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.

This paper aimed to explain the clinical thinking of using the method of unblocking the bowels and harmonizing viscera. Based on theory of "viscera-bowels extraordinary connection" of The Gateway to Medicine （《医学入门》）， combined with the theoretical research， clinical practice and individual experience of ancient physicians， modern scholars， it is believed that viscera qi disorder caused by bowels qi blocking is the basic mechanism of insomnia. In clinic， it is common that gallbladder phlegm-heat harassing the heart spirit， stagnant blood and qi in stomach blocking the pericardium， turbid heat in large intestine causing fire and affecting liver， dampness insmall intestine trapping the spleen， water retention in the bladder drying up lungs， and the inhibited original qi of sanjiao damaging the kidney， which could be treated with Wendan Decoction （温胆汤）， Taohe Chengqi Decoction （桃核承气汤）， Chengqi-series Decoction （承气汤类方）， Linggui Zhugan Decoction （苓桂术甘汤）， Wuling Powder （五苓散）， Xiaochaihu Decoction （小柴胡汤）， respectively.

Objective To observe the body surface calorific value characteristics of Governor Vessel and Conception Vessel,triple energizer,and zang-fu organs chronic insomnia patients with heart-spleen deficiency syndrome through infrared thermal imaging technology.Methods Totally 150 patients with chronic insomnia with heart-spleen deficiency syndrome who were treated in the outpatient department of Shenzhen Hospital of Beijing University of Chinese Medicine(Longgang)from December 2021 to December 2022 were selected as the observation group.Another 50 healthy subjects were recruited as the normal control group.Infrared thermal imaging technology was used to collect and measure the temperature of surface areas of Governor Vessel and Conception Vessel,triple energizer,and zang-fu organs,and the calorific values were analyzed and compared.Results Compared with healthy subjects,chronic insomnia patients with heart-spleen deficiency syndrome had a statistically significant decrease in the temperature of the Governor Vessel(P<0.05);there were statistically significant decreased in the temperature of upper energizer and middle energizer(P<0.05);there were statistically significant decreased in the temperature of chest,apex,right chest,epigastric region,big abdomen,and the temperature of left and right flank increased(P<0.05).Conclusion There were significant differences in infrared thermography distribution characteristics of Governor Vessel and Conception Vessel,triple energizer,and zang-fu organs between patients with chronic insomnia with heart-spleen deficiency syndrome and healthy subjects,which can provide some reference for the clinical diagnosis and syndrome differentiation of chronic insomnia with heart-spleen deficiency syndrome.

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.

Objective:To survey the perceived social support status and influencing factors of medical staffs working in community health service institutions in Shanghai Minhang District .Methods:The study was a cross-sectional study. From September 2022 to January 2023, a survey on the status of perceived social support was conducted among 181 medical staffs working in community health service institutions in Shanghai Minhang District. The self-designed general information questionnaire, perceived social support scale, general self-efficacy scale, quality of professional life scale, and trait coping style scale were used in the survey. The effects of demographic characteristics, general self-efficacy, empathy fatigue and trait coping style on perceived social support status of community medical workers were analyzed.Results:A total of 181 questionnairs were distributed and 178 valid ones returned with a valid recovery rate of 98.3%. In three dimensions of perceived social support, family support scored (17.11±8.87), friend support scored (17.08±8.41), other support scored (19.89±4.09), and the total score of understanding social support was (60.99±11.71). There were 2 cases of low support status (1.12%), 81 cases of intermediate support status (45.51%), and 95 cases of high support status (53.37%). Univariate analysis showed that there were significant differences in perceived social support among participants with different ages, marriage status, majors, professional titles, job satisfaction, positive or negative coping styles, general self-efficacy, and empathy fatigue ( P<0.05). Multivariate logistic regression analysis showed that people aged 40 and above had a higher degree of perceived social support than those under 40 ( OR=2.792, 95% CI: 1.051-7.418, P<0.05); compared with public health professionals, clinical medicine, nursing and other medical technique professionals had a higher degree of perceived social support ( OR=4.024, 95% CI: 1.479-10.953; OR=2.941, 95% CI: 1.031-8.393; OR=3.996, 95% CI: 0.543-29.409, all P<0.05); compared with those who were less satisfied with their self-assessment work, participants who were more satisfied or generally satisfied with their self-assessment work had lower perceived social support ( OR=0.200, 95% CI: 0.051-0.781; OR=0.320, 95% CI: 0.146-0.701, all P<0.05); compared with those with mild and moderate empathy fatigue, participants with high empathy fatigue had lower perceived social support ( OR=0.406, 95% CI: 0.182-0.909, P<0.05). Except supporting primary and secondary traumatic stress, the total score of perceived social support and its dimensions were positively correlated with empathy satisfaction; and negatively correlated with job burnout and secondary traumatic stress. Regression analysis shows that empathy satisfaction had a positive predictive effect on overall scores of perceived social support and its dimensions of friend support and other support capacity. Conclusions:The social support status of community healthcare workers in Shanghai Minhang district is generally acceptable. However, it is important to pay special attention to the social support status of those who are under 40 years old, have a background in public health, are satisfied with their work, and experience a high level of empathy fatigue. Measures should be implemented to specifically enhance empathy satisfaction among healthcare workers; timely guidance and intervention should be provided accordingly.