Objective:To investigate the effect of CT-derived fractional flow reserve (CT-FFR) measurement sites on the values and the diagnostic performance, and to determine the optimal measurement site for CT-FFR using invasive FFR as the reference standard.Methods:This study was part of the CT-FFR CHINA clinical trial. Patients with suspected coronary artery disease who were scheduled for invasive coronary angiography (ICA) were prospectively recruited from five clinical centers across the country from November 2018 to March 2020. Each enrolled patient underwent coronary CT angiography (CCTA), CT-FFR, ICA, and invasive pressure wire-based FFR assessments sequentially within one week. Four groups of CT-FFR values were obtained on each enrolled target vessels according to different CT-FFR measurement locations: 1, 2, 3 cm distal to the target lesion, and terminal vessel groups. Spearman and Bland-Altman analyses were used to explore the correlation and consistency of CT-FFR values and FFR values at different measurement sites. The measurement deviation of CT-FFR was also compared. Diagnostic accuracy and performance of CT-FFR, including sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC), in discriminating myocardial ischemia were analyzed across all measurement site groups on a per-vessel level, using FFR as the reference standard.Results:A total of 289 patients with 345 target lesion vessels were included. According to CCTA, there were 51 target vessels (14.8%) with<50% stenosis, 106 vessels (30.7%) with 50%-69% stenosis, and 188 vessels (54.5%) with stenosis≥70%. At per-vessel level, CT-FFR and FFR values at each measurement position group were highly positively correlated: 1 cm distal to target lesion group, r=0.734 ( P<0.001); 2 cm distal to target lesion group, r=0.732 ( P<0.001); 3 cm distal to target lesion group, r=0.737 ( P<0.001); terminal vessel group was 0.719 ( P<0.001). At per-vessel level, CT-FFR and FFR values of all measurement sites were in good agreement (Bland-Altman analysis results): 1 cm distal to target lesion group, 0.014 (95% LoA 0.002-0.026); 2 cm distal to target lesion group, 0.026 (95% LoA 0.015-0.038); 3 cm distal to target lesion group, 0.040 (95% LoA 0.039-0.051); terminal vessel group, 0.075 (95% LoA 0.064-0.087). And at per-vessel level, the accuracy of diagnosing myocardial ischemia with CT-FFR at 1 cm was highest [84.6% (95% CI 80.4%-88.3%)], and the lowest accuracy in the terminal vessel group [67.0% (95% CI 61.7%-72.0%)]. However, there was no significant difference in the diagnostic accuracy of CT-FFR at 1 cm, 2 cm [80.6% (95% CI 76.1%-84.6%)] and 3 cm [77.5% (95% CI 72.6%-81.7%)]. AUC of CT-FFR at 1 cm distal to the lesion were both highest for global level and moderately stenosis (50%-69%) lesions [0.85 (95% CI 0.81-0.89), 0.84 (95% CI 0.77-0.90)]. And the differences were statistically significant among the four measurement location groups (all P<0.05). Conclusions:The deviation of CT-FFR increases with measurement site distance distal to target lesions. One centimeter distal to the target lesion is the optimal measurement site, and the CT-FFR value here shows the highest diagnostic performance for myocardial ischemic lesions, especially for moderate stenosis.

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.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

High altitude heart disease(HAHD)is a chronic mountain sickness in which the body is exposed to high altitude(＞2 500 m)hypobaric hypoxia environment for a long time.HAHD has high morbidity and poor prognosis,and pulmonary hypertension is the main causative mechanism for its develop-ment.The phosphodiesterase-5 inhibitor sildenafil has become a hot drug for the treatment of pulmonary hypertension.This paper reviews the progress of HAHD and discusses the mechanism of action and effectiveness of sildenafil in the treatment of HAHD,with a view to providing a basis for the treatment of HAHD with sildenafil.

Objective:To investigate the selection of treatment methods for renal tumors in pilots as well as the clinical significance of robot-assisted surgery by summarizing the process of robot-assisted surgery in the treatment of renal cell carcinoma in a pilot.Methods:The diagnosis, robot-assisted surgery and aeromedical assessment of a pilot with renal cell carcinoma were reported, and the related literature was reviewed.Results:The patient was a 44-year-old male transporter pilot, who was diagnosed with a left renal mass in the middle-lower pole of the kidney during a routine abdominal CT scan. After detailed preoperative evaluation that ruled out the possibility of distant metastasis and other surgical contraindications, the patient underwent robot-assisted laparoscopic partial nephrectomy in August 2022. The postoperative recovery went well, and renal function remained within normal limits at follow-ups. In March 2023, the pilot was concluded as qualified for flight after aeromedical assessment.Conclusions:Robot-assisted partial nephrectomy can significantly reduce surgical trauma, lower the risk of complications, and maximally preserve renal function. It is a good approach to renal tumors in pilots who can recover quickly.