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.

Following the core outcome set standards for development(COS-STAD), this study aims to construct core outcome set(COS) for clinical research on traditional Chinese medicine(TCM) treatment of simple obesity. Firstly, a comprehensive review was conducted on the randomized controlled trial(RCT) and systematic review(SR) about TCM treatment of simple obesity that were published in Chinese and English databases to collect reported outcomes. Additional outcomes were obtained through semi-structured interviews with patients and open-ended questionnaire surveys for clinicians. All the collected outcomes were then merged and organized as an initial outcome pool, and then a preliminary list of outcomes was formed after discussion by the working group. Subsequently, two rounds of Delphi surveys were conducted with clinicians, methodology experts, and patients to score the importance of outcomes in the list. Finally, a consensus meeting was held to establish the COS for clinical research on TCM treatment of simple obesity. A total of 221 RCTs and 12 SRs were included, and after integration of supplementary outcomes, an initial outcome pool of 141 outcomes were formed. Following discussions in the steering advisory group meeting, a preliminary list of 33 outcomes was finalized, encompassing 9 domains. Through two rounds of Delphi surveys and a consensus meeting, the final COS for clinical research on TCM treatment of simple obesity was determined to include 8 outcomes: TCM symptom scores, body mass index(BMI), waist-hip ratio, waist circumference, visceral fat index, body fat rate, quality of life, and safety, which were classified into 4 domains: TCM-related outcomes, anthropometric measurements, quality of life, and safety. This study has preliminarily established a COS for clinical research on TCM treatment of simple obesity. It helps reduce the heterogeneity in the selection and reporting of outcomes in similar clinical studies, thereby improving the comparability of research results and the feasibility of meta-analysis and providing higher-level evidence support for clinical practice.
Humans ; Obesity/therapy* ; Medicine, Chinese Traditional ; Randomized Controlled Trials as Topic ; Treatment Outcome ; Drugs, Chinese Herbal/therapeutic use*

Homo- or heterodimeric compounds that affect dimeric protein function through interaction between monomeric moieties and protein subunits can serve as valuable sources of potent and selective drug candidates. Here, we screened an in-house dimeric natural product collection, and panepocyclinol A (PecA) emerged as a selective and potent STAT3 inhibitor with profound anti-tumor efficacy. Through cross-linking C712/C718 residues in separate STAT3 monomers with two distinct Michael receptors, PecA inhibits STAT3 DNA binding affinity and transcription activity. Molecular dynamics simulation reveals the key conformation changes of STAT3 dimers upon the di-covalent binding with PecA that abolishes its DNA interactions. Furthermore, PecA exhibits high efficacy against anaplastic large T cell lymphoma in vitro and in vivo, especially those with constitutively activated STAT3 or STAT3^Y640F. In summary, our study describes a distinct and effective di-covalent modification for the dimeric compound PecA to disrupt STAT3 function.

Objective To observe the effect of multi-modal hand hygiene(HH)intervention on HH compliance,as well as the relationship between HH compliance and the healthcare-associated(HA)case infection incidence.Methods From 2014 to 2022,the infection control team in a tertiary first-class hospital implemented multi-modal HH intervention for health care workers(HCWs).The changing trend of HH monitoring data,the correlation be-tween HH compliance rate and HA case infection incidence were analyzed retrospectively.Results The consump-tion of HH products in the wards showed a stable upward trend;HH compliance rate increased from 64.98％in 2014 to 85.01％in 2022(P＜0.001),and HA case infection incidence decreased from 1.21％to 0.83％(P＜0.05).HH compliance rate was negatively correlated with HA case infection incidence(r=-0.369,P=0.027).HH compliance rates in different regions and job posts in each quarter were increased(P＜0.001).For 5 different HH moments in each quarter,HH compliance rate fluctuated slightly before sterile manipulation and after touching patient;presented rising trend after touching surroundings around patient,and decreased before touching patient and after touching patient's body fluid since 2020(P＜0.001).Conclusion Multi-modal HH intervention can im-prove the HH compliance of HCWs,improving their HH awareness is conducive to reducing HA case infection incidence.

