Gorham-Stout disease(GSD) is a rare osteolytic disorder characterized by spontaneous and progressive osteolysis, along with abnormal angiogenesis and lymphangiogenesis, with no new bone formation. We present a case of a 15-year-old female admitted due to " recurrent right leg pain for 5 years, 11 months after undergoing right femoral fracture surgery". Through comprehensive integration of the patient's clinical phenotype, laboratory tests, imaging findings, pathological examinations, and molecular biological test results, GSD was considered highly likely. A multidisciplinary treatment approach was conducted, including a combination of zoledronic acid and sirolimus to inhibit osteolysis, along with rehabilitation training and orthopedic intervention, providing a personalized and comprehensive treatment strategy.

ObjectiveThis paper aims to conduct the feature analysis and correlation analysis on the ocular collateral features and differential metabolites in patients with chronic hepatitis B （CHB） complicated by glucose metabolism disorder （GMD），particularly those with the damp-heat syndrome type，by integrating shadowless scleral imaging and metabolomics technologies. MethodsA total of 313 patients were recruited from the Hepatology and Endocrinology Outpatient Departments of Public Health Clinical Center of Chengdu according to the inclusion/exclusion criteria，and they were divided into a CHB group and a CHB complicated by GMD groups （damp-heat syndrome group and non-damp-heat syndrome group）. All patients underwent high-definition ocular image acquisition and feature extraction using an intelligent analysis system for shadowless scleral imaging to analyze the differences in the counting of morphological feature scores of ocular collaterals among groups. By using a digital sampling method，24 patients from each group were randomly selected，along with 20 healthy volunteers，for untargeted metabolomic analysis of peripheral serum. Differential metabolites were identified，statistically analyzed，and subjected to potential biomarker analysis and pathway enrichment. Spearman method was performed to conduct the correlation analysis on the differential ocular collateral features and differential metabolites，followed by correlation network construction. ResultsCompared with those in the CHB group，patients with CHB complicated by GMD showed significant changes in ocular collateral feature scores such as "hillock"，"blood vessels"，and "pale dusky coloration" （P<0.05）. In comparison with those in the healthy group，metabolites including N-acetylglucosamine，acetylhomoserine，and myo-inositol （AUC>0.7） were identified as potential biomarkers for the disease. Compared with those in the CHB complicated by GMD group with non-damp-heat syndrome，patients with damp-heat syndrome exhibited significant changes in feature scores of "plaques"，"yellow coloration"，"spleen"，and "gallbladder" （P<0.05）. In comparison with those in the healthy group，metabolites such as O²′-4a-cyclic tetrahydrobiopterin，theobromine，xanthurenic acid，and L-glutamic acid 5-phosphate （AUC>0.7） were identified as potential biomarkers for the damp-heat syndrome type. The Spearman correlation analysis reveals weak to moderate linear correlations between the differential scleral collateral features and metabolites. By constructing a "disease-syndrome" network of ocular diagnosis and metabolites，"xanthurenic acid-gallbladder" and "theobromine-plaque/yellow coloration" were identified as specific molecular-phenotypic correlated biomarker clusters for CHB complicated by GMD with dampness-heat syndrome. ConclusionPatients with CHB complicated by GMD demonstrate differential ocular diagnostic features and serum metabolites corresponding to disease states and dampness-heat syndrome. These objective biomarkers can guide both clinical syndrome differentiation and medication. The macro-micro integration based on ocular feature clusters and potential metabolic biomarkers offers an innovative approach to a combined traditional Chinese and Western medicine diagnosis and treatment model for this disease.

Expert consensus, as an important supplement to clinical practice guidelines, supports clinical decision-making when evidence is lacking or controversial. Compared to clinical practice guidelines, the presentation of expert consensus is more diverse. Currently, there are no reporting guidelines for expert consensus in clinical and public health decision-making. The RIGHT (Reporting Items for Practice Guidelines in Healthcare) checklist is the most commonly used international guideline reporting standard, and is often referred to when writing expert consensus. However, the RIGHT checklist does not include a section on consensus formation methods; while the ACCORD (ACcurate COnsensus Reporting Document) checklist includes reporting requirements for consensus formation methods, but not for reporting recommendations. Therefore, this article integrates the RIGHT and ACCORD reporting checklists and proposes an integrated reporting framework (TIMER-DO) to help authors combine these two commonly used international reporting standards and complete the standardized reporting of expert consensus.

