ObjectiveTo investigate the independent predictive factors for 90-day mortality in patients with acute-on-chronic liver failure （ACLF）， to establish a risk predictive model， and to assess its predictive efficacy in comparison with MELD， MELD-Na， MELD 3.0， and COSSH-ACLF Ⅱ. MethodsA retrospective analysis was performed for the clinical data of 394 patients with ACLF who were admitted to The Affiliated Hospital of Inner Mongolia Medical University and Hohhot Second Hospital from July 2018 to July 2024， and general information and laboratory markers on admission were collected from all patients. The independent-samples t test or the Mann-Whitney U test was used for comparison of quantitative data between two groups， and the chi-square test or the adjusted chi-square test was used for comparison of qualitative data between two groups. The LASSO regression analysis was used to identify related variables， and the multivariate logistic regression analysis was used to establish a predictive model and generate a nomogram. The receiver operating characteristic （ROC） curve， the area under the ROC curve （AUC）， calibration curve， and clinical decision curve were used to assess the performance of the model. ResultsA total of 394 patients with ACLF were included in this study， with 136 patients in the training set， 58 in the internal validation set， and 200 in the external validation set. The cohort had a mean age of 52.9±11.7 years， among whom male patients accounted for 72.84% （287/394）， the patients with HBV infection accounted for 22.33% （88/394）， the patients with alcohol-related causes accounted for 45.94% （181/394）， and the patients with other causes （including drug-induced and autoimmune diseases） accounted for 31.73% （125/394）. The overall 90-day mortality rate was 27.41% （108/394）. The multivariate logistic regression analysis showed that diabetes （odds ratio ［OR］= 5.831， 95% confidence interval ［CI］： 1.587 — 21.424， P=0.008）， cystatin C （Cys-C） （OR=2.984， 95%CI： 1.501 — 5.933， P=0.002）， and spontaneous peritonitis （SBP） （OR=5.692， 95%CI： 2.150 — 15.071， P<0.001） were independent risk factors， and a nomogram was generated based on these factors. This model had an AUC of 0.836 in the training set， 0.881 in the internal validation set， and 0.878 in the external validation set， showing a good discriminatory ability. The calibration curve showed a good degree of fitting， with a relatively high net clinical benefit. The subgroup analysis based on etiology showed that the model had an AUC of 0.850 in the patients with HBV infection， 0.858 in the patients with alcohol-induced ACLF， and 0.908 in the patients with other etiologies， indicating that the model had a good discriminatory ability across the populations with different etiologies. Compared with traditional scores， the model （AUC=0.836） had a significantly better predictive value than MELD （AUC=0.619， Z=3.197， P=0.001）， MELD-Na （AUC=0.651， Z=2.998， P=0.003）， MELD 3.0 （AUC=0.601， Z=3.682， P<0.001）， and COSSH-ACLF Ⅱ （AUC=0.719， Z=2.396， P=0.017） alone. ConclusionDiabetes， SBP， and Cys-C are independent risk factors for 90-day mortality in patients with ACLF. Compared with MELD， MELD-Na， MELD 3.0， and COSSH-ACLF Ⅱ scores， this model has a higher predictive value for 90-day prognosis in patients with ACLF and is suitable for patients with ACLF caused by various etiologies.

Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

Objective Based on the characteristics of common diseases in primary care,it explores the achievabili-ty of internet first diagnosis from the perspective of clinical doctors in large tertiary hospitals,providing a reference for promoting the policy of internet first diagnosis.Methods Stratified sampling was used to select about 10 attending physicians or above from each specialty.A total of 164 doctors were surveyed on the achievability of specific diseases.Chi-square test or Fisher's exact test were conducted to identify the influencing factors of the achievabili-ty of each disease.Results Among the common diseases in primary care,13 diseases(25.49％)had a low degree of achievability for diagnosis,18 diseases(35.29％)had a medium degree,and 20 diseases(39.22％)had a high de-gree.For treatment,19 diseases(37.25％)had a low degree of achievability,22 diseases(43.14％)had a medium degree,and 10 diseases(19.61％)had a high degree.The emergency level,severity,diagnostic complexity,ex-pected treatment outcome,information provided,and diagnostic technology matching degree all had significant impacts on the achievability of Internet first diagnosis(P＜0.05).Conclusion The feasibility of the first diagnosis of common diseases through online medical services varies greatly.It is suggested that a differentiated online first diagnosis ser-vice system for common diseases be established based on the differences in the feasibility of the first diagnosis through the Internet,and the feasibility of the first diagnosis through the Internet be enhanced by developing smart medical technologies.