Objective To explore the application of nurse-performed point-of-care ultrasound in abdominal distension of ICU patients with enteral nutrition.Methods Purposive sampling method was used to select 108 patients with enteral nutrition abdominal distension admitted to the ICU of a tertiary A general hospital in Hefei City from January to December 2022,and they were divided into an experimental group and a control group according to random number table method.The experimental group used bedside ultrasound to evaluate the stomach,intestine and abdominal cavity of patients with abdominal distension,and implemented targeted treatment measures according to the evaluation results.The control group was given corresponding treatment measures according to the abdominal sight,touch,tapping,listening and traditional syringe withdrawal method.Intra-abdominal pressure,abdominal circumference,feeding compliance rate and feeding interruption rate,ICU stay time and mechanical ventilation time were compared at the 1st,3rd and 5th day.Results 11 cases dropped out of the study due to transfer,automatic discharge,death,etc.,and 97 cases were included 51 cases in the experimental group and 46 cases in the control group.Repeated measurement ANOVA showed that intra-abdominal pressure and abdominal circumference time in the 2 groups had interaction with each other(F=41.724,P＜0.001;F=17.762,P＜0.001).Generalised estimating equations showed that there was only a between-group effect for the rates of feeding compliance and feeding disruption in 2 groups(Wald y2=18.033,P＜0.001;Wald x2=6.567,P＜0.001).Simple effect analysis showed that on the 3rd and 5th day after intervention.The experimental group had lower abdominal depression and the feeding interruption rate was lower than the control group(P＜0.05).On the 5th day after interven-tion,the abdominal circumference of the experimental group was lower than that of the control group,the feeding compliance rate was higher than that of control group(P＜0.05).After intervention,in the experimental group,the mechanical ventilation time was shorter than that of the control group(P＜0.05).There was no significant difference in ICU stay time between the 2 groups(P=0.095).Conclusion The application of nurse-performed point-of-care ultrasound in the management of abdominal distension in patients with enteral nutrition in ICU is feasible and scientific,which is helpful for the management of patients with enteral nutrition abdominal distension in ICU,reducing internal abdominal pressure,shortening mechanical ventilation time,and avoiding the occurrence of feeding intolerance.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective:To explore the feasibility of the AI intelligent reconstruction model based on knee joint magnetic resonance data developed by Nuctech Company Limited for evaluating knee cartilage injury.Methods:Thirty-three patients (a total of forty-one knees) who were hospitalized with severe knee osteoarthritis in Beijing Tsinghua Changgung Hospital from May 2021 to April 2022 were selected. All of them were planned to be performed total knee arthroplasty (TKA) for the treatment of knee osteoarthritis. Fifteen males with an average age of 71±5 years old and twenty six females with an average age of 71±9 years old were included in this study. There were 19 cases of left knee and 22 cases of right knee. Thin layer MRI examination on the patients' knee joints was performed before the surgery, and artificial intelligence model based on the thin layer MRI data of the knee joint was reconstructed. The cartilage part of the model was selected and corrected by Principal Component Analysis (PCA) in order to realize model straightening. The tibial plateau cartilage of knee joint which intercepted during operation was classified according to the International Cartilage Repair Society (ICRS). Finally the results were compared with the ICRS classification results of knee artificial intelligence reconstruction model and artificial recognition of knee joint MRI images.Results:Compared with the grade of cartilage injury intercepted during our operation which was according to the ICRS classification, the sensitivity of artificial intelligence reconstruction model for the diagnosis of cartilage injury with ICRS classification grade four was 93.1%. The specificity of artificial intelligence reconstruction model was 91.4%. The positive predictive value (PPV) of artificial intelligence reconstruction model was 92.2%. And the negative predictive value (NPV) of artificial intelligence reconstruction model was 80.3%. The area under ROC curve (AUC) was 0.92. The ICRS classification consistency between artificial intelligence model and physical inspection results was good with kappa value 0.81 ( P<0.001) . In the aspect of artificial recognition of cartilage injury grading in MRI images, the sensitivity of artificial recognition was 92.10% compared with the manual identification of cartilage injury classification in MRI images. The specificity of artificial recognition was 91.60%. The positive predictive value (PPV) of artificial recognition was 97.20% and the negative predictive value (NPV) of artificial recognition was 78.8%. The kappa value of the cartilage injury classification in MRI images consistency between artificial recognition and manual identification was 0.79 ( P<0.001). Conclusion:Based on the evaluation of cartilage injury by AI reconstruction model of knee joint, the sensitivity and specificity of the diagnosis of ICRS grade IV cartilage injury can be acceptable, but still needs to be improved.

