact of liver diseases on global and Chinese health systems.
Humans ; Non-alcoholic Fatty Liver Disease/mortality* ; Global Burden of Disease ; China/epidemiology* ; Prevalence ; Male ; Disability-Adjusted Life Years ; Female ; Incidence ; Middle Aged ; Chronic Disease ; Adult ; Quality-Adjusted Life Years ; Liver Diseases/epidemiology* ; Aged

Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T _NANC), time to symptom improvement (T _SI), and time of hospital stay (T _HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T _NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.

Medical equipment, as an important indicator of smart hospital evaluation, plays a vital role in hospital operations. To ensure the safe and efficient operation of medical equipment, a reasonable performance evaluation system is indispensable. This study introduces a platform based on Internet of Things (IoT) technology that connects medical devices and collects data, achieving standardized and structured data processing, and supporting online operational supervision. Through the Delphi method, a performance evaluation system for large medical equipment is constructed, including 4 primary indicators and 22 secondary indicators. DICOM data acquisition devices are used to achieve functions such as efficiency analysis, benefit analysis, usage evaluation, and decision-making support for medical equipment. The study is still in its early stages, and in the future, it is expected to integrate more types of equipment, achieve rational resource allocation, and significantly impact decision-making for the development of public hospitals.
Internet of Things ; Delphi Technique

Objective To compare and find an optimal model for predicting the risk of DKD occurrence in patients with type 2 diabetes mellitus(T2DM).Methods A total of 2005 patients with T2DM were enrolled in this study from The Second Hospital of Shijiazhuang City during December 2017 to December 2022.All the subjects were divided into a training set(n=1403)and a validation set(n=602)according to the ratio of 3∶1 by simple random sampling.With the occurrence of DKD as the outcome variablein the training set,important feature variables were screened by LASSO regression.Six different machine learning models were established according to the feature variables,thenthe optimal model was determined by comparison,and anonlinerisk predictor for DKD occurrence was constructed in patients with T2DM.Results Taking the occurrence of DKD as the outcome variable in the training set,the results of LASSO regression analysis showed that the optimal value of the model was 10-fold cross validation lambda.1se=0.01662473,and 15 characteristic variables with nonzero coefficient were screened out to be related to the occurrence of DKD.The data included sex,age,family history of DM,DM duration,LDL-C,HbA1c,WBC,PDW,Scr,urine α1-microglobulin,urine β2-microglobulin,urine microalbumin,hypertension,hypokalemia,and DR.In the training set and validation set,the prediction performance of XGBoost model was better than that of other models(AUC=0.872,0.893,95%CI 0.853～0.891,0.865～0.921),the sensitivity was 0.779,0.863,and the specificity was 0.721,0.758,respectively.The F1 scores were 0.774 and 0.787.DCA analysis showed that the XGBoost model had a greater net benefit and threshold probability.According to the XGBoost model,the online predictor of DKD risk in T2DM patients was laid out,and two patients were selected for application,the results showed that the predictive value of the model was 0.185 in non-DKD patients,and the predictive value was 0.510 in DKD patients.Conclusions The XGBoost model is the best model for predicting the occurrence of DKD in T2DM patients,and an online predictor was successfully built.

Objective:To construct a risk prediction model for early post-injury respiratory failure in patients with traumatic cervical spinal cord injury (TCSCI) and validate its efficacy.Methods:A retrospective cohort study was conducted to analyze the clinical data of 393 TCSCI patients admitted to Zhengzhou Central Hospital Affiliated to Zhengzhou University from January 2020 to October 2024, including 294 males and 99 females, aged 18-82 years [59(45, 72)years]. Among them, 76 patients had respiratory failure (19.3%). The patients were randomly divided into the training set ( n=275) and validation set ( n=118) at a ratio of 7∶3. According to the presence of respiratory failure within one week after admission, 275 patients in the training set were divided into respiratory failure group ( n=53) and non-respiratory failure group ( n=222). The demographic data, injury characteristics, laboratory test results, and imaging findings of the patients were collected. Risk factors were determined through univariate analysis and multivariate Logistic regression analysis and a nomogram prediction model was constructed. The area under the receiver operating characteristic (ROC) curve (AUC) and Hosmer-Lemeshow test were used to evaluate the discrimination and calibration of the model. Decision curve analysis (DCA) was plotted to evaluate the clinical effectiveness of the prediction model. Results:The results of the univariate analysis showed that there were significant differences in history of respiratory diseases, causes of injury, Glasgow coma scale (GCS), American Spinal Injury Association (ASIA) classification, ASIA-motor score (AMS), injury severity score (ISS), clinical pulmonary infection score (CPIS), hypoproteinemia and cervical vertebra fracture and dislocation between the respiratory failure group and non-respiratory failure group in the training set ( P<0.05). The results of multivariate Logistic regression analysis indicated that GCS, ASIA classification, CPIS, and hypoproteinemia were independent risk factors for early post-injury respiratory failure in TCSCI patients ( P<0.05). Based on the above four variables, a Logistic regression equation was constructed: Logit( P)=2.361-0.675×ASIA classification+0.419×CPIS-0.358×GCS+0.854×hypoproteinemia. In the prediction model established based on this equation, the AUC was 0.96 (95% CI 0.94, 0.99) in the training set and 0.89 (95% CI 0.82, 0.96) in the validation set. In the calibration curves of the training set and validation set, the prediction curve and reference curve were approximately overlapping, with the average absolute errors of 0.04 and 0.03. DCA results demonstrated that both the training and validation sets exhibited positive net benefits when threshold probabilities fell within ranges of 0%-78% and 0%-87%, respectively. Conclusion:The risk prediction model for early post-injury respiratory failure in TCSCI patients based on GCS, ASIA classification, CPIS and hypoproteinemia has good predictive efficacy and clinical practicability.

Dendrobium is the largest genus of the Orchidaceae family.The fresh and dried stems of many species of this genus have been used as Shihu(Dendrobii Caulis)in traditional Chinese medicine,it is known as the foremost of the"Nine Great Herbs of China".Ancient texts highlight its uses for"strengthening yin,enhancing essence,nourishing the five viscera,alleviating fatigue,and dispelling skin heat and prickly heat".Modern research confirms that the polysaccharides and alkaloids it contains have antiviral ef-fects,it can apply in treating immunodeficiency caused by viral infections clinically.While studies are gradually uncovering the antivi-ral mechanisms and material basis of Dendrobium,the lack of systematic analysis and organization has hindered its resource develop-ment.The paper employed CiteSpace software for bibliometric analysis of Chinese and English literature on Dendrobium.It reviewed the herbalism,material basis,and mechanisms of its antiviral properties building upon the systematic review of ancient materia medica and modern literature.Results indicate that Dendrobium can boost vital energy and resist pathogens,showing great potential in antiviral drug development.

Crohn's disease (CD) is a refractory and recurrent chronic inflammatory bowel disease with an unclear etiology. In addition to intestinal symptoms, the disease is often accompanied by various extraintestinal manifestations. Studies have found that abnormalities in central nervous system activity in CD patients are closely related to the brain-gut axis, which may be one of the reasons for the high incidence of adverse emotions such as anxiety and depression. Functional magnetic resonance imaging (fMRI) has been widely used in the field of neurogastroenterology due to its non-invasiveness, high spatial resolution, and whole-brain coverage. This article reviews the application and progress of fMRI in CD brain functional study, aiming to comprehensively analyze and integrate the impact of the disease on brain function and provide a reference for clinical diagnosis, treatment, and future research.