ObjectiveTo investigate the ameliorative effect of Wendantang combined with Danshenyin and Dushentang （WDD） on mice with ischemic heart disease （IHD） presenting phlegm-stasis syndrome based on the inflammatory phenotype and differentiation of circulating monocytes. MethodsA model of IHD with phlegm-stasis syndrome was established using left anterior descending coronary artery ligation supplemented with a high-fat diet. Eighty model mice were randomly assigned to the model group， WDD low-dose group （WDD-L）， WDD medium-dose group （WDD-M）， WDD high-dose group （WDD-H）， and atorvastatin calcium tablet group， with 16 mice in each group. An additional 16 C57BL/6J mice were designated as the sham-operation group. The WDD groups received intragastric administration at doses of 8.91， 17.81， 35.62 g·kg^-1， and the atorvastatin calcium tablet group received the corresponding drug at 1.3 mg·kg^-1， twice daily. The sham-operation and model groups were given the same volume of pure water by gavage each day. After 5 consecutive weeks of administration， the cardiac index was calculated. Cardiac function was assessed by echocardiography. Myocardial histopathology was examined by hematoxylin-eosin （HE） staining. Serum N-terminal pro-B-type natriuretic peptide （pro-BNP） content was measured by enzyme-linked immunosorbent assay （ELISA）. Hemorheological parameters were analyzed using an automated hemorheology analyzer. Serum levels of total cholesterol （TC）， triglycerides （TG）， low-density lipoprotein （LDL）， and high-density lipoprotein （HDL） were determined using an automated biochemical analyzer. Changes in circulating monocytes were detected by flow cytometry. Mouse bone marrow mononuclear cells were isolated in vitro and divided into blank group， model serum group， WDD-L drug-containing serum group， WDD-M drug-containing serum group， and WDD-H drug-containing serum group. CD36 expression and macrophage differentiation in each group were assessed by flow cytometry. The mechanism by which WDD mediates circulating monocyte differentiation was further explored using CD36 knockdown/overexpression RAW264.7 cell lines. ResultsCompared with the sham-operation group， the model group showed a significantly increased cardiac index （P0.01）， significantly decreased fractional shortening （FS） （P0.01）， and significantly increased left ventricular end-diastolic internal diameter （LVDD） and left ventricular end-systolic internal diameter （LVDS） （P0.01）. Cardiomyocytes exhibited marked deformation and necrosis with inflammatory cell infiltration. Serum pro-BNP levels were significantly elevated （P0.01）， and whole-blood viscosity （BV） at high， medium， and low shear rates was significantly increased （P0.01）. Compared with the model group， the WDD groups showed significantly reduced cardiac index （P0.05， P0.01）， significantly increased FS （P0.05， P0.01）， significantly decreased LVDD and LVDS （P0.01）， markedly improved cardiomyocyte morphology， significantly reduced inflammatory infiltration， significantly decreased serum pro-BNP levels （P0.01）， and significantly decreased BV at high， medium， and low shear rates （P0.01）， with the most pronounced improvement observed in the WDD-M group. Compared with the sham-operation group， TC， TG， and LDL levels were significantly increased in the model group （P0.05， P0.01）， while HDL levels were significantly decreased （P0.05）. After WDD-H treatment， TC， TG， and LDL levels were significantly reduced and HDL levels were significantly increased in mice （P0.05， P0.01）. Compared with the sham-operation group， classical monocytes in blood and bone marrow and intermediate monocytes in blood were significantly increased in the model group （P0.01）， whereas intermediate monocytes in bone marrow and non-classical monocytes in blood were significantly decreased （P0.01）. After WDD administration， all circulating monocyte subsets in blood and bone marrow were significantly alleviated （P0.05， P0.01）， with the WDD-M group showing the optimal effect. In vitro， compared with the blank group， CD36 expression on bone marrow monocytes and the proportion of differentiated macrophages were significantly increased in the model serum group （P0.01）， and CD36 expression was significantly upregulated on RAW264.7 cells （P0.01）. Compared with the model serum group， all drug-containing serum groups exhibited significantly reduced CD36 expression on bone marrow monocytes and significantly reduced macrophage differentiation （P0.01）. WDD downregulated CD36 expression in both CD36 knockdown and overexpression RAW264.7 cell lines （P0.05， P0.01）， with the strongest regulatory effect observed in the WDD-M drug-containing serum group. ConclusionWDD can significantly improve the manifestations of phlegm-stasis syndrome in IHD mice and reduce the proportion of classical circulating monocytes. Its mechanism may be related to the inhibition of CD36 expression on classical circulating monocytes.

