Objective To explore the prognostic value of glycolysis-related genes in colorectal cancer (CRC) patients and formulate a novel glycolysis-related prognostic risk model. Methods Single-cell and bulk transcriptomic data of CRC patients, along with clinical information, were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Glycolysis scores for each sample were calculated using single-sample Gene Set Enrichment Analysis (ssGSEA). Kaplan-Meier survival curves were generated to analyze the relationship between glycolysis scores and overall survival. Novel glycolysis-related subgroups were defined among the cell type with the highest glycolysis scores. Gene enrichment analysis, metabolic activity assessment, and univariate Cox regression were performed to explore the biological functions and prognostic impact of these subgroups. A prognostic risk model was built and validated based on genes significantly affecting the prognosis. Gene Set Enrichment Analysis (GSEA) was conducted to explore differences in biological processes between high- and low-risk groups. Differences in immune microenvironment and drug sensitivity between these groups were assessed using R packages. Potential targeted agents for prognostic risk genes were predicted using the Enrichr database. Results Tumor tissues showed significantly higher glycolysis scores than normal tissues, which was associated with a poor prognosis in CRC patients. The highest glycolysis score was observed in epithelial cells, within which we defined eight novel glycolysis-related cell subpopulations. Specifically, the P4HA1⁺ epithelial cell subpopulation was associated with a poor prognosis. Based on signature genes of this subpopulation, a six-gene prognostic risk model was formulated. GSEA revealed significant biological differences between high- and low-risk groups. Immune microenvironment analysis demonstrated that the high-risk group had increased infiltration of macrophages and tumor-associated fibroblasts, along with evident immune exclusion and suppression, while the low-risk group exhibited higher levels of B cell and T cell infiltration. Drug sensitivity analysis indicated that high-risk patients were more sensitive to Abiraterone, while low-risk patients responded to Cisplatin. Additionally, Valproic acid was predicted as a potential targeted agent. Conclusion High glycolytic activity is associated with a poor prognosis in CRC patients. The novel glycolysis-related prognostic risk model formulated in this study offers significant potential for enhancing the diagnosis and treatment of CRC.
Humans ; Colorectal Neoplasms/pathology* ; Glycolysis/genetics* ; Prognosis ; Transcriptome ; Tumor Microenvironment/genetics* ; Gene Expression Profiling ; Single-Cell Analysis ; Gene Expression Regulation, Neoplastic ; Male ; Female ; Kaplan-Meier Estimate

Objective:To understand the usage situation of e-cigarettes among residents aged 18-65 in Beijing, explore the relationship between e-cigarette use and cigarette smoking as well as smoking cessation behaviors, and provide scientific support for the developing and improving policies and measures related to e-cigarettes.Methods:Using 19 684 residents data from the Beijing Non-communication Chronic Disease and Risk Factors Surveillance in 2022, complex sampling weighted methods were used to estimate proportions, and complex sampling logistic regression analysis was applied to explore the relationship between e-cigarette use, cigarette smoking, and smoking cessation.Results:Among all study participants, the proportion of those who had ever used e-cigarettes was 3.36%, with the current e-cigarette use at 1.26%. The proportion of current e-cigarette users (1.87%) and the former e-cigarette users (3.47%) were higher ( χ2=64.70, P<0.001) among males compared to females (0.60% and 0.64% respectively). The top three reasons for using e-cigarettes were wanting to quit smoking, perceiving e-cigarettes as less harmful, and enjoying the flavors of e-cigarettes. 83.54% of e-cigarette users started with cigarettes. The results of the complex sampling multivariable logistic regression analysis showed that current smoking ( OR=61.35, 95% CI: 36.98-101.76) and former smoking ( OR=31.20, 95% CI: 15.52-62.71) were positively associated with e-cigarette, while current e-cigarette use ( OR=0.13, 95% CI: 0.04-0.39) was negatively associated with quitting cigarette smoking. Conclusions:The proportion of e-cigarette use in Beijing was relatively low. E-cigarette use was associated with cigarette use and was not conducive to smoking cessation. Therefore, stronger regulatory measures and health education campaigns regarding the risks of e-cigarettes should be implemented.