ObjectiveTo characterize the evidence distribution and methodological quality of randomized controlled trials （RCTs） on oral Chinese herbal medicine （CHM） for atopic dermatitis （AD） based on evidence mapping. MethodsSeven databases （CNKI， Wanfang Data， VIP， CBM， Cochrane Library， PubMed， and Embase） and the Chinese Clinical Trial Registry were searched for the RCTs in Chinese and English. Evidence distribution was presented graphically and textually， and methodological quality was assessed via the Cochrane Risk of Bias tool （ROB 1.0）. ResultsA total of 168 RCTs were included. The number of annual publications showing an increasing trend， and 72.6% RCTs had sample sizes of 51-100 participants. The studies evaluated 108 distinct CHM interventions categorized as decoctions， granules， Chinese patent medicines， and extracts. Compound Glycyrrhizin was the most frequently used， followed by Xiaofengsan and Chushi Weiling decoction. Among the RCTs， 57.1% had the treatment courses of 4-8 weeks. Outcome measures predominantly focused on clinical response rate， skin lesion severity scores， and adverse events， with less attention to TCM symptom scores， skin barrier function， and relapse rates. The overall risk of bias was generally high. ConclusionWhile CHM for AD is a research hotspot and demonstrates clinical advantages， the related studies have problems such as unclear clinical positioning， poor research standardization and methodological quality， and insufficient prominence of TCM clinical advantages. Large-sample， methodologically rigorous， and high-quality studies are needed to enhance the evidence base for CHM in treating AD.

ObjectiveTo characterize the evidence distribution and methodological quality of randomized controlled trials （RCTs） on oral Chinese herbal medicine （CHM） for atopic dermatitis （AD） based on evidence mapping. MethodsSeven databases （CNKI， Wanfang Data， VIP， CBM， Cochrane Library， PubMed， and Embase） and the Chinese Clinical Trial Registry were searched for the RCTs in Chinese and English. Evidence distribution was presented graphically and textually， and methodological quality was assessed via the Cochrane Risk of Bias tool （ROB 1.0）. ResultsA total of 168 RCTs were included. The number of annual publications showing an increasing trend， and 72.6% RCTs had sample sizes of 51-100 participants. The studies evaluated 108 distinct CHM interventions categorized as decoctions， granules， Chinese patent medicines， and extracts. Compound Glycyrrhizin was the most frequently used， followed by Xiaofengsan and Chushi Weiling decoction. Among the RCTs， 57.1% had the treatment courses of 4-8 weeks. Outcome measures predominantly focused on clinical response rate， skin lesion severity scores， and adverse events， with less attention to TCM symptom scores， skin barrier function， and relapse rates. The overall risk of bias was generally high. ConclusionWhile CHM for AD is a research hotspot and demonstrates clinical advantages， the related studies have problems such as unclear clinical positioning， poor research standardization and methodological quality， and insufficient prominence of TCM clinical advantages. Large-sample， methodologically rigorous， and high-quality studies are needed to enhance the evidence base for CHM in treating AD.

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 clinical burden of colorectal cancer (CRC) is high. Population-based screening and early detection are essential to improve the long-term clinical outcome. Nonetheless, a significant proportion of patients still present at an advanced stage, including with acute large bowel obstruction. Image-enhanced endoscopy and artificial intelligence can improve the detection and diagnosis of colonic adenomas and early cancer. Endoscopic resection is regarded as the preferred curative treatment option for colonic adenoma and T0 and T1 CRC limited to the superficial submucosa. Emergency colonic stenting as bridge to interval curative surgery is increasingly accepted as a first-line option when technically feasible. Minimally invasive resection techniques such as laparoscopic colectomy and robot-assisted colorectal surgery have also come of age. These techniques reduce post-treatment morbidity, shorten the recovery process and can be cost-effective while maintaining long-term oncological cure. These outcome measures are relevant to our patients; therefore, minimally invasive approaches to curative resection should be embraced.
Humans ; Colorectal Neoplasms/surgery* ; Minimally Invasive Surgical Procedures/methods* ; Laparoscopy/methods* ; Colectomy/methods* ; Robotic Surgical Procedures/methods* ; Treatment Outcome ; Colonoscopy/methods*

Definitive treatment of lung cancer with radiotherapy is challenging, as respiratory motion and anatomical changes can increase the risk of severe off-target effects during radiotherapy. Online adaptive radiotherapy (ART) is an evolving approach that enables timely modification of a treatment plan during the interfraction of radiotherapy, in response to physiologic or anatomic variations, aiming to improve the dose distribution for precise targeting and delivery in lung cancer patients. The effectiveness of online ART depends on the seamless integration of multiple components: sufficient quality of linear accelerator-integrated imaging guidance, deformable image registration, automatic recontouring, and efficient quality assurance and workflow. This review summarizes the present status of online ART for lung cancer, including key technologies, as well as the challenges and areas of active research in this field.
Humans ; Lung Neoplasms/radiotherapy* ; Radiotherapy Planning, Computer-Assisted/methods*

BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome