BACKGROUND: Biomarkers-based prediction of long-term risk of acute coronary syndrome (ACS) is scarce. We aim to develop a risk score integrating clinical routine information (C) and plasma biomarkers (B) for predicting long-term risk of ACS patients. METHODS: We included 2729 ACS patients from the OCEA (Observation of cardiovascular events in ACS patients). The earlier admitted 1910 patients were enrolled as development cohort; and the subsequently admitted 819 subjects were treated as validation cohort. We investigated 10-year risk of cardiovascular (CV) death, myocardial infarction (MI) and all cause death in these patients. Potential variables contributing to risk of clinical events were assessed using Cox regression models and a score was derived using main part of these variables. RESULTS: During 16,110 person-years of follow-up, there were 238 CV death/MI in the development cohort. The 7 most important predictors including in the final model were NT-proBNP, D-dimer, GDF-15, peripheral artery disease (PAD), Fibrinogen, ST-segment elevated MI (STEMI), left ventricular ejection fraction (LVEF), termed as CB-ACS score. C-index of the score for predication of cardiovascular events was 0.79 (95% CI: 0.76-0.82) in development cohort and 0.77 (95% CI: 0.76-0.78) in the validation cohort (5832 person-years of follow-up), which outperformed GRACE 2.0 and ABC-ACS risk score. The CB-ACS score was also well calibrated in development and validation cohort (Greenwood-Nam-D'Agostino: P = 0.70 and P = 0.07, respectively). CONCLUSIONS CB-ACS risk score provides a useful tool for long-term prediction of CV events in patients with ACS. This model outperforms GRACE 2.0 and ABC-ACS ischemic risk score.

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

Objective:To compare the application of Micronutritional Risk Assessment(MNA),Universal Screening Tool for Malnutrition(MUST)and Nutritional Risk Screening 2002(NRS2002)in nutritional risk assessment among patients with digestive tract tumors during perichemotherapy,based on the Global Leadership Initiative on Malnutrition(GLIM)standard.Methods:A prospective cross-section study was conducted,including 114 patients with digestive tract tumors hospitalized by Department of General Surgery,Huangshan Shoukang Hospital from January 2020 to December 2021.All patients were evaluated by GLIM assessment,the correlation between GLIM and MNA,MUST and NRS 2002 screening results was compared,and the consistency among different methods was compared.Patients were divided into malnourished group(nutritional risk group)or normal nourished group according to the results of the three tools.The differences in single anthropometric or test indicators between the groups were compared.Results:According to GLIM,the proportion of malnutrition was 36.8%.The proportion of malnutrition evaluated by MNA,MUST,and NRS2002 were 63.2%,47.4%,and 32.5%,respectively.The sensitivity and negative predictive value of MNA in assessing nutrition-related risks were the highest,while the specificity,Jorden index,Kappa value and positive predictive value of NRS2002 were the highest.There were statistical differences in levels of body mass index,hemoglobin(Hb),triglyceride,total cholesterol,albumin,prealbumin(P-ALB),blood creatinine,lymphocyte counts,and hospitalization costs between two groups assessed by three different tools(P<0.05).Levels of Hb and P-ALB were statistically different between the two groups of the three screening tools.Conclusion:Based on GLIM evaluation results,MNA and other nutritional screening tools are applicable to the assessment of nutritional risks of patients with gastrointestinal cancer during perichemotherapy due to the joint evaluation of measurement indicators.The MNA is more recommended with the highest detection rate and sensitivity for nutritional risks assessment.

Objective To develop a machine learning-based risk prediction model for postoperative acute kidney injury(AKI)and a model for mortality in obese patients admitted to intensive care unit(ICU)in order to improve early warning and prognostic evaluation to support clinical decision-making.Methods Data of obese postoperative ICU patients were retrospectively retrieved from the MIMIC-Ⅳ and eICU databases for statistical analysis.Ultimately,2 520 patients(670 from MIMIC-Ⅳ and 1 850 from eICU databases)were included to build the risk prediction models for AKI and mortality.The data included demographic information,vital signs,laboratory findings,surgical types,comorbidities,and medication use.After data cleaning and preprocessing,Boruta feature selection was applied,followed by the construction of prediction models using 7 machine learning algorithms,that is,Gradient Boosting Machine(GBM),Generalized Linear Model(GLM),k-Nearest Neighbors(KNN),Na?ve Bayes(NB),Neural Network(NNET),Support Vector Machine(SVM),and XGBoost.Model performance was evaluated through cross-validation and external validation.Results In the risk prediction models of AKI,the SVM model achieved the highest AUC value of 0.80 in the testing set and 0.71 in the external validation test.For the risk prediction models of mortality,the GBM model outperformed others in the prediction,attaining an AUC value of 0.91 in the testing set.Conclusion Risk predictive models for postoperative AKI and mortality in obese ICU patients are successfully constructed,and are valuable tools for clinicians to optimize early intervention and improve clinical outcomes for the patients.

Puerarin is a monomeric isoflavone compound derived from Puerariae Lobatae Radix. It exhibits poor solubility in both water and lipids, resulting in suboptimal oral absorption and low bioavailability. There is therefore an urgent need to develop new methods of applying puerarin to enhance its solubility and bioavailability. Studies have revealed that puerarin possesses distinctive physical and chemical properties, including the ability to self-assemble into supramolecular hydrogels in response to temperature changes. In this review, the research progress of puerarin as a hydrogel system containing loaded drugs, as well as a hydrogel system composed of hydrogel matrix in the field of tissue regeneration was summarized. This is intended to provide a reference for the rational and efficient use of drugs and lay the groundwork for the development and preparation of new drug carrier platforms.