Objective:To investigate immunological non-responders (INRs) and immunological responders (IRs) during long-term antiretroviral therapy (ART), and study the dynamics of HIV reservoir and α4β7 cells in INRs and IRs and their correlation.Methods:Twenty-six patients with chronic HIV infection who received ART for 5 years were included. They were divided into INRs (CD4 + T cell counts≤350 cells/μl, n=9) and IRs (CD4 + T cell counts≥500 cells/μl, n=17) based on immune reconstitution outcomes. The percentages and numbers of α4β7 cells in both groups at baseline, ART 1, 3, and 5 years were detected by flow cytometry, and the levels of HIV DNA and cell-associated HIV RNA were quantified by real-time fluorescent quantitative PCR during the same periods. HIV viral decay, α4β7 cells dynamics, and their correlations with T cells were compared at baseline, ART 1, 3 and 5 years between the two groups. Results:Over 5 years of ART, INRs exhibited higher HIV reservoir levels compared to IRs, but the decline trend was not slow. The counts of α4β7 cell were lower and the growth trend was slow in INRs ( P<0.05). α4β7 cell counts were strongly positively correlated with CD4 + T cell counts at all timepoints (Year 1: r=0.887; Year 3: r=0.878; Year 5: r=0.887; P all <0.001), while showing significantly negative correlations with activated CD38 + HLA-DR + CD4 + T cells (Year 1: r=-0.619, P=0.001), CD38 + HLA-DR + CD8 + T cells (Year 1: r=-0.517; Year 5: r=-0.532; P all <0.01), and PD-1 + CD4 + T cells (Year 1: r=-0.476, Year 5: r=-0.390, P all <0.05). Conclusions:During long-term ART, INRs maintained higher HIV reservoir and lower α4β7 cell counts compared with IRs, and decreased α4β7 cells may be associated with disease progression.

Objective:To investigate the value of midtreatment 18F-FDG PET/CT metabolic parameters for predicting the pathological response in patients with locally advanced gastric cancer (LAGC) after neoadjuvant immunochemotherapy (NICT). Methods:Twenty-five LAGC patients (19 males, 6 females, age: (64.8±8.6) years) who underwent 18F-FDG PET/CT after NICT in Henan Cancer Hospital from August 2019 to June 2024 were retrospectively analyzed. The lesion′s ROI was delineated, then the SUV max and metabolic tumor volume (MTV) were measured, and the SUV max was divided by SUV mean of the descending aorta to obtain the tumor-to-background ratio (TBR). Patients underwent surgery after PET/CT imaging. Based on the tumor regression grade (TRG) system by the American Joint Committee on Cancer (AJCC) criteria on surgical specimen, patients were divided into responders (TRG0+ 1) and non-responders (TRG2+ 3). Independent-sample t test, Mann-Whitney U test, one-way analysis of variance, and Kruskal-Wallis rank-sum test were used to compare the differences of data. The predictive efficacy of PET/CT metabolic parameters was assessed by the ROC curve analysis. Results:Postsurgical pathology showed that 9 patients were responders and 16 were non-responders. The SUV max (3.10±1.95) and TBR (2.44±1.54) of primary lesions in responders were lower than those in non-responders (7.40±4.68, 5.85±3.74; t values: -2.61, -2.59, both P<0.05), while the MTV of primary tumors and short diameter and metabolic parameters of positive lymph nodes were not significantly different between those 2 groups ( t=-1.50, Z values: -1.09 to -0.75, all P>0.05). No significant relation was found between PET/CT parameters and pathological differentiation or Lauren classification, or other pathological features ( t values: -1.55 to 1.38, Z values: -1.84 to 0, F values: 0.12-2.43, H values: 0.13-0.98, all P>0.05). ROC curve showed that the cut-off value of SUV max for predicting postoperative TRG was 5.40, and the AUC reached 0.77 (95% CI: 0.56-0.91), with the sensitivity and specificity of 9/16, 9/9, respectively. With TBR=3.54 as the cut-off value, its AUC reached 0.77 (95% CI: 0.56-0.91), and the sensitivity and specificity were 11/16, 8/9, respectively. The sensitivity and specificity of PET/CT for predicting lymph node positivity of patients were 8/12 and 13/13, respectively. Conclusion:Interim 18F-FDG PET/CT metabolic parameters can accurately predict the pathological response of LAGC patients after NICT.

Objective:To observe any effect of supplementing treatment according to the Early Start Denver model (ESDM) with repeated transcranial magnetic stimulation (rTMS) in the treatment of children with autism spectrum disorder (ASD).Methods:Sixty-seven children on the autism spectrum aged 2 or 3 years were randomly divided into a control group of 33 and an observation group of 34. Both groups were treated as specified by the ESDM for 24 weeks, but the observation group additionally received rTMS. At 12 and 24 weeks, both groups were evaluated using the Autism Behavior Checklist, the Childhood Autism Rating Scale (CARS), the revised version of the Repetitive Behavior Scale (RBS-R), Gesell Development Schedules, and the Autism Treatment Evaluation Checklist (ATEC).Results:The CARS, Gesell, RBS-R and ATEC results of both groups had improved significantly after 12 weeks, with further improvements observed another 12 weeks later, when the average Autism Behavior Checklist scores had also improved significantly. At that point the results of the observation group were significantly better than those of the control group, on average.Conclusions:Combining ESDM and rTMS can significantly relieve the main symptoms of autism and improve the comprehensive development of children on the autism spectrum 2 or 3 years old. Therefore, such combination is worthy of application in clinical practice.