ObjectiveTo investigate the ameliorative effect of Wendantang combined with Danshenyin and Dushentang （WDD） on mice with ischemic heart disease （IHD） presenting phlegm-stasis syndrome based on the inflammatory phenotype and differentiation of circulating monocytes. MethodsA model of IHD with phlegm-stasis syndrome was established using left anterior descending coronary artery ligation supplemented with a high-fat diet. Eighty model mice were randomly assigned to the model group， WDD low-dose group （WDD-L）， WDD medium-dose group （WDD-M）， WDD high-dose group （WDD-H）， and atorvastatin calcium tablet group， with 16 mice in each group. An additional 16 C57BL/6J mice were designated as the sham-operation group. The WDD groups received intragastric administration at doses of 8.91， 17.81， 35.62 g·kg^-1， and the atorvastatin calcium tablet group received the corresponding drug at 1.3 mg·kg^-1， twice daily. The sham-operation and model groups were given the same volume of pure water by gavage each day. After 5 consecutive weeks of administration， the cardiac index was calculated. Cardiac function was assessed by echocardiography. Myocardial histopathology was examined by hematoxylin-eosin （HE） staining. Serum N-terminal pro-B-type natriuretic peptide （pro-BNP） content was measured by enzyme-linked immunosorbent assay （ELISA）. Hemorheological parameters were analyzed using an automated hemorheology analyzer. Serum levels of total cholesterol （TC）， triglycerides （TG）， low-density lipoprotein （LDL）， and high-density lipoprotein （HDL） were determined using an automated biochemical analyzer. Changes in circulating monocytes were detected by flow cytometry. Mouse bone marrow mononuclear cells were isolated in vitro and divided into blank group， model serum group， WDD-L drug-containing serum group， WDD-M drug-containing serum group， and WDD-H drug-containing serum group. CD36 expression and macrophage differentiation in each group were assessed by flow cytometry. The mechanism by which WDD mediates circulating monocyte differentiation was further explored using CD36 knockdown/overexpression RAW264.7 cell lines. ResultsCompared with the sham-operation group， the model group showed a significantly increased cardiac index （P<0.01）， significantly decreased fractional shortening （FS） （P<0.01）， and significantly increased left ventricular end-diastolic internal diameter （LVDD） and left ventricular end-systolic internal diameter （LVDS） （P<0.01）. Cardiomyocytes exhibited marked deformation and necrosis with inflammatory cell infiltration. Serum pro-BNP levels were significantly elevated （P<0.01）， and whole-blood viscosity （BV） at high， medium， and low shear rates was significantly increased （P<0.01）. Compared with the model group， the WDD groups showed significantly reduced cardiac index （P<0.05， P<0.01）， significantly increased FS （P<0.05， P<0.01）， significantly decreased LVDD and LVDS （P<0.01）， markedly improved cardiomyocyte morphology， significantly reduced inflammatory infiltration， significantly decreased serum pro-BNP levels （P<0.01）， and significantly decreased BV at high， medium， and low shear rates （P<0.01）， with the most pronounced improvement observed in the WDD-M group. Compared with the sham-operation group， TC， TG， and LDL levels were significantly increased in the model group （P<0.05， P<0.01）， while HDL levels were significantly decreased （P<0.05）. After WDD-H treatment， TC， TG， and LDL levels were significantly reduced and HDL levels were significantly increased in mice （P<0.05， P<0.01）. Compared with the sham-operation group， classical monocytes in blood and bone marrow and intermediate monocytes in blood were significantly increased in the model group （P<0.01）， whereas intermediate monocytes in bone marrow and non-classical monocytes in blood were significantly decreased （P<0.01）. After WDD administration， all circulating monocyte subsets in blood and bone marrow were significantly alleviated （P<0.05， P<0.01）， with the WDD-M