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

Objective:To analyze the current status of the research in two emerging fields-digital health and digital medicine,and the distinctions and interconnections between them,and to explore critical cognitionfor benign development of this field.Methods:Based on bibliometric method,this study analyzed 1 747 papers published in two Q1 journals categorized under"medical informatics"in Chinese Academy of Sciences Journal Citation Reports between January 1st,2019,and June 30th,2024.A biclustering analysis of highly cited and source article was conducted using a"co-cited literature clustering and all articles citing this cluster"approach.Results:In 1 747 literature,a total of 28 classic high cited articles in digital medicinejournals and digital health journals were screened out afterthe literatures of irrelevant citations were deleted,and then,they were further analyzed.The clustering performancesof similar clusters for high cited articles of two kinds of journals were similar,and the difference of intra-cluster similarity(Isim)between them was not statistically significant(P>0.05).The inter-cluster similarity(Esim)of digital health journal was 0.0480,which was significantly higher than that of digital health journal,and the difference of that between them wasstatistically significant(t=-3.925,P<0.05).The clustering result of digital medicine was better,which whole research direction could be divided into deep learning-based ophthalmic medical image analysis,image recognition with artificial intelligence(AI),algorithm model of using AI,reporting standard and assessment method of digital medicine and scientific research by using AI.However,the contents of high cited literatures of digital health field had a lot of overlap with digital medicine field,and various clusters of literature have inconsistent themesafter these literatures were clustered.Conclusions:Research of digital medicine is tending towards two primary directions:specific application of AI,and theimprovement of digital medical standards and processes.Meanwhile,the articles and literatures with high quality in digital health still cannot divorce the medical field,and the discipline system still is immature.

Objective:To analyze the current status of the research in two emerging fields-digital health and digital medicine,and the distinctions and interconnections between them,and to explore critical cognitionfor benign development of this field.Methods:Based on bibliometric method,this study analyzed 1 747 papers published in two Q1 journals categorized under"medical informatics"in Chinese Academy of Sciences Journal Citation Reports between January 1st,2019,and June 30th,2024.A biclustering analysis of highly cited and source article was conducted using a"co-cited literature clustering and all articles citing this cluster"approach.Results:In 1 747 literature,a total of 28 classic high cited articles in digital medicinejournals and digital health journals were screened out afterthe literatures of irrelevant citations were deleted,and then,they were further analyzed.The clustering performancesof similar clusters for high cited articles of two kinds of journals were similar,and the difference of intra-cluster similarity(Isim)between them was not statistically significant(P>0.05).The inter-cluster similarity(Esim)of digital health journal was 0.0480,which was significantly higher than that of digital health journal,and the difference of that between them wasstatistically significant(t=-3.925,P<0.05).The clustering result of digital medicine was better,which whole research direction could be divided into deep learning-based ophthalmic medical image analysis,image recognition with artificial intelligence(AI),algorithm model of using AI,reporting standard and assessment method of digital medicine and scientific research by using AI.However,the contents of high cited literatures of digital health field had a lot of overlap with digital medicine field,and various clusters of literature have inconsistent themesafter these literatures were clustered.Conclusions:Research of digital medicine is tending towards two primary directions:specific application of AI,and theimprovement of digital medical standards and processes.Meanwhile,the articles and literatures with high quality in digital health still cannot divorce the medical field,and the discipline system still is immature.

The aim of this study is to establish a simple and accurate method for vaccine immune e-valuation of porcine pseudorabies virus.In this research,PRV-gD recombinant protein was ex-pressed from mammalian cell HEK-293F as coating antigen,and then the reaction conditions of gD-iELISA were optimized according to checkerboard titration method.The gD-iELISA was used to detect the antibody levels of 211 clinical pig serum samples and the consistency with the neu-tralizing antibody levels wasanalyzed.The results showed that the antigen coating concentration was 0.90 mg/L;the serum to be detected was diluted 1∶100 and incubated at 37 ℃ for 30 min;goat anti-pig IgG-HRP antibody was diluted 1∶55 000 and incubated at 37 ℃ for 30 min;TMB sub-strate was developed at 37 ℃ for 20 min.The method could detect 1∶6 400 diluted PRV positive serum.The results of CSFV,PRRSV,PCV-2,PEDV and FMDV positive sera were all negative by gD-iELISA,and there was no cross-reaction between the method and the above positive sera.The coincidence rate of gD-iELISA and commercial kits was 95.26％,and the intra-and inter-batch co-efficients of variation were both less than 10％.Correlation analysis showed that the correlation coefficient(r)between gD antibody level and neutralizing antibody level was significantly greater than that of gB antibody level,and the gD antibody level had a good linear relationship with the neutralizing antibody level.The results indicated that gD-iELISA was more suitable for vaccine im-mune evaluation of PRV than gB-iELISA.Therefore,the method will have a good prospect of ap-plication in the immunization control of the PRV.