Objective:To understand the prevalence of chronic kidney disease (CKD) and influencing factors in adults with hypertension in China and provide evidence for the management of CKD in hypertension patients.Methods:The prevalence data of CKD in hypertension patients in China were collected from China Chronic Disease and Risk Factor Surveillance in 2018, the data of 68 829 hypertension patients were analyzed. After complex weighting, the prevalence of CKD in the study population was compared. A multivariate logistic regression model was used to explore the influencing factors of CKD in adults with hypertension.Results:The prevalence of CKD in the hypertension patients was 18.2% (95% CI: 17.4%-19.0%) and increased with age, and the prevalence was 16.4% in men and 20.6% in women ( P<0.001). In different age groups, CKD at stage G1 mainly occurred in those aged 18-44 and 45-59 years, with the prevalence of 10.8% and 7.8%, respectively, while CKD at stages G2 and G3a mainly occurred in those aged >60 years, with the prevalence of 9.4% and 9.7%. Multivariate logistic regression results showed that in the hypertension patients, being aged ≥60 years, being women, smoking (including current and ever smoking), physical inactivity, being underweight or obese, and suffering from diabetes, dyslipidemia and hyperuricemia were the potential risk factors for CKD (all P<0.05). Conclusion:The prevalence of CKD was higher in people with hypertension than in general population in China, and age, gender, smoking status, physical activity level, and suffering from diabetes, dyslipidemia, and hyperuricemia or not were significant influencing factors. It is necessary to strengthen health education and kidney function testing in adults with hypertension and develop comprehensive CKD prevention and control measures targeting high-risk population.

Objective:To investigate the trends in insulin resistance, as represented by the triglyceride-glucose index (TyG index), among Chinese adult residents from 2010 to 2018 and to explore influencing factors.Methods:China Chronic Disease and Risk Factor Surveillance was conducted in 2010, 2013, and 2018, using a multi-stage stratified cluster random sampling method across all 31 provinces (autonomous regions and municipalities) in China. This study sampled 98 712 adults in 2010, 176 534 adults in 2013, and 184 876 adults in 2018, all aged ≥18 years, totaling 406 933 participants. Individuals with a TyG index > P75 were classified as having insulin resistance. The mean TyG index and the prevalence of insulin resistance were calculated for different years, sexes, age groups, provinces (autonomous regions and municipalities), and subgroups for 2018. Linear and logistic regression models were used to test trends in means and rates over time, and multivariate logistic regression models were conducted to analyze potential factors associated with insulin resistance. All analyses were adjusted for complex sampling weights based on the study design. Results:From 2010 to 2018, the mean TyG index among Chinese adults increased from 8.44±0.63 to 8.70±0.64, with significant upward trends observed across different age groups, sexes, and urban-rural residencies (all P<0.001). The mean TyG index was higher among males, urban residents, and those aged 45-59. There were significant differences in the mean TyG indices and prevalence of insulin resistance across provinces (autonomous regions and municipalities) (all P<0.05). Higher insulin resistance prevalence was independently associated with being male, aged ≥45 years, living in urban areas, excessive alcohol consumption, and insufficient physical activity (all P<0.05). Conclusions:From 2010 to 2018, the level of insulin resistance, as indicated by the TyG index, showed an increasing trend among Chinese adults. Males, individuals aged ≥45 years, urban residents, and individuals with unhealthy lifestyles such as excessive alcohol consumption or insufficient physical activity should be the focus of efforts to prevent and control metabolic diseases related to insulin resistance.

This paper introduces the academic characteristics of Professor ZHANG Ren in treatment with acupuncture for refractory eye diseases in modern times, guided by "homotherapy for heteropathy" (same therapy for different diseases sharing the same pathogenesis). The refractory eye diseases in modern times include a variety of conditions such as glaucoma, macular degeneration, diabetic retinopathy, high myopia and its complications, dry eye, cortical visual impairment and genetic eye diseases. The same therapy is used because these diseases share the similar location and pathogenesis. Professor ZHANG optimizes the methods of acupoint selection and provides the comprehensive prescriptions, "basic prescription, prescription based on disease differentiation, and supplementary prescription". A variety of acupuncture manipulation techniques are operated in clinical practice, such as compound needling methods, penetration needling, manipulations for promoting qi movement and conducting qi flow. "Early, regular and persistent" treatment is the common requirement with "the same acupoints, the same prescription and the same acupuncture method" as well as at "the same time". It is also proposed that the treatment should be provided flexibly according to the different symptoms, "identifying the differences within similarities".
Acupuncture Therapy/methods* ; Humans ; Eye Diseases/history* ; Acupuncture Points ; History, 20th Century ; China ; History, 21st Century