Liver cirrhosis is a common chronic progressive liver disease， and such patients often have coagulation disorders， which may lead to thrombotic and hemorrhagic events. While traditional anticoagulant therapies have various limitations， the emergence of novel oral anticoagulants （NOAC） provides new options for anticoagulation treatment in patients with liver cirrhosis. This article comprehensively reviews the application of NOAC in patients with liver cirrhosis， discusses their advantages and potential risks， analyzes their pharmacokinetic and pharmacodynamic characteristics， and evaluates their efficacy and safety in the prevention and treatment of cirrhosis-associated thrombosis based on clinical evidence， in order to provide a reference for clinical decision-making.

Objective:To investigate the value of an MRI and digital pathology images based omics nomogram for the prediction of recurrence risk in soft tissue sarcoma (STS).Methods:This was a retrospective cohort study. From January 2016 to March 2021, 192 patients with STS confirmed by pathology in the Affiliated Hospital of Qingdao University were enrolled, among which 112 patients in the Laoshan campus were enrolled as training set, and 80 patients in the Shinan campus were enrolled as validation set. The patients were divided into recurrence group ( n=87) and no recurrence group ( n=105) during follow-up. The clinical and MRI features of patients were collected. The radiomics features based on fat saturated T 2WI images and pathomics features based on digital pathology images of the lesions were extracted respectively. The clinical model, radiomics model, pathomics model, radiomics-pathomics combined model, and omics nomogram which combined the optimal prediction model and the clinical model were established by multivariate Cox regression analysis. The concordance index (C index) and time-dependent area under the receiver operating characteristic curve (t-AUC) were used to evaluate the performance of each model in predicting STS postoperative recurrence. The DeLong test was used for comparison of t-AUC between every two models. The X-tile software was used to determine the cut-off value of the omics nomogram, then the patients were divided into low risk ( n=106), medium risk ( n=64), and high risk ( n=22) groups. Three groups′ cumulative recurrence-free survival (RFS) rates were calculated and compared by the Kaplan-Meier survival curve and log-rank test. Results:The performance of the radiomics-pathomics combined model was superior to the radiomics model and pathomics model, with C index of 0.727 (95% CI 0.632-0.823) and medium t-AUC value of 0.737 (95% CI0.584-0.891) in the validation set. The omics nomogram was established by combining the clinical model and the radiomics-pathomics combined model, with C index of 0.763 (95% CI 0.685-0.842) and medium t-AUC value of 0.783 (95% CI0.639-0.927) in the validation set. The t-AUC value of omics nomogram was significantly higher than that of clinical model, TNM model, radiomics model, and pathomics model in the validation set ( Z=3.33, 2.18, 2.08, 2.72, P=0.001, 0.029, 0.037, 0.007). There was no statistical difference in t-AUC between the omics nomogram and radiomics-pathomics combined model ( Z=0.70, P=0.487). In the validation set, the 1-year RFS rates of STS patients in the low, medium, and high recurrence risk groups were 92.0% (95% CI 81.5%-100%), 55.9% (95% CI 40.8%-76.6%), and 37.5% (95% CI 15.3%-91.7%). In the training and validation sets, there were statistically significant in cumulative RFS rates among the low, medium, and high groups of STS patients (training set χ2=73.90, P<0.001; validation set χ2=18.70, P<0.001). Conclusion:The omics nomogram based on MRI and digital pathology images has favorable performance for the prediction of STS recurrence risk.

Subthreshold depression belongs to the category of psychological sub-health.Because it does not meet the diagnostic criteria of depression,it may cause misdiagnosis,missed diagnosis,excessive medical treatment,violation of patient autonomy,poor effect or unclear adverse reactions.The ethical problems in clin-ical diagnosis and treatment are worthy of attention.This article aimed to explore the ethical issues that may exist in the clinical diagnosis and treatment of subthreshold depression,a sub-depression state,and propose so-lutions.

