An Expert-Knowledge-Based Graph Convolutional Network for Skeleton- Based Physical Rehabilitation Exercises Assessment.

Physical therapists play a crucial role in guiding patients through effective and safe rehabilitation processes according to medical guidelines. However, due to the therapist-patient imbalance, it is neither economical nor feasible for therapists to provide guidance to every patient during recovery sessions. Automated assessment of physical rehabilitation can help with this problem, but accurately quantifying patients' training movements and providing meaningful feedback poses a challenge. In this paper, an Expert-knowledge-based Graph Convolutional approach is proposed to automate the assessment of the quality of physical rehabilitation exercises. This approach utilizes experts' knowledge to improve the spatial feature extraction ability of the Graph Convolutional module and a Gated pooling module for feature aggregation. Additionally, a Transformer module is employed to capture long-range temporal dependencies in the movements. The attention scores and weight matrix obtained through this approach can serve as interpretability tools to help therapists understand the assessment model and assist patients in improving their exercises. The effectiveness of the proposed method is verified on the KIMORE dataset, achieving state-of-the-art performance compared to existing models. Experimental results also illustrate the interpretability of the method in both spatial and temporal dimensions.

Current scenario and challenges of clinical pharmacists to implement pharmaceutical care in DRG/DIP payment hospitals in China: a qualitative interview study.

Purpose: The Diagnosis-Related Group (DRG) or Diagnosis-Intervention Packet (DIP) payment system, now introduced in China, intends to streamline healthcare billing practices. However, its implications for clinical pharmacists, pivotal stakeholders in the healthcare system, remain inadequately explored. This study sought to assess the perceptions, challenges, and roles of clinical pharmacists in China following the introduction of the DRG or DIP payment system. Methods: Qualitative interviews were conducted among a sample of clinical pharmacists. Ten semi-structured interviews were conducted, either online or face to face. Thematic analysis was employed to identify key insights and concerns related to their professional landscape under the DRG or DIP system. Results: Clinical pharmacists exhibited variable awareness levels about the DRG or DIP system. Their roles have undergone shifts, creating a balance between traditional responsibilities and new obligations dictated by the DRG or DIP system. Professional development, particularly concerning health economics and DRG-based or DIP-based patient care, was highlighted as a key need. There were calls for policy support at both healthcare and national levels and a revised, holistic performance assessment system. The demand for more resources, be it in training platforms or personnel, was a recurrent theme. Conclusion: The DRG or DIP system's introduction in China poses both opportunities and challenges for clinical pharmacists. Addressing awareness gaps, offering robust policy support, ensuring adequate resource allocation, and recognizing the evolving role of pharmacists are crucial for harmoniously integrating the DRG or DIP system into the Chinese healthcare paradigm.

Optimal Decision-Making of Closed-Loop Supply Chains in E-Commerce Platform Considering Sales Cooperations under Environmental Effects and WEEE Regulations.

Nowadays, to achieve carbon neutrality, e-commerce platforms participate in the sales and recycling of electrical and electronic products in consideration of waste electrical and electronic equipment (WEEE) regulations and environmental effects. This study builds a Stackelberg game model for an e-commerce closed-loop supply chain (ECLSC) under different sales cooperation modes between a manufacturer of electrical and electronic products and an e-commerce platform. Reverse induction is used to obtain the optimal decision-making and profit of the ECLSC under three sales cooperation modes, considering the influence of environmental effects on optimal decision and objective functions. The results show the following: the sales cooperation mode and environmental cost do not affect the WEEE recovery prices of manufacturers and e-commerce platforms, nor do they affect government subsidy standards for dismantling WEEEs; they are, however, positively correlated with environmental benefits. Furthermore, the wholesale and retail prices of electrical and electronic products under different sales cooperation modes are related to sales cooperation modes and environmental costs. Moreover, the processing fees imposed on the manufacturers are related to the environmental costs of the electrical and electronic products; the thresholds of environmental costs of products for government to levy processing fees are different under different sales cooperation modes. Finally, the environmental cost of products required by the government's levying of processing fees are the lowest under a hybrid model. Generally speaking, under WEEE regulations, governments should levy more processing fees for electrical and electronic products with higher environmental costs. Meanwhile, increased environmental benefits will always increase the profits of supply chain members, but increased environmental costs do not always reduce the profits of supply chain members, and multichannel product sales do not always generate profits for manufacturers.

A Polynesian-specific missense CETP variant alters the lipid profile.