Objective: To investigate the clinical characteristics of hospitalized children infected with the Omicron variant in Kunming after the withdrawal of non-pharmaceutical interventions (NPI) and analyze the risk factors of severe cases. Methods: Clinical data was retrospectively collected from 1 145 children with SARS-CoV-2 Omicron infection who were hospitalized in six tertiary grade A hospitals in Kunming from December 10^th, 2022 to January 9^th, 2023. According to clinical severity, these patients were divided into the general and severe SARS-CoV-2 groups, and their clinical and laboratory data were compared. Between-group comparison was performed using t-test, chi-square test and Mann-Whitney U test. Spearman correlation test and multivariate Logistic regression analysis were used to determine the risk factors of severe illness. Results: A total of 1 145 hospitalized patients were included, of whom 677 were male and 468 female. The age of these patients at visit was 1.7 (0.5, 4.1) years. Specifically, there were 758 patients (66.2%) aged ≤3 years at visit and 387 patients (33.8%) aged >3 years. Of these children, 89 cases (7.8%) had underline diseases and the remaining 1 056 cases (92.2%) had no combined diseases. Additionally, of all the patients, 319 cases (27.9%) were vaccinated with one or two doses of SARS-CoV-2 vaccine, 748 cases (65.3%) had acute upper respiratory tract infection (AURTI), and six cases died (0.5%). A total of 1 051 cases (91.8%) were grouped into general SARS-CoV-2 group and 94 cases (8.2%) were grouped into severe SARS-CoV-2 group. Compared with the general cases, the severe cases showed a lower rate of SARS-CoV-2 vaccination and younger median age, lower lymphocyte count, as well as proportions of CD8⁺T lymphocyte (36 cases (38.3%) vs. 283 cases (26.9%), 0.5 (2.6, 8.0) vs. 1.6 (0.5, 3.9) years, 1.3 (1.0, 2.7) ×10⁹ vs. 2.7 (1.3,4.4)×10⁹/L, 0.17 (0.12, 0.24) vs. 0.21 (0.15, 0.16), respectively, χ²=4.88, Z=-2.21,-5.03,-2.53, all P<0.05). On the other hand, the length of hospital stay, proportion of underline diseases, ALT, AST, creatine kinase isoenzyme, and troponin T were higher in the severe group compared to those in the general group ((11.6±5.9) vs. (5.3±1.8) d, 41 cases (43.6%) vs. 48 cases (4.6%), 67 (26,120) vs. 20 (15, 32) U/L, 51 (33, 123) vs. 44 (34, 58) U/L、56.9 (23.0, 219.3) vs. 3.6 (1.9, 17.9) U/L, 12.0 (4.9, 56.5) vs. 3.0 (3.0, 7.0) ×10^-3 pg/L,respectively, t=-20.43, χ²=183.52, Z=-9.14,-3.12,-6.38,-3.81, all P<0.05). Multivariate regression analysis indicated that increased leukocyte count (OR=1.88, 95%CI 1.18-2.97, P<0.01), CRP (OR=1.18, 95%CI 1.06-1.31, P<0.01), ferritin (OR=1.01, 95%CI 1.00-1.00, P<0.01), interleukin (IL)-6 (OR=1.05, 95%CI 1.01-1.08, P=0.012), D-dimer (OR=2.56, 95%CI 1.44-4.56, P<0.01) and decreased CD4⁺T lymphocyte (OR=0.84, 95%CI 0.73-0.98, P=0.030) were independently associated with the risk of severe SARS-CoV-2 in hospitalized children with Omicron infection. Conclusions: After the withdrawal of NPI, the pediatric inpatients with Omicron infection in Kunming were predominantly children younger than 3 years of age, and mainly manifested as AURTI with relatively low rate of severe SARS-CoV-2 infection and mortality. Elevated leukocyte counts, CRP, ferritin, IL-6, D-dimer, and decreased CD4⁺T lymphocytes are significant risk factors for developing severe SARS-CoV-2 infection.
Humans ; Child ; Female ; Male ; COVID-19 ; COVID-19 Vaccines ; Retrospective Studies ; SARS-CoV-2 ; Ferritins ; Interleukin-6

Humans ; Muscular Dystrophy, Duchenne/epidemiology* ; Prevalence ; Myocardium