group showing the optimal effect. In vitro， compared with the blank group， CD36 expression on bone marrow monocytes and the proportion of differentiated macrophages were significantly increased in the model serum group （P<0.01）， and CD36 expression was significantly upregulated on RAW264.7 cells （P<0.01）. Compared with the model serum group， all drug-containing serum groups exhibited significantly reduced CD36 expression on bone marrow monocytes and significantly reduced macrophage differentiation （P<0.01）. WDD downregulated CD36 expression in both CD36 knockdown and overexpression RAW264.7 cell lines （P<0.05， P<0.01）， with the strongest regulatory effect observed in the WDD-M drug-containing serum group. ConclusionWDD can significantly improve the manifestations of phlegm-stasis syndrome in IHD mice and reduce the proportion of classical circulating monocytes. Its mechanism may be related to the inhibition of CD36 expression on classical circulating monocytes.

Adverse drug reactions （ADRs） refer to harmful or unintended reactions unrelated to the intended purpose of medication administration， which can lead to various issues such as accelerated disease progression and prolonged hospitalization. Traditional ADRs monitoring systems （such as spontaneous reporting systems） suffer from limitations such as low reporting rates and inconsistent data quality， which hinder the early prevention and control of ADRs. With the rapid development of information technology， machine learning has emerged as a powerful tool for management and decision-making of ADRs by leveraging its strengths in feature extraction and dynamic temporal pattern analysis. By reviewing relevant literature at home and abroad in recent years， this paper summarizes the progress in the application of machine learning for ADRs prediction. It is found that machine learning has gradually been applied to the early warning and risk prediction of ADRs in target organs such as the kidneys， liver， heart and bone marrow （such as acute kidney injury， drug-induced liver injury， and so on）. Although machine learning demonstrates significant application potential in the field of ADRs prediction， it still faces limitations such as inadequate quality control of clinical data， lack of standardized criteria for model performance evaluation， insufficient model interpretability and difficulties in clinical translation. In the future， the development trend of machine learning in the field of ADRs prediction should follow a “technology-validation-integration” pathway to systematically promote the practical implementation of models.

Objective To understand the current status of low-density lipoprotein cholesterol (LDL-C) control in patients after coronary artery bypass grafting (CABG). Methods Clinical data of patients who underwent isolated CABG in Beijing Anzhen Hospital in 2023 were collected. All patients returned to our hospital approximately one year after surgery (10-13 months) for a lipid level recheck. We analyzed their LDL-C attainment status and influencing factors. Patients were categorized into two groups based on whether their LDL-C met the target: a LDL-C attainment group and a LDL-C non-attainment group. Results This study included 1456 patients who underwent CABG, including 320 females and 1136 males, with an average age of (61.41±9.12) years. One year post-surgery, 234 patients achieved the LDL-C target, with an attainment rate of 16.07%. The proportion of patients in the LDL-C attainment group who were ultra-high risk (77.35% vs. 92.06%, P＜0.001), female (16.24% vs. 23.08%, P=0.021), and those with comorbid hypertension (55.98% vs. 63.18%, P=0.038) was significantly lower than those in the LDL-C non-attainment group. Additionally, the baseline body mass index (BMI) [(25.37±3.24) kg/m2 vs. (26.03±3.56) kg/m2, P=0.017], total cholesterol levels [(3.30±0.84) mmol/L vs. (4.01±1.03) mmol/L, P＜0.001], LDL-C [(1.62±0.63) mmol/L vs. (2.25±0.85) mmol/L, P＜0.001], and high-density lipoprotein cholesterol [(0.98±0.26) mmol/L vs. (1.02±0.24) mmol/L, P=0.049] upon admission in the attainment group were all lower than those in the non-attainment group. Moreover, the lipid-lowering drug usage rate in the attainment group (100.00% vs. 96.24%, P=0.003) and the proportion using two types of drugs together (25.21% vs. 10.72%, P＜0.001) were both higher than those in the non-attainment group, while the statin monotherapy rate was lower than that in the non-attainment group (74.79% vs. 85.19%, P＜0.001). Logistic regression analysis showed that baseline BMI (OR=0.928, P=0.012) and baseline LDL-C levels (OR=0.207, P<0.001), patient cardiovascular risk stratification (OR=0.155, P<0.001) and lipid-lowering drug treatment regimen (OR=3.758, P<0.001) are significant factors affecting the LDL-C control status. Conclusion The LDL-C compliance rate of patients undergoing CABG is at a relatively low level 1 year after surgery. Patients with very high risk of atherosclerotic cardiovascular disease, high baseline LDL-C levels, and overweight or obesity should be strengthened lipid management. For these patients, the intensity of lipid-lowering drug use or combination medication should be increased upon discharge.

Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

OBJECTIVE: To investigate the risk factors, clinical characteristics, and bacterial resistance of bloodstream infections caused by Streptococcus mitis in children with hematological disease, so as to provide a reference for infection control. METHODS: The clinical information and laboratory findings of pediatric patients complicated with blood cultures positive for Streptococcus mitis from January 2018 to December 2020 in the Institute of Hematology & Blood Diseases Hospital were searched and collected. The clinical characteristics, susceptibility factors, and antibiotic resistance of the children were retrospectively analyzed. RESULTS: Data analysis from 2018 to 2020 showed that the proportion of Streptococcus mitis isolated from bloodstream infections in children (≤14 years old) with hematological diseases was the highest (19.91%) and significantly higher than other bacteria, accounting for 38.64% of Gram-positive cocci, and presented as an increasing trend year by year. A total of 427 children tested positive blood cultures, including 85 children with bloodstream infections caused by Streptococcus mitis who tested after fever. Most children experienced a recurrent high fever in the early and middle stages (≤6 d) of neutropenia and persistent fever for more than 3 days. After adjusting the antibiotics according to the preliminary drug susceptibility results, the body temperature of most children (63.5%) returned to normal within 4 days. The 85 children were mainly diagnosed with acute myeloid leukemia (AML), accounting for 84.7%. The proportion of children in the neutropenia stage was 97.7%. The incidence of oral mucosal damage, lung infection, and gastrointestinal injury symptoms was 40%, 31.8%, and 27.1%, respectively. The ratio of elevated C-reactive protein (CRP) and procalcitonin was 65.9% and 9.4%, respectively. All isolated strains of Streptococcus mitis were not resistant to vancomycin and linezolid, and the resistance rate to penicillin, cefotaxime, levofloxacin, and quinupristin-dalfopristin was 10.6%, 8.2%, 9.4%, and 14.1%, respectively. None of children died due to bloodstream infection caused by Streptococcus mitis. CONCLUSION The infection rate of Streptococcus mitis is increasing year by year in children with hematological diseases, especially in children with AML. Among them, neutropenia and oral mucosal damage after chemotherapy are high-risk infection factors. The common clinical symptoms include persistent high fever, oral mucosal damage, and elevated CRP. Penicillin and cephalosporins have good sensitivity. Linezolid, as a highly sensitive antibiotic, can effectively control infection and shorten the course of disease.
Humans ; Child ; Streptococcal Infections/microbiology* ; Retrospective Studies ; Hematologic Diseases/complications* ; Streptococcus mitis ; Drug Resistance, Bacterial ; Risk Factors ; Microbial Sensitivity Tests ; Anti-Bacterial Agents ; Female ; Male ; Bacteremia/microbiology* ; Child, Preschool ; Adolescent

BACKGROUND: Lung cancer is one of the most common malignant tumors worldwide and a major cause of cancer-related deaths. Early-stage lung cancer is often manifested as pulmonary nodules, and accurate assessment of the malignancy risk is crucial for prolonging survival and avoiding overtreatment. This study aims to construct a model based on image feature parameters automatically extracted by artificial intelligence (AI) to evaluate its effectiveness in predicting the malignancy of part-solid nodule (PSN). METHODS: This retrospective study analyzed 229 PSN from 222 patients who underwent pulmonary nodule resection at Lanzhou University Second Hospital between October 2020 and February 2025. According to pathological results, 45 cases of benign lesions and precursor glandular lesion were categorized into the non-malignant group, and 184 cases of pulmonary malignancies were categorized into the malignant group. All patients underwent preoperative chest computed tomography (CT), and AI software was used to extract imaging feature parameters. Univariate analysis was used to screen significant variables; variance inflation factor (VIF) was calculated to exclude highly collinear variables, and LASSO regression was further applied to identify key features. Multivariate Logistic regression was used to determine independent risk factors. Based on the selected variables, five models were constructed: Logistic regression, random forest, XGBoost, LightGBM, and support vector machine (SVM). Receiver operating characteristic (ROC) curves were used to assess the performance of the models. RESULTS: The independent risk factors for the malignancy of PSN include roughness (ngtdm), dependence variance (gldm), and short run low gray-level emphasis (glrlm). Logistic regression achieved area under the curves ( AUCs) of 0.86 and 0.89 in the training and testing sets, respectively, showing good performance. XGBoost had AUCs of 0.78 and 0.77, respectively, demonstrating relatively balanced performance, but with lower accuracy. SVM showed an AUC of 0.93 in the training set, which decreased to 0.80 in the testing set, indicating overfitting. LightGBM performed excellently in the training set with an AUC of 0.94, but its performance declined in the testing set, with an AUC of 0.88. In contrast, random forest demonstrated stable performance in both the training and testing sets, with AUCs of 0.89 and 0.91, respectively, exhibiting high stability and excellent generalizability. CONCLUSIONS The random forest model constructed based on independent risk factors demonstrated the best performance in predicting the malignancy of PSN and could provide effective auxiliary predictions for clinicians, supporting individualized treatment decisions.
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Humans ; Male ; Female ; Lung Neoplasms/pathology* ; Middle Aged ; Retrospective Studies ; Artificial Intelligence ; Aged ; Tomography, X-Ray Computed ; Adult ; Solitary Pulmonary Nodule/diagnostic imaging* ; ROC Curve

Fibrosis, the pathological scarring of vital organs, is a severe and often irreversible condition that leads to progressive organ dysfunction. It is particularly pronounced in organs like the liver, kidneys, lungs, and heart. Despite its clinical significance, the full understanding of its etiology and complex pathogenesis remains incomplete, posing substantial challenges to diagnosing, treating, and preventing the progression of fibrosis. Among the various molecular players involved, platelet-derived growth factor-C (PDGF-C) has emerged as a crucial factor in fibrotic diseases, contributing to the pathological transformation of tissues in several key organs. PDGF-C is a member of the PDGFs family of growth factors and is synthesized and secreted by various cell types, including fibroblasts, smooth muscle cells, and endothelial cells. It acts through both autocrine and paracrine mechanisms, exerting its biological effects by binding to and activating the PDGF receptors (PDGFRs), specifically PDGFRα and PDGFRβ. This binding triggers multiple intracellular signaling pathways, such as JAK/STAT, PI3K/AKT and Ras-MAPK pathways. which are integral to the regulation of cell proliferation, survival, migration, and fibrosis. Notably, PDGF-C has been shown to promote the proliferation and migration of fibroblasts, key effector cells in the fibrotic process, thus accelerating the accumulation of extracellular matrix components and the formation of fibrotic tissue. Numerous studies have documented an upregulation of PDGF-C expression in various fibrotic diseases, suggesting its significant role in the initiation and progression of fibrosis. For instance, in liver fibrosis, PDGF-C stimulates hepatic stellate cell activation, contributing to the excessive deposition of collagen and other extracellular matrix proteins. Similarly, in pulmonary fibrosis, PDGF-C enhances the migration of fibroblasts into the damaged areas of lungs, thereby worsening the pathological process. Such findings highlight the pivotal role of PDGF-C in fibrotic diseases and underscore its potential as a therapeutic target for these conditions. Given its central role in the pathogenesis of fibrosis, PDGF-C has become an attractive target for therapeutic intervention. Several studies have focused on developing inhibitors that block the PDGF-C/PDGFR signaling pathway. These inhibitors aim to reduce fibroblast activation, prevent the excessive accumulation of extracellular matrix components, and halt the progression of fibrosis. Preclinical studies have demonstrated the efficacy of such inhibitors in animal models of liver, kidney, and lung fibrosis, with promising results in reducing fibrotic lesions and improving organ function. Furthermore, several clinical inhibitors, such as Olaratumab and Seralutinib, are ongoing to assess the safety and efficacy of these inhibitors in human patients, offering hope for novel therapeutic options in the treatment of fibrotic diseases. In conclusion, PDGF-C plays a critical role in the development and progression of fibrosis in vital organs. Its ability to regulate fibroblast activity and influence key signaling pathways makes it a promising target for therapeutic strategies aiming at combating fibrosis. Ongoing research into the regulation of PDGF-C expression and the development of PDGF-C/PDGFR inhibitors holds the potential to offer new insights and approaches for the diagnosis, treatment, and prevention of fibrotic diseases. Ultimately, these efforts may lead to the development of more effective and targeted therapies that can mitigate the impact of fibrosis and improve patient outcomes.

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.

Objective: To evaluate the effects of dietary intervention on blood pressure and renal function in patients with hypertensive nephropathy, so as to provide dietary and nutritional guidances for this population. Methods: Hypertensive nephropathy patients who were treated at Zhucheng People's Hospital from March 2023 to February 2024 were selected as the study subjects and randomly divided into the intervention group and the control group. The control group received routine antihypertensive treatment and health lifestyle guidance. On the basis of the treatment and guidance received by the control group, the intervention group implemented dietary intervention in accordance with the Clinical Practice Guidelines for Nutritional Therapy of Chronic Kidney Disease in China (2021 edition) for a period of 3 months. Systolic blood pressure (SBP), diastolic blood pressure (DBP) were measured before and after the intervention, and serum creatinine (Scr), blood urea nitrogen (BUN), uric acid (UA), cystatin and β2-microglobulin were detected. Differences of indicators before and after intervention between the two groups were compared using generalized estimation equation. Results: A total of 83 patients with hypertensive nephropathy were followed up, including 43 cases in the intervention group and 40 cases in the control group. There were no statistically significant differences in gender, age, body mass index, duration of hypertension, family history of hypertension, hypertension grade, physical activity index, or smoking status between the two groups (all P>0.05). The differences in SBP, DBP, Scr, BUN, and UA between the two groups, as well as the differences before and after the intervention, were statistically significant, and there was an interaction between the groups and the intervention time (all P<0.05). After intervention, the levels of SBP, DBP, Scr, BUN, and UA in the intervention group were lower than those in the control group (all P<0.05). The differences in cystatin and β2-microglobulin between the two groups and before and after the intervention were not statistically significant, and there was no interaction between the groups and the intervention time (all P>0.05). Conclusion Dietary intervention has a certain effect on reducing blood pressure and improving renal function indicators in patients with hypertensive nephropathy.