Objective:To analyze the prevalence trends and epidemiological characteristics of cardiometabolic multimorbidity(CMM) in Beijing from 2005 to 2022.Methods:A series of representative cross-sectional surveys were conducted in Beijing between 2005 and 2022 using a stratified multistage cluster random sampling method. A total of 110 496 permanent residents aged 18-79 years participated in face-to-face interviews, physical examinations, and laboratory testing. Complex sampling logistic regression models were employed to identify factors associated with CMM, and Joinpoint regression was used to assess temporal trends in prevalence. Results:The prevalence of CMM was 22.3% in 2005 and 24.3% in 2022, with an average annual percent change of 0.1%(95% CI -1.3%-1.3%, P>0.05). In rural areas, the prevalence increased by 1.3% per year(95% CI 0.2%-2.6%, P<0.05), while among obese individuals, it decreased by 1.0% annually( P<0.05). The most common CMM patterns were hypertension combined with dyslipidemia(13.2%), hypertension combined with diabetes(7.0%), and diabetes combined with dyslipidemia(5.8%). The prevalence of hypertension and dyslipidemia comorbidity showed a long-term decline among females, those aged 60-79 and obese individuals( P<0.05). In contrast, the prevalence of hypertension and diabetes comorbidity increased over time in rural residents and individuals with normal body weight( P<0.05). Furthermore, diabetes and dyslipidemia comorbidity rates increased significantly among males, adults aged 18-59 years, those with a college education or above, rural residents and individuals with normal body weight( P<0.05). Multivariable logistic regression indicated that male, older age, overweight, obese, and lower education level were independently associated with a higher risk of CMM( P<0.05). Conclusion:From 2005 to 2022, the prevalence of CMM remained high among adults in Beijing. While prevalence decreased among obese individuals, it increased significantly in rural areas. Hypertension combined with dyslipidemia was the most common multimorbidity pattern throughout the study period.

Objective To evaluate the association between self-reported neighborhood walkability environments and mortality in China.Methods The Prospective Urban Rural Epidemiology study in China(PURE-China)recruited 47 931 participants aged 35-70 from 12 provinces in China between 2005 and 2009.Neighborhood environmental indicators were collected using the Neighborhood Environment Walkability Scale(NEWS)questionnaire,with higher scores indicating better walkable environments.The primary outcomes were all-cause mortality and cardiovascular mortality,using Cox fragile model to evaluate the association between community walkability and outcomes,as well as exploring mediating pathways.Results Of 35 490 participants included in this study,60%were female,with a mean(SD)age of 51.5(9.6)years.The median follow-up was 11.7 years.This study found an association between higher community walkability score and reduced risk of all-cause mortality,with the total score(HR=0.85;95%CI,0.80-0.89),land-use mix(HR=0.84;95%CI,0.79-0.88),and crime safety(HR=0.84;95%CI,0.80-0.89)showing the most significant associations.NEWS can affect long-term adverse outcomes through lifestyle.Conclusions In the Chinese population,favorable community walkability is associated with lower all-cause mortality risk,which may support policymakers to take actions to mitigate the adverse effects of poor community en-vironments on health.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Objective:To explore the impact of the two-way referral model on compliance and prognosis in patients with heart failure.Methods:This bidirectional cohort study enrolled chronic heart failure (CHF) patients treated at Qilu Hospital of Shandong University or designated primary hospitals between March 2018 and March 2022. Patients were categorized into two groups based on referral status: two-way referral group (participating in the referral model with≥1 follow-up visit at primary hospitals) and the core hospital group (receiving treatment and follow-up exclusively at Qilu Hospital). Baseline clinical characteristics were collected and compared between groups. Patients underwent followed-up, with primary endpoints including follow-up rate, drug (β-blockers, angiotension converting enzyme inhibitor (ACEI)/angiotensin Ⅱ receptor blockers (ARB)/angiotensin receptor-neprilysin inhibitor (ARNI), sodium-glucose cotransporter 2 inhibitors and mineralocorticoid receptor antagonists) utilization rate and target dose achievement rate. Secondary endpoints encompassed changes from baseline in left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVEDd), and N-terminal pro-brain natriuretic peptide (NT-proBNP), plus cardiovascular mortality and heart failure rehospitalization. Generalized linear mixed models analyzed longitudinal trends in LVEF, LVEDd, and NT-proBNP levels. Kaplan-Meier curves and Cox regression evaluated LVEF recovery rates, supplemented by subgroup analyses. Multivariate logistic regression was used to identify factors influencing target dose achievement rate for β-blockers and ACEI/ARB/ARNI therapies in CHF patients.Results:A total of 357 patients were enrolled, aged 53 (41, 63) years, including 256 males (71.7%). 157 patients were in the two-way referral group and 200 patients in the core hospital-treated group. Compared with the core hospital-treated group, the two-way referral group had lower baseline LVEF (28 (22, 34)% vs. 31 (23, 36)%, P=0.021) and systolic blood pressure (116 (104, 125) mmHg vs. 121 (109, 134) mmHg (1 mmHg=0.133 kPa), P=0.010). The 12-month follow-up rate of the two-way referral group was higher than the core hospital-treated group (73.8% vs. 56.0%, P=0.004). No significant between-group differences were observed in drug utilization rate of β-blockers, ACEI/ARB/ARNI, or sodium-glucose cotransporter 2 inhibitors during follow-up (all P>0.05), while mineralocorticoid receptor antagonists use showed a declining trend in both groups. Although the core hospital-treated group had higher target dose achievement rates for β-blockers (65.4% vs. 49.3%, P=0.042) and ACEI/ARB/ARNI (79.8% vs. 65.8%, P=0.046) than the two-way referral group, multivariate logistic regression indicated that the two-way referral model was not a negative predictor for these outcomes (all P>0.05). Both groups showed improved NT-proBNP, LVEDd, and LVEF from baseline (all P<0.001) with no significant difference in trends between groups (all P>0.05). There was no significant difference in the composite incidence (7.6% vs. 6.5%, P=0.674) and cumulative incidence (log-rank P=0.684) of cardiovascular death and heart failure rehospitalization at 12 months between two groups. Conclusion:The two-way referral model demonstrates advantages in improving medication adherence, drug utilization rates, and targetdoseachievement rates among CHF patients. This model not only promotes cardiac functional recovery but also reduces risks of cardiovascular mortality and heart failure rehospitalization, achieving comparable therapeutic and management outcomes to those observed in core hospital-treated patients.

Objective:To understand the usage situation of e-cigarettes among residents aged 18-65 in Beijing, explore the relationship between e-cigarette use and cigarette smoking as well as smoking cessation behaviors, and provide scientific support for the developing and improving policies and measures related to e-cigarettes.Methods:Using 19 684 residents data from the Beijing Non-communication Chronic Disease and Risk Factors Surveillance in 2022, complex sampling weighted methods were used to estimate proportions, and complex sampling logistic regression analysis was applied to explore the relationship between e-cigarette use, cigarette smoking, and smoking cessation.Results:Among all study participants, the proportion of those who had ever used e-cigarettes was 3.36%, with the current e-cigarette use at 1.26%. The proportion of current e-cigarette users (1.87%) and the former e-cigarette users (3.47%) were higher ( χ2=64.70, P<0.001) among males compared to females (0.60% and 0.64% respectively). The top three reasons for using e-cigarettes were wanting to quit smoking, perceiving e-cigarettes as less harmful, and enjoying the flavors of e-cigarettes. 83.54% of e-cigarette users started with cigarettes. The results of the complex sampling multivariable logistic regression analysis showed that current smoking ( OR=61.35, 95% CI: 36.98-101.76) and former smoking ( OR=31.20, 95% CI: 15.52-62.71) were positively associated with e-cigarette, while current e-cigarette use ( OR=0.13, 95% CI: 0.04-0.39) was negatively associated with quitting cigarette smoking. Conclusions:The proportion of e-cigarette use in Beijing was relatively low. E-cigarette use was associated with cigarette use and was not conducive to smoking cessation. Therefore, stronger regulatory measures and health education campaigns regarding the risks of e-cigarettes should be implemented.

Objective:To analyze the prevalence trends and epidemiological characteristics of cardiometabolic multimorbidity(CMM) in Beijing from 2005 to 2022.Methods:A series of representative cross-sectional surveys were conducted in Beijing between 2005 and 2022 using a stratified multistage cluster random sampling method. A total of 110 496 permanent residents aged 18-79 years participated in face-to-face interviews, physical examinations, and laboratory testing. Complex sampling logistic regression models were employed to identify factors associated with CMM, and Joinpoint regression was used to assess temporal trends in prevalence. Results:The prevalence of CMM was 22.3% in 2005 and 24.3% in 2022, with an average annual percent change of 0.1%(95% CI -1.3%-1.3%, P>0.05). In rural areas, the prevalence increased by 1.3% per year(95% CI 0.2%-2.6%, P<0.05), while among obese individuals, it decreased by 1.0% annually( P<0.05). The most common CMM patterns were hypertension combined with dyslipidemia(13.2%), hypertension combined with diabetes(7.0%), and diabetes combined with dyslipidemia(5.8%). The prevalence of hypertension and dyslipidemia comorbidity showed a long-term decline among females, those aged 60-79 and obese individuals( P<0.05). In contrast, the prevalence of hypertension and diabetes comorbidity increased over time in rural residents and individuals with normal body weight( P<0.05). Furthermore, diabetes and dyslipidemia comorbidity rates increased significantly among males, adults aged 18-59 years, those with a college education or above, rural residents and individuals with normal body weight( P<0.05). Multivariable logistic regression indicated that male, older age, overweight, obese, and lower education level were independently associated with a higher risk of CMM( P<0.05). Conclusion:From 2005 to 2022, the prevalence of CMM remained high among adults in Beijing. While prevalence decreased among obese individuals, it increased significantly in rural areas. Hypertension combined with dyslipidemia was the most common multimorbidity pattern throughout the study period.