Objective·To investigate the imaging features of computed tomography(CT)and magnetic resonance imaging(MRI)in the patients with Kimura disease(KD)in the head and neck.Methods·Sixty-four cases of KD in the head and neck comfirmed by histopathology were retrospectively collected from 2009 to 2023 in Shanghai Ninth People's Hospital,Shanghai Jiao Tong University School of Medicine.All patients completed CT and/or MRI enhancement imaging before surgery.Clinical and imaging characteristics were collected,recorded and analyzed,including age,gender,peripheral blood eosinophilic ratio,serum IgE level,the lesion location,shape,size,CT density and degree of enhancement,MRI signal intensity and degree of enhancement,apparent diffusion coefficient(ADC),time-signal intensity curve(TIC)patterns,wash-in rate,and time to peak(TTP).Results·The average age of the 64 KD patients was(40±19)years,and 92.2%were males.A total of 73.5%of the patients showed an elevated ratio of peripheral blood eosinophil,and all 10 tested patients exhibited increased serum IgE levels.There were 82 extranodal(subcutaneous and glandular)lesions and 144 lymph node lesions detected by CT and MRI.Among the extranodal lesions,80.5%were subcutaneous or glandular patchy lesions with unclear boundaries,and the rest were nodular lesions with clear boundaries.All lesions exhibited isodensity on CT scans and showed isointensity on T1-weighted imaging(T1WI)and hyperintensity on T2-weighted imaging(T2WI)in MRI.Most extranodal lesions tended to show heterogeneous enhancement,while most lymph node lesions showed homogeneous enhancement.The median ADCs of the extranodal lesions and the lymph node lesions were 1.04×10-3 mm2/s and 0.67×10-3 mm2/s,respectively,which were significantly different(P=0.000).The dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)results showed that the TIC patterns of extranodal lesions were predominantly type Ⅰ andⅡ,accounting for 57.5%and 42.5%,respectively;while the TIC patterns of lymph node lesions were predominantly type Ⅱ(96.6%).The difference in the TTP and the wash-in rate between the extranodal lesions and the lymph node lesions were both statistically significant(P=0.000).Conclusion·Extranodal lesions and lymph node lesions of KD both show isodensity on CT,and isointensity on T1WI and hyperintensity on T2WI in MRI.Extranodal lesions often show high ADC,TIC type Ⅰ or Ⅱ,and mostly heterogeneous enhancement;lymph node lesions often show low ADC,TIC type Ⅱ,and mostly homogenous enhancement.

Computational fluid dynamics (CFD) is an emerging technology applied in the field of cardiovascular medicine, which can obtain hemodynamic data by simulating the blood flow in the patient′s heart for cardiac function assessment and disease diagnosis. Left ventricular function plays a key role in the occurrence and development of cardiomyopathies and coronary disease. CFD can reconstruct the left ventricular anatomic structures of patients to clarify pathophysiologic mechanisms and analyze hemodynamic parameters to evaluate left ventricular function, verify surgical efficacy, and guide surgical strategy, which has a positive effect on achieving early diagnosis and reducing mortality from cardiomyopathies and coronary disease. At present, there are still technical limitations in the large-scale clinical application of CFD, and various solutions are being developed and tested, and further improvement and refinement are needed.

Aortic aneurysm and dissection are critical cardiovascular diseases that threaten human life and health seriously. No pharmacological treatment can effectively prevent disease progression. The imbalance of aortic wall cells and non-cellular components leads to structural or functional degeneration of the aorta, which is a prerequisite for disease occurrence. As the important non-cellular component, extracellular matrix (ECM) is crucial to maintain the aortic structure, function, and homeostasis. Abnormal production of elastin and collagen, destruction of cross-linking between elastic fibers and collagen fibers, and the imbalance of metalloproteinase and inhibitors leads to excessive degradation of ECM proteins, all of which have destroyed the structure and function of aorta. It will provide more ideas for disease prevention and treatment by learning ECM proteins and their metabolic mechanism. Here, we focus on the ECM proteins that have been reported to be involved in aortic aneurysm and dissection, and discuss the regulatory mechanism of metalloproteinase and inhibitors.

Objective To evaluate the value of rs61330082 and rs4730153 polymorphisms of Visfatin locus for the diagnosis of type 2 diabetes mellitus(T2DM)in a high-risk population.Methods SNPscanTM high-throughput single nucleotide polymorphism typing technique was used to genotype Visfatin gene loci rs61330082 and rs4730153 in 346 T2DM patients(T2DM group)and 1426 normal controls(NC group).Logistic regression analysis was used to analyze T2DM risk factors.ROC curves were used to analyze the optimal cut-off values of Visfatin gene rs61330082 and rs4730153 for the diagnosis of T2DM.Results The proportion of women,age,obesity,smoking,hypertension,FPG,HbA1c and TG were higher in T2DM group than those in NC group(P<0.01)and HDL-C was lower than in NC group(P<0.01).The frequency of G allele and GG genotype was higher in T2DM group compared with NC group(P<0.05).Logistic regression analysis showed that age,female,obesity,hypertension,TG,and GG genotype at rs4730153 locus were risk factors for T2DM,HDL-C was a protective factor for T2DM.The area under the ROC curve of GG genotype at Visfatin rs4730153 mutation for diagnosis of T2DM was 0.668 and the optimal cut-off point for predicting T2DM was 20.04%,with sensitivity 60.1%and specificity 66.1%,respectively.Conclusion The GG genotype of Visfatin gene rs4730153 locus is associated with the risk of T2DM and can beused as a candidate gene for predicting phenotype of T2DM.

Objective:To explore the impact of treatment duration with human urinary kallidinogenase (HUK) on the efficacy and safety of acute ischemic stroke (AIS).Methods:In this subgroup analysis of RESK study, a total of 990 AIS patients recruited from 65 centers in China between August 2015 and June 2020 were included and divided into short medication group (HUK for 8 days, n=185) or long medication group (HUK for 15 days or 21 days, n=805). The proportions of patients with modified Rankin Scale (mRS) score of 0, 0-1, 0-2 at 90 days, National Institutes of Health Stroke Scale (NIHSS) score change from baseline to 22 days, the proportions of patients with Barthel index (BI)≥95 at 90 days, and the incidences of adverse events were analyzed. Comparisons between groups were conducted using chi-square test, single factor and multivariate Logistic regression analysis, etc. Results:Multivariate regression analysis showed that the proportions of patients with 90-day mRS score of 0-2 [74.1% (137/185) vs 75.0% (604/805); OR=1.047, 95% CI 0.676-1.620, P=0.838] and 22-day NIHSS score change from baseline (4.60±2.00 vs 4.26±2.80; OR=-0.390, 95% CI -1.125-0.344, P=0.297) showed no statistically significant difference between the short medication and long medication groups; the proportions of patients with 90-day mRS score of 0-1 [48.1% (89/185) vs 59.1% (476/805); OR=0.674, 95%CI 0.463-0.983, P=0.041] and 90-day BI≥95 [43.6% (79/181) vs 55.1% (442/802); OR=0.614, 95%CI 0.420-0.897, P=0.012] were significantly lower in the short medication group than in the long medication group. There was no statistically significant difference in the incidences of adverse events between these 2 groups. Conclusions:In AIS patients, consecutive 8-day dosing of HUK improved immediate (22-day NIHSS score) and long-term outcome (90-day mRS score 0-2) and was safely tolerated. When applicable, extended duration of HUK could improve long-term disability-free rate (90-day mRS score 0-1) and quality of life (90-day BI) without increasing the risk of adverse events.

Computational fluid dynamics (CFD) is an emerging technology applied in the field of cardiovascular medicine, which can obtain hemodynamic data by simulating the blood flow in the patient′s heart for cardiac function assessment and disease diagnosis. Left ventricular function plays a key role in the occurrence and development of cardiomyopathies and coronary disease. CFD can reconstruct the left ventricular anatomic structures of patients to clarify pathophysiologic mechanisms and analyze hemodynamic parameters to evaluate left ventricular function, verify surgical efficacy, and guide surgical strategy, which has a positive effect on achieving early diagnosis and reducing mortality from cardiomyopathies and coronary disease. At present, there are still technical limitations in the large-scale clinical application of CFD, and various solutions are being developed and tested, and further improvement and refinement are needed.