Objective:To investigate the possible mechanism of DiI labeled bone marrow mesenchymal stem cells (BMSCs) in contact co-cultured with neonatal rat cardiomyocytes (CMs) on polycaprolactone (PCL) film to make myocardial patch.Methods:BMSCs from Sprague Dawley rats (aged 5-6 weeks) were isolated, cultured, and characterized for surface marker expression using flow cytometry. CMs from 15 neonatal rats were isolated and cultured. After cultured for 3 generations, BMSCs were labeled with DiI dye. On PCL film, DiI labeled BMSCs were co-cultured with CMs as the experimental group, and CMs were replaced with the same amount of unlabeled BMSCs in the control group. After 24 h of co-culture, the cell growth was observed under fluorescence microscope and the co-culture was observed under scanning electron microscope. Immunofluorescence staining was performed after 7 days to detect myocardial markers, including cardiac troponin T (cTnT) and α-actinin. BMSC differentiation on the PCL film was observed under a fluorescence microscope. The differentiation efficiency of BMSCs into cardiomyoid cells was analyzed by flow cytometry on days 1 and 7 of co-culture. Intercellular dye transfer was observed by staining CMs with calcein and co-culturing them with DiI-labeled BMSCs on PCL film. The cells were stained with immunofluorescence to detect the expression of connexin 43 (Cx43) and observe the relationship between gap junction and contact co-culture.Results:Flow cytometry showed strong positivity for CD90 and CD44 and negativity for CD11b/c and CD45 on BMSCs. After 24 h of co-culture, DiI labeled BMSCs glowed red on the PCL film, while unlabeled CMs did not; the number of cells on PCL film was large and cell morphology appeared normal under scanning electron microscope. On the 7th day of co-culture, some DiI labeled BMSCs expressed cTnT and α-actinin. Flow cytometry showed a higher differentiation rate of stem cells in the experimental group on day 7 compared to the control group ((20.12±0.15)% vs. (3.49±0.20)%, P<0.05). From the second day of co-culture, some BMSCs exhibited green dot fluorescence in Cx43 immunofluorescence staining; and by the third day, dye transfer test showed green fluorescence emission from some BMSCs. Conclusion:Contact co-culture of DiI labeled BMSCs and CMs on PCL film can make myocardial patch. The mechanism of contact co-culture promoting the differentiation and formation of myocardial patch may be associated with gap junctions and intercellular signal pathways mediated by gap junctions.

Objective To develop the'E-Bone',a comprehensive one-stop preoperative planning system for reverse total shoulder arthroplasty with improved accuracy and efficiency.Methods The nnU-net deep neural network was utilized for scapula segmentation to obtain precise scapula segmentation results.Based on the 3 key factors,namely bone density,upward and downward angle and nail length,the base was automatically positioned.The quantitative parameters required for surgical planning were calculated.A personalized guide plate was generated by combining glenoid morphology and base positioning information.The system interface was developed to modularize various functions for easy use,providing interactive operation and real-time display.Results Compared with the Mimics system,the'E-bone'preoperative planning system reduced complex manual adjustments during the planning process.The average planned nail length was longer than that of the Mimics system,and the planning time was reduced by 86%.The scapula segmentation accuracy of this system reached 99.93%,better than that of Mimics to achieve a higher precision.Conclusion The"E-bone"system provides a one-stop,efficient,and accurate preoperative planning system for reverse shoulder replacement and potentially broader clinical applications.

Thyroid cancer is the common malignant tumor in the neck, and surgery is the important treatment measure for it. Some patients suffer from hypoparathyroidism and hypocalcemia after thyroidectomy, which will seriously affect the patient’s life quality and prognosis. This article reported a case of 42 years old female patient with hypocalcemia for 6 years after total thyroidectomy due to thyroid cancer, who still had frequent hypocalcemia with high dose of oral calcium and active vitamin D supplementation. Long-term and frequent facial and limb numbness, convulsions, epileptic-like seizures and sudden unconsciousness afflicted her due to hypocalcemia. After admission, her symptoms were obviously relieved after one week of adequate calcium supplementation through oral administration or intravenous infusion under close monitoring. Upon discharge she was able to maintain the normal level of blood calcium by decreased dose of oral calcium supplementation alone. Long-term limb numbness, convulsions, low back pain, shoulder pain, walking instability and other symptoms disappeared basically. The epileptic-like seizures did not recur. During six months of follow-up, her blood calcium was still well controlled in normal level.

Objective To develop the'E-Bone',a comprehensive one-stop preoperative planning system for reverse total shoulder arthroplasty with improved accuracy and efficiency.Methods The nnU-net deep neural network was utilized for scapula segmentation to obtain precise scapula segmentation results.Based on the 3 key factors,namely bone density,upward and downward angle and nail length,the base was automatically positioned.The quantitative parameters required for surgical planning were calculated.A personalized guide plate was generated by combining glenoid morphology and base positioning information.The system interface was developed to modularize various functions for easy use,providing interactive operation and real-time display.Results Compared with the Mimics system,the'E-bone'preoperative planning system reduced complex manual adjustments during the planning process.The average planned nail length was longer than that of the Mimics system,and the planning time was reduced by 86%.The scapula segmentation accuracy of this system reached 99.93%,better than that of Mimics to achieve a higher precision.Conclusion The"E-bone"system provides a one-stop,efficient,and accurate preoperative planning system for reverse shoulder replacement and potentially broader clinical applications.