Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

Sarin(GB)is a typical representative of nerve agents with high toxicity,and very low amount can cause death.GB can cause water and atmospheric environment poisoning,so the detection of GB in water and air is of great significance.In this work,a colorimetric sensor array(CSA)based on GB inhibition of cholinesterase activity was constructed to detect GB with high selectivity.A 4×4 colorimetric array was constructed using acetylcholinesterase(AChE),butyryl cholinesterase(BuChE)and the corresponding substrate acetylthiocholine iodide(S-ACh),butyryl thiocholine iodide(S-BCh),acetylcholine chloride(ACh),butyryl choline chloride(BCh)and 2,6-dichloroindophenol ethyl ester(DCIE).The linear curve of the sensor was Y=131.3×lgC+271.6(R2=0.997),where Y was the array response Euclidean distance,C was the concentration of GB(mg/L),the linear range was 0.03?0.32 mg/L,and the detection limit was 27.6 μg/L.The method could effectively distinguish chemical warfare agents(CWA)such as VX,Soman(GD),mustard gas(HD),Louie reagent(L),and had high anti-interference ability,sensitivity and good repeatability.It was successfully applied to the detection of GB in simulated water and simulated air samples,and the sample recovery rate was 97.2% ?100.9%.This method would be potentially applied to the field rapid detection of nerve agents.

Objective:To evaluate the efficacy and safety of endoscopic submucosal dissection (ESD) for the treatment of ileocecal valve lipoma.Methods:A retrospective cohort study was performed on data of ileocecal lipoma patients who underwent ESD at the Endoscopy Center of Zhongshan Hospital, Fudan University from December 2013 to June 2023. According to the lesion location, the patients were divided into ileocecal valve group and cecum group. The operation time, operation speed, en bloc resection rate, complications, and follow-up outcomes between the two groups were compared.Results:A total of 59 patients with ileocecal lipoma were enrolled, including 31 patients in the ileocecal valve group and 28 patients in the cecum group.There were no significant differences in gender, age, specimen size, or lesion size between the two groups ( P>0.05). Lipomas in both the ileocecal valve group and the cecum group were successfully resected by ESD. The en bloc resection rates were 100.0% (31/31) and 92.9% (26/28) respectively, and the difference was not statistically significant ( χ2=0.033, P=0.133). Median operative duration significantly differed between the two groups ( ileocecal valve group 26 min VS cecum group 20 min, Z=-0.136, P=0.027), as did resection speed (ileocecal valve group 0.14 cm2/min VS cecum group 0.24 cm2/min, Z=-0.223, P=0.022). Adverse events included one postoperative fever in the ileocecal valve group and one delayed bleeding in the cecum group. During the median follow-up of 38 months (7-106 months), there was no case of residual tumor or recurrence. Conclusion:Despite technical challenges in ESD of ileocecal valve lipoma, it is still a safe, feasible and effective treatment method.

Objective:To investigate the status of post-traumatic stress disorder (PTSD) and its influencing factors in postoperative breast cancer patients.Methods:A convenience sampling method was used to select 410 postoperative breast cancer patients from the Provincial Hospital of the First Medical University of Shandong between January 2023 and December 2024. The PTSD Checklist-Civilian Version (PCL-C), the Connor-Davidson Resilience Scale (CD-RISC), and the Simple Coping Style Questionnaire (SCSQ) were used for assessment. Binary Logistic regression analysis was performed to analyze influencing factors.Results:A total of 410 questionnaires were distributed, and 405 valid questionnaires were returned, with an effective recovery rate of 98.78% (405/410). Among them, 150 patients were PTSD-positive. Binary Logistic regression analysis showed that educational level, monthly family income, psychological resilience, and coping style were influencing factors for PTSD in postoperative breast cancer patients ( P<0.05) . Conclusions:Low education level, low income, and negative coping style are risk factors for PTSD in postoperative breast cancer patients; positive coping style and high psychological resilience are protective factors. Clinical practitioners should develop preventive or intervention measures based on these influencing factors to reduce the occurrence of PTSD in postoperative breast cancer patients.

Objective:To investigate the status of post-traumatic stress disorder (PTSD) and its influencing factors in postoperative breast cancer patients.Methods:A convenience sampling method was used to select 410 postoperative breast cancer patients from the Provincial Hospital of the First Medical University of Shandong between January 2023 and December 2024. The PTSD Checklist-Civilian Version (PCL-C), the Connor-Davidson Resilience Scale (CD-RISC), and the Simple Coping Style Questionnaire (SCSQ) were used for assessment. Binary Logistic regression analysis was performed to analyze influencing factors.Results:A total of 410 questionnaires were distributed, and 405 valid questionnaires were returned, with an effective recovery rate of 98.78% (405/410). Among them, 150 patients were PTSD-positive. Binary Logistic regression analysis showed that educational level, monthly family income, psychological resilience, and coping style were influencing factors for PTSD in postoperative breast cancer patients ( P<0.05) . Conclusions:Low education level, low income, and negative coping style are risk factors for PTSD in postoperative breast cancer patients; positive coping style and high psychological resilience are protective factors. Clinical practitioners should develop preventive or intervention measures based on these influencing factors to reduce the occurrence of PTSD in postoperative breast cancer patients.

Objective:To investigate the predictive value of tumor morphology in hepatoce-llular carcinoma (HCC) immunotherapy.Methods:The propensity score matching and retrospective cohort study was conducted. The clinical data of 227 HCC patients who underwent immunotherapy in The First Affiliated Hospital of University of Science and Technology of China from January 2021 to December 2023 were collected. There were 203 males and 24 females, aged (57±11)years. Of the 227 patients, 93 patients with regular tumor morphology of HCC evaluated by computed tomography (CT) or magnetic resonance imaging (MRI) were divided into the regular morphology group, and 134 patients with irregular tumor morphology of HCC evaluated by CT or MRI were divided into the irregular morphology group. Observation indicators: (1) propensity score matching and comparison of general data of patients between the two groups after matching; (2) analysis of factors affecting prognosis of patients; (3) prognosis of patients after propensity score matching. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data was conducted using the Mann-Whitney U test. The Kaplan-Meier method was used to calculate survival rate and draw survival curve. The Log-rank test was used for survival analysis. The Cox proportional hazards regression model was used for univariate and multivariate analyses. Propensity score matching was done by the 1∶1 nearest neighbor matching method, with a caliper value of 0.02. Results:(1) Propensity score matching and comparison of general data of patients between the two groups after matching. Of 227 HCC patients undergoing immunotherapy, 164 cases were successfully matched, including 82 cases in the regular morphology group and 82 cases in the irregular morphology group. After propensity score matching, the elimination of patients who underwent radical surgical resection in the past, tumor number and alpha fetoprotein confounding bias ensured comparability between the two groups. (2) Analysis of factors affecting prognosis of patients. Results of multivariate analysis showed that body mass index ≥25 kg/m 2 and irregular tumor morphology were independent risk factors affecting overall survival time of patients ( hazard ratio=0.891, 1.870, 95% confidence interval as 0.825-0.963, 1.151-3.038, P<0.05). (3) Prognosis of patients after propensity score matching. After propensity score matching, the median progression-free survival time was 11.9(95% confidence interval as 9.2-16.1)months for patients in the regular tumor morphology group and 6.4(95% confidence interval as 4.4-8.1)months for patients in the irregular tumor morphology group, the 1-year progress-free survival rate was 48.48% for patients in the regular tumor morphology group and 22.25% for patients in the irregular tumor morphology group. There was a significant difference in progress-free survival between patients in the regular tumor morphology group and the irregular tumor morphology group ( χ2=16.000, P<0.05). The median overall survival time was 27.2(95% confidence interval as 23.7-not reached)months for patients in the regular tumor morphology group and 18.1 (95% confidence interval as 15.8-20.8)months for patients in the regular tumor morphology group, the 1-year overall survival rate was 83.27% for patients in the regular tumor morphology group and 66.98% for patients in the irregular tumor morphology group. There was a significant difference in overall survival between patients in the regular tumor morphology group and the irregular tumor morphology group ( χ2=13.400, P<0.05). Conclusions:Tumor morphology has a predictive value for the efficacy of immunotherapy for HCC. Compared with HCC patients of regular tumor morphology, immunotherapy is less effective in patients with irregular tumor morphology.