Identifying population-specific genetic variants associated with disease and disease-predisposing traits is important to provide insights into the genetic determinants of health and disease between populations, as well as furthering genomic justice. Various common pan-population polymorphisms at CETP associate with serum lipid profiles and cardiovascular disease. Here, sequencing of CETP identified a missense variant rs1597000001 (p.Pro177Leu) specific to Maori and Pacific people that associates with higher HDL-C and lower LDL-C levels. Each copy of the minor allele associated with higher HDL-C by 0.236 mmol/L and lower LDL-C by 0.133 mmol/L. The rs1597000001 effect on HDL-C is comparable with CETP Mendelian loss-of-function mutations that result in CETP deficiency, consistent with our data, which shows that rs1597000001 lowers CETP activity by 27.9%. This study highlights the potential of population-specific genetic analyses for improving equity in genomics and health outcomes for population groups underrepresented in genomic studies.

Assessment of a novel variation in DHODH gene causing Miller syndrome: The first report in Chinese population.

BACKGROUND: Miller syndrome is a rare type of postaxial acrofacial dysostosis caused by biallelic mutations in the DHODH gene, which is characterized mainly by craniofacial malformations of micrognathia, orofacial clefts, cup-shaped ears, and malar hypoplasia, combined with postaxial limb deformities like the absence of fifth digits. METHODS: In this study, a prenatal case with multiple orofacial-limb abnormities was enrolled, and a thorough clinical and imaging examination was performed. Subsequently, genetic detection with karyotyping, chromosomal microarray analysis (CMA) and whole-exome sequencing (WES) was carried out. In vitro splicing analysis was also conducted to clarify the impact of one novel variant. RESULTS: The affected fetus displayed typical manifestations of Miller syndrome, and WES identified a diagnostic compound heterozygous variation in DHODH, consisting of two variants: exon(1-3)del and c.819 + 5G > A. We conducted a further in vitro validation with minigene system, and the result indicated that the c.819 + 5G > A variant would lead to an exon skipping in mRNA splicing. CONCLUSIONS: These findings provided with the first exonic deletion and first splice site variant in DHODH, which expanded the mutation spectrum of Miller syndrome and offered reliable evidence for genetic counseling to the affected family.

Machine learning approaches for the mortality risk assessment of patients undergoing hemodialysis.

Introduction: Mortality is a major primary endpoint for long-term hemodialysis (HD) patients. The clinical status of HD patients generally relies on longitudinal clinical observations such as monthly laboratory examinations and physical examinations. Methods: A total of 829 HD patients who met the inclusion criteria were analyzed. All patients were tracked from January 2009 to December 2013. Taken together, this study performed full-adjusted-Cox proportional hazards (CoxPH), stepwise-CoxPH, random survival forest (RSF)-CoxPH, and whale optimization algorithm (WOA)-CoxPH model for the all-cause mortality risk assessment in HD patients. The model performance between proposed selections of CoxPH models were evaluated using concordance index. Results: The WOA-CoxPH model obtained the highest concordance index compared with RSF-CoxPH and typical selection CoxPH model. The eight significant parameters obtained from the WOA-CoxPH model, including age, diabetes mellitus (DM), hemoglobin (Hb), albumin, creatinine (Cr), potassium (K), Kt/V, and cardiothoracic ratio, have also showed significant survival difference between low- and high-risk characteristics in single-factor analysis. By integrating the risk characteristics of each single factor, patients who obtained seven or more risk characteristics of eight selected parameters were dichotomized as high-risk subgroup, and remaining is considered as low-risk subgroup. The integrated low- and high-risk subgroup showed greater discrepancy compared with each single risk factor selected by WOA-CoxPH model. Conclusion: The study findings revealed WOA-CoxPH model could provide better risk assessment performance compared with RSF-CoxPH and typical selection CoxPH model in the HD patients. In summary, patients who had seven or more risk characteristics of eight selected parameters were at potentially increased risk of all-cause mortality in HD population.

Carrier Free O2 -Economizer for Photodynamic Therapy Against Hypoxic Tumor by Inhibiting Cell Respiration.

Abnormal tumor metabolism causes the hypoxic microenvironment, which greatly limits the efficacy of photodynamic therapy (PDT). In this work, a strategy of metabolic reprogramming is proposed to economize O2 for enhanced PDT against hypoxic tumors. The carrier-free O2 -economizer (designated as LonCe) is prepared based on the metabolic antitumor drug of Lonidamine (Lon) and the photosensitizer of chlorin e6 (Ce6). By virtue of intermolecular interactions, Lon and Ce6 self-assemble into nanosized LonCe with favorable stability and high drug contents. Compared with Ce6, LonCe exhibits an improved cellular uptake and photodynamic property for tumor treatment. Moreover, LonCe is capable of inhibiting cell metabolism and mitochondrial respiration to remit the tumor hypoxia, which would promote reactive oxygen species (ROS) production and elevate the PDT efficacy on tumor suppression. In vivo experiments indicate that intravenously injected LonCe prefers to accumulate at the tumor site for highly efficient PDT regardless of the hypoxic environment. Besides, the self-delivery LonCe is fabricated without any carriers, which avoids the excipients induced system toxicity and immunogenicity in vivo. This carrier-free nanomedicine with cell respiratory inhibition mechanism would expedite the development and clinical translation of photodynamic nanoplatforms in tumor treatment.

Chinese Consensus Report on Family-Based Helicobacter pylori Infection Control and Management (2021 Edition).

OBJECTIVE: Helicobacter pylori infection is mostly a family-based infectious disease. To facilitate its prevention and management, a national consensus meeting was held to review current evidence and propose strategies for population-wide and family-based H. pylori infection control and management to reduce the related disease burden. METHODS: Fifty-seven experts from 41 major universities and institutions in 20 provinces/regions of mainland China were invited to review evidence and modify statements using Delphi process and grading of recommendations assessment, development and evaluation system. The consensus level was defined as ≥80% for agreement on the proposed statements. RESULTS: Experts discussed and modified the original 23 statements on family-based H. pylori infection transmission, control and management, and reached consensus on 16 statements. The final report consists of three parts: (1) H. pylori infection and transmission among family members, (2) prevention and management of H. pylori infection in children and elderly people within households, and (3) strategies for prevention and management of H. pylori infection for family members. In addition to the 'test-and-treat' and 'screen-and-treat' strategies, this consensus also introduced a novel third 'family-based H. pylori infection control and management' strategy to prevent its intrafamilial transmission and development of related diseases. CONCLUSION: H. pylori is transmissible from person to person, and among family members. A family-based H. pylori prevention and eradication strategy would be a suitable approach to prevent its intra-familial transmission and related diseases. The notion and practice would be beneficial not only for Chinese residents but also valuable as a reference for other highly infected areas.

Plasma membrane targeted photodynamic O2 economizer for hypoxic tumor therapy.

The development of photodynamic therapy (PDT) is severely limited by short half-life of singlet oxygen (1O2) and the hypoxic microenvironment. In this work, a plasma membrane targeted photodynamic O2 economizer (designated as P-POE) is developed to improve the subcellular delivery of photosensitizers and alleviate the tumor hypoxia for enhanced PDT effect. After self-assembly into nanomicelles, P-POE has a relatively high stability and a favorable photochemical performance, which are conducive to boosting the 1O2 production. Besides, the plasma membrane anchoring of P-POE contributes to enhancing the preferential retention and cellular accumulation of photosensitizers on tumor tissues and cells. More importantly, P-POE-induced mitochondrial respiratory depression is demonstrated to reduce the O2 consumption of tumor cells to relieve the hypoxia. Consequently, P-POE still exhibits a robust PDT effect against hypoxic tumors, which greatly inhibits the proliferation of breast cancer with low adverse reactions. This innovative combination of subcellular targeting and hypoxic alleviation would advance the development of individualized drug delivery systems for photodynamic therapy against hypoxic tumors.

Mitochondria Targeted O2 Economizer to Alleviate Tumor Hypoxia for Enhanced Photodynamic Therapy.

Photodynamic therapy (PDT) often suffers from the exacerbated tumor hypoxia and the heterogeneous distribution of photosensitizers, leading to an inefficient ROS productivity and availability. In this work, a mitochondria targeted O2 economizer (designated as Mito-OxE) is developed to improve PDT efficiency by alleviating tumor hypoxia and enhancing the subcellular localization of photosensitizers. Specifically, the photosensitizer of protoporphyrin IX (PpIX) is modified with the hydrophilic polyethylene glycol and the lipophilic cation of triphenylphosphine (TPP) to fabricate the biocompatible mitochondria targeted photosensitizers (designated as Mito-PSs). And Mito-OxE is prepared by using Mito-PSs to load the mitochondrial oxidative phosphorylation inhibitors of atovaquone (ATO). Benefiting from the targeting capability of TPP, Mito-OxE can selectively accumulate in mitochondria after cellular uptake. Subsequently, the mitochondrial respiration would be suppressed to with the participation of ATO, resulting in a local hypoxia mitigation for enhanced PDT. Compared with Mito-PSs, Mito-OxE maximizes the therapeutic effect against hypoxic tumors under light irradiation. This design of mitochondria targeted O2 economizer would advance the development of targeted drug delivery system for effective PDT regardless of hypoxic microenvironment.

A porphysome-based photodynamic O2 economizer for hypoxic tumor treatment by inhibiting mitochondrial respiration.

A porphysome-based photodynamic O2 economizer (P-PAT) is prepared for hypoxic tumor therapy. The self-assembled porphyrin bilayers of P-PAT possess high loading capacity to atovaquone (ATO) (nearly 70%), which could restrain mitochondrial respiration to relieve hypoxia and enhance photodynamic therapy.

[Research advances in assessment tools for feeding problems in children].

As one of the most important non-nutritional factors associated with children's growth and development, feeding problems in children are getting more and more attention from medical professionals and guardians. The evaluation of feeding problems has developed from the single-factor and descriptive research in the past to the multi-factor and analytical research at present, and thus a good quantitative analysis system is increasingly important for researchers. However, the development of localized quantitative analysis tools remains a weak link in this field. Therefore, it is a research hotspot to develop child feeding assessment scales and questionnaires with high reliability, validity, and operability in combination with China's cultural background and eating habits and provide effective assessment tools for feeding problems in Chinese children. Through classification based on research mode and screening, this article reviews the research findings in the field of child feeding, so as to provide a basis for future research.

Self-Delivery Nanomedicine for O2-Economized Photodynamic Tumor Therapy.

Tumor hypoxia is the Achilles heel of oxygen-dependent photodynamic therapy (PDT), and tremendous challenges are confronted to reverse the tumor hypoxia. In this work, an oxidative phosphorylation inhibitor of atovaquone (ATO) and a photosensitizer of chlorine e6 (Ce6)-based self-delivery nanomedicine (designated as ACSN) were prepared via π-π stacking and hydrophobic interaction for O2-economized PDT against hypoxic tumors. Specifically, carrier-free ACSN exhibited an extremely high drug loading rate and avoided the excipient-induced systemic toxicity. Moreover, ACSN not only dramatically improved the solubility and stability of ATO and Ce6 but also enhanced the cellular internalization and intratumoral permeability. Abundant investigations confirmed that ACSN effectively suppressed the oxygen consumption to reverse the tumor hypoxia by inhibiting mitochondrial respiration. Benefiting from the synergistic mechanism, an enhanced PDT effect of ACSN was observed on the inhibition of tumor growth. This self-delivery system for oxygen-economized PDT might be a potential appealing clinical strategy for tumor eradication.

Region-of-Interest based sparse feature learning method for Alzheimer's disease identification.

BACKGROUND AND OBJECTIVE: In recent years, some clinical parameters, such as the volume of gray matter (GM) and cortical thickness, have been used as anatomical features to identify Alzheimer's disease (AD) from Healthy Controls (HC) in some feature-based machine learning methods. However, fewer image-based feature parameters have been proposed, which are equivalent to these clinical parameters, to describe the atrophy of regions-of-interest (ROIs) of the brain. In this study, we aim to extract effective image-based feature parameters to improve the diagnostic performance of AD with magnetic resonance imaging (MRI) data. METHODS: A new subspace-based sparse feature learning method is proposed, which builds a union-of-subspace representation model to realize feature extraction and disease identification. Specifically, the proposed method estimates feature dimensions reasonably, at the same time, it protects local features for the specified ROIs of the brain, and realizes image-based feature extraction and classification automatically instead of computing the volume of GM or cortical thickness preliminarily. RESULTS: Experimental results illustrate the effectiveness and robustness of the proposed method on feature extraction and classification, which are based on the sampled clinical dataset from Peking University Third Hospital of China and the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. The extracted image-based feature parameters describe the atrophy of ROIs of the brain well as clinical parameters but show better performance in AD identification than clinical parameters. Based on them, the important ROIs for AD identification can be identified even for correlated variables. CONCLUSION: The extracted features and the proposed identification parameters show high correlation with the volume of GM and the clinical mini-mental state examination (MMSE) score respectively. The proposed method will be useful in denoting the changes of cerebral pathology and cognitive function in AD patients.

A Scientometric Review of Resource Recycling Industry.

With rapid economic development and urbanization, a large number of primary resources are consumed and accumulate in society as recyclable resource, which causes great pressure on the environment. The development of the resource recycling industry (RRI) can reduce environmental impacts and achieve sustainable development and green growth. Scholars are paying more attention to the resource recycling industry (RRI), and the related literature continues to increase. There are over 7041 publications covering RRI in the Web of Science database from 1996 to 2018. This paper analyzes the time distribution characteristics of the literature and the status of the scientific research cooperation network using the visualization analysis software CiteSpace. The number of documents increased from 94 in 1996 to a peak of 963 in 2018. There is no relatively stable core author group. The number of papers published by "Chinese Acad Sci" ranks first among all research institutions. Document co-citation analysis and burst detection are adopted to assess the status and emerging trends in the RRI research domain. A publication by M.C. Monte on waste management is the most cited paper. Additionally, "green and sustainable and technology" and "science and technology-other topics" are the latest emerging subject categories in RRI research. Furthermore, "e-waste", "reverse logistics" and "lean manufacturing" are emerging research trends for RRI, and "carbon emissions", "policy", "demolition waste", "supply chain management" and "compressive strength" have become hot topics. These findings may provide inspiration for scholars to search for new research directions and ideas.

Decision Theory-Based COI-SNP Tagging Approach for 126 Scombriformes Species Tagging.

The mitochondrial gene cytochrome c oxidase I (COI) is commonly used for DNA barcoding in animals. However, most of the COI barcode nucleotides are conserved and sequences longer than about 650 base pairs increase the computational burden for species identification. To solve this problem, we propose a decision theory-based COI SNP tagging (DCST) approach that focuses on the discrimination of species using single nucleotide polymorphisms (SNPs) as the variable nucleotides of the sequences of a group of species. Using the example of 126 teleost mackerel fish species (order: Scombriformes), we identified 281 SNPs by alignment and trimming of their COI sequences. After decision rule making, 49 SNPs in 126 fish species were determined using the scoring system of the DCST approach. These COI-SNP barcodes were finally transformed into one-dimensional barcode images. Our proposed DCST approach simplifies the computational complexity and identifies the most effective and fewest SNPs to resolve or discriminate species for species tagging.

Cardiovascular health in urban Chinese children and adolescents.

INTRODUCTION: Cardiovascular diseases remain the leading cause of death and disease burden in China and worldwide. We aimed to evaluate the status of cardiovascular health among urban Chinese children and adolescents. METHODS: We conducted a cross-sectional study comprising 12,618 children and adolescents aged 6-18 years, who were recruited from Chinese urban areas during 2013-2015. The poor, intermediate, and ideal levels of 7 cardiovascular health metrics, including smoking, body mass index, dietary intake, physical activity, blood pressure, blood glucose, and total cholesterol were defined according to revised American Heart Association criteria. RESULTS: Ideal smoking status was the most prevalent health component (overall, 90.7%; males, 86.3% and females, 95.4%), whereas ideal health diet score (overall, 8.7%; males, 9.1% and females, 8.3%) was the least prevalent among urban Chinese children and adolescents. The majority (overall, 84.9%; males, 82.6% and females, 87.4%) of participants had 3-5 ideal metrics. The overall prevalence of ideal cardiovascular health (i.e. meeting all 7 ideal components) was extremely low (overall, 0.5%; males, 0.5% and females, 0.4%). CONCLUSIONS: The prevalence of ideal cardiovascular health in urban Chinese children and adolescents is extremely low, particularly for physical activity and healthy dietary intake. Effective public health interventions are required to improve cardiovascular health in children and adolescents to reduce future cardiovascular risk. Key messages Ideal health diet score was the least prevalent health component among urban Chinese children and adolescents The prevalence of ideal cardiovascular health in urban Chinese children and adolescents was extremely low Effective public health interventions are required to improve cardiovascular health in children and adolescents to reduce future cardiovascular risk.

Multiple-Criteria Decision Analysis-Based Multifactor Dimensionality Reduction for Detecting Gene-Gene Interactions.

Gene-gene interactions (GGIs) are important markers for determining susceptibility to a disease. Multifactor dimensionality reduction (MDR) is a popular algorithm for detecting GGIs and primarily adopts the correct classification rate (CCR) to assess the quality of a GGI. However, CCR measurement alone may not successfully detect certain GGIs because of potential model preferences and disease complexities. In this study, multiple-criteria decision analysis (MCDA) based on MDR was named MCDA-MDR and proposed for detecting GGIs. MCDA facilitates MDR to simultaneously adopt multiple measures within the two-way contingency table of MDR to assess GGIs; the CCR and rule utility measure were employed. Cross-validation consistency was adopted to determine the most favorable GGIs among the Pareto sets. Simulation studies were conducted to compare the detection success rates of the MDR-only-based measure and MCDA-MDR, revealing that MCDA-MDR had superior detection success rates. The Wellcome Trust Case Control Consortium dataset was analyzed using MCDA-MDR to detect GGIs associated with coronary artery disease, and MCDA-MDR successfully detected numerous significant GGIs (p < 0.001). MCDA-MDR performance assessment revealed that the applied MCDA successfully enhanced the GGI detection success rate of the MDR-based method compared with MDR alone.

Decision Tree Algorithm-Generated Single-Nucleotide Polymorphism Barcodes of rbcL Genes for 38 Brassicaceae Species Tagging.

DNA barcode sequences are accumulating in large data sets. A barcode is generally a sequence larger than 1000 base pairs and generates a computational burden. Although the DNA barcode was originally envisioned as straightforward species tags, the identification usage of barcode sequences is rarely emphasized currently. Single-nucleotide polymorphism (SNP) association studies provide us an idea that the SNPs may be the ideal target of feature selection to discriminate between different species. We hypothesize that SNP-based barcodes may be more effective than the full length of DNA barcode sequences for species discrimination. To address this issue, we tested a ribulose diphosphate carboxylase (rbcL) SNP barcoding (RSB) strategy using a decision tree algorithm. After alignment and trimming, 31 SNPs were discovered in the rbcL sequences from 38 Brassicaceae plant species. In the decision tree construction, these SNPs were computed to set up the decision rule to assign the sequences into 2 groups level by level. After algorithm processing, 37 nodes and 31 loci were required for discriminating 38 species. Finally, the sequence tags consisting of 31 rbcL SNP barcodes were identified for discriminating 38 Brassicaceae species based on the decision tree-selected SNP pattern using RSB method. Taken together, this study provides the rational that the SNP aspect of DNA barcode for rbcL gene is a useful and effective sequence for tagging 38 Brassicaceae species.

Assessment of three risk evaluation systems for patients aged ≥70 in East China: performance of SinoSCORE, EuroSCORE II and the STS risk evaluation system.

OBJECTIVES: To assess and compare the predictive ability of three risk evaluation systems (SinoSCORE, EuroSCORE II and the STS risk evaluation system) in patients aged ≥70, and who underwent coronary artery bypass grafting (CABG) in East China. METHODS: Three risk evaluation systems were applied to 1,946 consecutive patients who underwent isolated CABG from January 2004 to September 2016 in two hospitals. Patients were divided into two subsets according to their age: elderly group (age ≥70) with a younger group (age <70) used for comparison. The outcome of interest in this study was in-hospital mortality. The entire cohort and subsets of patients were analyzed. The calibration and discrimination in total and in subsets were assessed by the Hosmer-Lemeshow and the C statistics respectively. RESULTS: Institutional overall mortality was 2.52%. The expected mortality rates of SinoSCORE, EuroSCORE II and the STS risk evaluation system were 0.78(0.64)%, 1.43(1.14)% and 0.78(0.77)%, respectively. SinoSCORE achieved the best discrimination (the area under the receiver operating characteristic curve (AUC) = 0.829), followed by the STS risk evaluation system (AUC = 0.790) and EuroSCORE II (AUC = 0.769) in the entire cohort. In the elderly group, the observed mortality rate was 4.82% while it was 1.38% in the younger group. SinoSCORE (AUC = .829) also achieved the best discrimination in the elderly group, followed by the STS risk evaluation system (AUC = .730) and EuroSCORE II (AUC = 0.640) while all three risk evaluation systems all had good performances in the younger group. SinoSCORE, EuroSCORE II and the STS risk evaluation system all achieved positive calibrations in the entire cohort and subsets. CONCLUSION: The performance of the three risk evaluation systems was not ideal in the entire cohort. In the elderly group, SinoSCORE appeared to achieve better predictive efficiency than EuroSCORE II and the STS risk evaluation system.