Objective:To explore the central venous catheter maintenance compliance among nurses in Class Ⅱ and Ⅲ hospitals in Hunan Province.Methods:From January to March 2022, 297 nurses from 22 Class Ⅱ and Ⅲ hospitals in Hunan Province were selected as the research subject by convenience sampling. Nurses were surveyed using the self-made Central Venous Catheter Maintenance Compliance Questionnaire. Multiple linear regression was used to analyze the influencing factors of nurse compliance with central venous catheter maintenance, the items of the Central Venous Catheter Maintenance Compliance Questionnaire were analyzed.Results:A total of 297 questionnaires were distributed, and 268 valid questionnaires were collected, with an effective response rate of 90.24%. The hospital level, specialized training in intravenous therapy, and age were the influencing factors on the compliance of nurses with central venous catheter maintenance. Analyzing specific items, only 34.3% (92/268) of nurses correctly executed the item "alcohol cotton pads were recommended", and only 66.4% (178/268) of nurses correctly performed the item "sterile gauze dressings should be replaced at least every two days".Conclusions:There is a certain gap in the central venous catheter maintenance compliance among nurses at all levels of hospitals, and there is a need to improve compliance in disinfection of infusion joints and replacement of sterile gauze dressings. We should strengthen the training of specialist nurses, especially the training of nurses in ClassⅡ hospitals on specialized skills related to intravenous therapy.

Objective Exploring the clinical application value of long chain non-coding RNA(lncRNA)H19 in peripheral blood mononuclear cells(PBMCs)in type 2 diabetes mellitus(T2DM)patients with osteoporosis(OP).Methods A total of 176 patients with T2DM admitted to the Department of Endocrinology of the First People's Hospital of Lianyungang City from December 2022 to June 2023 were selected.They were divided into OP group(n=100)and simple T2DM group(n=76)according to the results of bone mineral density(BMD)determination by dual-energy X-ray.General data and biochemical indicators were compared between the two groups.The correlation between lncRNA H19 and other clinical indicators was analyzed by Spearman correlation analysis and the influencing factors for T2DM with OP were analyzed by logistic regression.Receiver operating characteristic(ROC)curve was used to evaluate the diagnostic value of lncRNA H19 in T2DM with OP.Results Compared with T2DM group,the proportion of females,age,HbA1c,TC and TGF-β1 were higher(P<0.05),while BMI,SUA,BMD and lncRNA H19 were lower in OP group(P<0.05).Spearman correlation analysis showed that lncRNA H19 expression level was positively correlated with BMI,SUA and BMD(P<0.05),and negatively correlated with age,HbA1c and TGF-β1(P<0.05).Logistic regression analysis showed that age,BMI,TC,TGF-β1 and lncRNA H19 were the influencing factors for T2DM combined with OP(P<0.05).ROC curve analysis showed that the AUC of lncRNA H19 in the diagnosis of T2DM with OP was 0.839,the sensitivity was 76.3%,and the specificity was 86.0%.Multiple linear regression analysis showed that age,TGF-β1 and OP were the influencing factors for lncRNA H19(P<0.05).Conclusion LncRNA H19 expression decreased in PBMCs in patients with T2DM with OP,which may participate in the occurrence and development of T2DM with OP through glucose metabolism and lncRNA H19/TGF-β1 pathway.

Objective:To observe the clinical efficacy of autologous platelet rich gel (APG) in the treatment of type 2 diabetic foot (DF) patients and the effect of APG on the expression of metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) in peripheral blood mononuclear cells (PBMCs).Methods:A total of 62 patients with DF admitted to the Affiliated Hospital of Kangda College of Nanjing Medical University from February 2021 to May 2022 were randomly divided into a control group (30 cases) and an observation group (32 cases) using a random number table method. The control group received ultrasound debridement and dressing change treatment, while the observation group received ultrasound debridement combined with APG treatment. After 6 weeks of treatment, the effective rate, transcutaneous oxygen partial pressure (TcPO 2), and serum tumor necrosis factor- α (TNF-α), interleukin-6 (IL-6), vascular endothelial growth factor (VEGF), hypoxia inducible factor α (HIF-1 α)and the level of MALAT1 expression in PBMCs of the two groups of patients were observed. The Pearson correlation analysis was used to investigate the relationship between the expression change of MALAT (△ MALAT1) and the total effective rate of treatment. Results:The total effective rate of the observation group was higher than that of the control group [93.75%(30/32) vs 73.33%(22/30), P<0.05]. After treatment, the systolic blood pressure (SBP), diastolic blood pressure (DBP), cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), fasting blood glucose (FPG), glycosylated hemoglobin (HbA 1c), urinary microalbumin/creatinine (UACR), uric acid (UA), white blood cells (WBC), TNF- α and IL-6 of both groups had decreased compared to before; HIF-1 α, VEGF and MALAT1 increased compared to before treatment (all P<0.05); After treatment, there was a statistically significant difference in UA, HIF-1α, VEGF, and MALAT1 between the observation group and the control group (all P<0.05). Pearson correlation analysis showed that Δ MALAT1 in DF patients was negatively correlated with TNF -α ( r=-0.61, P=0.02), IL-6 ( r=-0.52, P=0.04), WBC ( r=-0.53, P=0.03), and positively correlated with VEGF ( r=0.58, P=0.03) and HIF-1α ( r=0.54, P=0.03). The total effective rate of DF treatment was higher in the high change group of△ MALAT [88.37%(38/43) vs 73.68%(14/19), P<0.05]. There was no statistically significant difference in the incidence of adverse reactions between the two groups ( P>0.05). Conclusions:APG can significantly upregulate the expression of MALAT, improve wound tissue blood perfusion, wound angiogenesis, and inflammatory response, promote ulcer healing, and changes in MALAT expression can help determine the prognosis of DF.