Objective:To explore the impact of the two-way referral model on compliance and prognosis in patients with heart failure.Methods:This bidirectional cohort study enrolled chronic heart failure (CHF) patients treated at Qilu Hospital of Shandong University or designated primary hospitals between March 2018 and March 2022. Patients were categorized into two groups based on referral status: two-way referral group (participating in the referral model with≥1 follow-up visit at primary hospitals) and the core hospital group (receiving treatment and follow-up exclusively at Qilu Hospital). Baseline clinical characteristics were collected and compared between groups. Patients underwent followed-up, with primary endpoints including follow-up rate, drug (β-blockers, angiotension converting enzyme inhibitor (ACEI)/angiotensin Ⅱ receptor blockers (ARB)/angiotensin receptor-neprilysin inhibitor (ARNI), sodium-glucose cotransporter 2 inhibitors and mineralocorticoid receptor antagonists) utilization rate and target dose achievement rate. Secondary endpoints encompassed changes from baseline in left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVEDd), and N-terminal pro-brain natriuretic peptide (NT-proBNP), plus cardiovascular mortality and heart failure rehospitalization. Generalized linear mixed models analyzed longitudinal trends in LVEF, LVEDd, and NT-proBNP levels. Kaplan-Meier curves and Cox regression evaluated LVEF recovery rates, supplemented by subgroup analyses. Multivariate logistic regression was used to identify factors influencing target dose achievement rate for β-blockers and ACEI/ARB/ARNI therapies in CHF patients.Results:A total of 357 patients were enrolled, aged 53 (41, 63) years, including 256 males (71.7%). 157 patients were in the two-way referral group and 200 patients in the core hospital-treated group. Compared with the core hospital-treated group, the two-way referral group had lower baseline LVEF (28 (22, 34)% vs. 31 (23, 36)%, P=0.021) and systolic blood pressure (116 (104, 125) mmHg vs. 121 (109, 134) mmHg (1 mmHg=0.133 kPa), P=0.010). The 12-month follow-up rate of the two-way referral group was higher than the core hospital-treated group (73.8% vs. 56.0%, P=0.004). No significant between-group differences were observed in drug utilization rate of β-blockers, ACEI/ARB/ARNI, or sodium-glucose cotransporter 2 inhibitors during follow-up (all P>0.05), while mineralocorticoid receptor antagonists use showed a declining trend in both groups. Although the core hospital-treated group had higher target dose achievement rates for β-blockers (65.4% vs. 49.3%, P=0.042) and ACEI/ARB/ARNI (79.8% vs. 65.8%, P=0.046) than the two-way referral group, multivariate logistic regression indicated that the two-way referral model was not a negative predictor for these outcomes (all P>0.05). Both groups showed improved NT-proBNP, LVEDd, and LVEF from baseline (all P<0.001) with no significant difference in trends between groups (all P>0.05). There was no significant difference in the composite incidence (7.6% vs. 6.5%, P=0.674) and cumulative incidence (log-rank P=0.684) of cardiovascular death and heart failure rehospitalization at 12 months between two groups. Conclusion:The two-way referral model demonstrates advantages in improving medication adherence, drug utilization rates, and targetdoseachievement rates among CHF patients. This model not only promotes cardiac functional recovery but also reduces risks of cardiovascular mortality and heart failure rehospitalization, achieving comparable therapeutic and management outcomes to those observed in core hospital-treated patients.

Objective:To evaluate the risk factors for the formation of parastomal Hernias(PSH)using meta-analysis,and to provide a theoretical basis for the prevention and treatment of PSH.Methods:Case control or Cohort study of PSH risk factors were collected by searching PubMed,CNKI,Wanfang data and other databases.Extract relevant data and perform meta-analysis using RevMan 5.3.Results:The results included a total of 16 studies,with a total sample size of 2411 cases,including 670 in the PSH group and 1741 in the non PSH group.The results showed that advanced age,female gender,BMI≥25,hypertension,COPD/chronic cough,diabetes,and postoperative Hypoproteinemia could increase the risk of PSH(P＜0.05);Smoking,previous ab-dominal surgery history,preoperative radiotherapy/chemotherapy etc.,were not significantly asso-ciated with the occurrence of PSH(P＞0.05).Conclusion:The current evidence shows that ad-vanced age,female gender,BMI≥25,hypertension,COPD/chronic cough,diabetes,postoperative Hypoproteinemia are risk factors for PSH,and extraperitoneal stoma can reduce the occurrence of PSH.