Objective:To present an evaluation indicator system for access to cancer screening services.Methods:The evaluation indicator pool was constructed through a scoping review. The theoretical framework was constructed based on the multi-source indicators, and the qualitative expert consultation method was employed to form the initial version of the three-level evaluation indicator system. Delphi expert consultation method was conducted in two rounds to evaluate the relevance, importance, and availability of the proposed evaluation indicator system. The expert positive coefficient, authority coefficient, coordination degree of expert opinions, and concentration of expert opinions were subjected to analysis. Subsequently, the three-level evaluation indicator system for access to cancer screening services was adjusted and determined based on the boundary value method and the open opinions of experts. Finally, the combination weight method was employed to determine the weight.Results:The initial version of the indicator system comprised 3 primary (first-level) indicators, 11 secondary (second-level) indicators, and 46 tertiary (third-level) indicators. Delphi expert consultation was conducted for the initial version, and 17 experts ultimately completed it, exhibiting a positive coefficient of 100% and an authority coefficient of 0.87. In comparison to the initial round of consultation, Kendall's W coefficient ranges (0.15-0.43, all P<0.05) of relevance, importance, and availability scores for each tertiary indicator in the second round exhibited an improvement. The analysis of the importance dimension indicates that expert opinions are also more concentrated, as evidenced by an increase of 8.5% and 7.0% in the proportion of the tertiary indicators with an arithmetic mean above 8 and a full mark ratio above 0.5, respectively. The final evaluation indicator system comprises three primary indicators, with the weights of structure evaluation, process evaluation, and outcome evaluation being 0.338, 0.378, and 0.285, respectively. It also comprises 11 secondary indicators and 45 tertiary indicators. Conclusions:The evaluation indicator system developed in this article can be an effective evaluation tool for quantitative comparison of access to cancer screening services across different populations, cancer types, and before and after intervention. Furthermore, it is recommended that the system undergo continuous optimization concerning its application.

Objective To screen the predictors of early initiation of continuous renal replacement therapy(CRRT)in children with sepsis and construct a linear model,based on LASSO regression analysis.Methods A total of 55 children diagnosed with sepsis at Jiangmen Maternity and Child Health Care Hospital from April 2023 to February 2025.They were divided into CRRT group(n=17)and non-CRRT group(n=38)based on CRRT treatment usage.Using LASSO regression screening,predictive factors were identified and a Logistic regression model was established.The model's performance was evaluated using receiver operating characteristic(ROC)curve and calibration curve.Results There were significant differences in age,respiratory rate,body temperature,and mechanical ventilation between two groups(P＜0.05).Through LASSO regression analysis,four independent predictors of respiratory rate,body temperature,blood glucose,and C-reactive protein were identified.The constructed model demonstrated an area under the ROC curve of 0.94(95％CI:0.87-1.00),indicating good calibration accuracy.Conclusion The column line model based on body temperature,respiratory rate,blood glucose and C-reactive protein can effectively predict the need for early initiation of CRRT in sepsis children.

Objective:To present an evaluation indicator system for access to cancer screening services.Methods:The evaluation indicator pool was constructed through a scoping review. The theoretical framework was constructed based on the multi-source indicators, and the qualitative expert consultation method was employed to form the initial version of the three-level evaluation indicator system. Delphi expert consultation method was conducted in two rounds to evaluate the relevance, importance, and availability of the proposed evaluation indicator system. The expert positive coefficient, authority coefficient, coordination degree of expert opinions, and concentration of expert opinions were subjected to analysis. Subsequently, the three-level evaluation indicator system for access to cancer screening services was adjusted and determined based on the boundary value method and the open opinions of experts. Finally, the combination weight method was employed to determine the weight.Results:The initial version of the indicator system comprised 3 primary (first-level) indicators, 11 secondary (second-level) indicators, and 46 tertiary (third-level) indicators. Delphi expert consultation was conducted for the initial version, and 17 experts ultimately completed it, exhibiting a positive coefficient of 100% and an authority coefficient of 0.87. In comparison to the initial round of consultation, Kendall's W coefficient ranges (0.15-0.43, all P<0.05) of relevance, importance, and availability scores for each tertiary indicator in the second round exhibited an improvement. The analysis of the importance dimension indicates that expert opinions are also more concentrated, as evidenced by an increase of 8.5% and 7.0% in the proportion of the tertiary indicators with an arithmetic mean above 8 and a full mark ratio above 0.5, respectively. The final evaluation indicator system comprises three primary indicators, with the weights of structure evaluation, process evaluation, and outcome evaluation being 0.338, 0.378, and 0.285, respectively. It also comprises 11 secondary indicators and 45 tertiary indicators. Conclusions:The evaluation indicator system developed in this article can be an effective evaluation tool for quantitative comparison of access to cancer screening services across different populations, cancer types, and before and after intervention. Furthermore, it is recommended that the system undergo continuous optimization concerning its application.