Objective:To explore the effect of healthcare failure mode and effect analysis (HFMEA) management mode on perioperative nursing quality of cancer patients at arm infusion port.Methods:Using the convenient sampling, 68 cancer patients with arm infusion port in Hunan Cancer Hospital from January to October 2020 were selected as the control group, and 84 cancer patients with arm infusion port from November 2020 to August 2021 were selected as the intervention group. The control group followed the hospital's original perioperative safety management of chest wall port and peripherally inserted central catheter (PICC) insertion, while the intervention group adopted the HFMEA management mode for the perioperative safety management of arm infusion port. The risk priority number (RPN) , the occurrence of high-risk failure modes and complications of the two groups were compared.Results:The RPN values of failure modes such as inadequate preoperative evaluation, loss of intraoperative accessories, low puncture position, too short catheter clipping, loose connection between catheter and injection base, catheter positioning after incision suture, and insufficient postoperative health education in the intervention group were lower than those in the control group, with statistical differences ( P<0.05) . The incidence of inadequate preoperative evaluation, inadequate postoperative health education and postoperative complications in the intervention group were statistically lower than those in the control group ( P<0.05) . Conclusions:The HFMEA management mode can reduce the risk of perioperative links of cancer patients at arm infusion port and decrease the incidence of postoperative complications, which is worthy of clinical promotion.

Objective:To investigate the value of a preoperatively MRI-based deep learning (DL) radiomics machine learning model to distinguish low-grade and high-grade soft tissue sarcomas (STS).Methods:From November 2007 to May 2019, 151 patients with STS confirmed by pathology in the Affiliated Hospital of Qingdao University were enrolled as training sets, and 131 patients in the Affiliated Hospital of Shandong First Medical University and the Third Hospital of Hebei Medical University were enrolled as external validation sets. According to the French Federation Nationale des Centres de Lutte Contre le Cancer classification (FNCLCC) system, 161 patients with FNCLCC grades Ⅰ and Ⅱ were defined as low-grade and 121 patients with grade Ⅲ were defined as high-grade. The hand-crafted radiomic (HCR) and DL radiomic features of the lesions were extracted respectively. Based on HCR features, DL features, and HCR-DL combined features, respectively, three machine-learning models were established by decision tree, logistic regression, and support vector machine (SVM) classifiers. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each machine learning model and choose the best one. The univariate and multivariate logistic regression were used to establish a clinical-imaging factors model based on demographics and MRI findings. The nomogram was established by combining the optimal radiomics model and the clinical-imaging model. The AUC was used to evaluate the performance of each model and the DeLong test was used for comparison of AUC between every two models. The Kaplan-Meier survival curve and log-rank test were used to evaluate the performance of the optimal machine learning model in the risk stratification of progression free survival (PFS) in STS patients.Results:The SVM radiomics model based on HCR-DL combined features had the optimal predicting power with AUC values of 0.931(95%CI 0.889-0.973) in the training set and 0.951 (95%CI 0.904-0.997) in the validation set. The AUC values of the clinical-imaging model were 0.795 (95%CI 0.724-0.867) and 0.615 (95%CI 0.510-0.720), and of the nomogram was 0.875 (95%CI 0.818-0.932) and 0.786 (95%CI 0.701-0.872) in the training and validation sets, respectively. In validation set, the performance of SVM radiomics model was better than those of the nomogram and clinical-imaging models ( Z=3.16, 6.07; P=0.002,<0.001). Using the optimal radiomics model, there was statistically significant in PFS between the high and low risk groups of STS patients (training sets: χ2=43.50, P<0.001; validation sets: χ2=70.50, P<0.001). Conclusion:Preoperative MRI-based DL radiomics machine learning model has accurate prediction performance in differentiating the histopathological grading of STS. The SVM radiomics model based on HCR-DL combined features has the optimal predicting power and was expected to undergo risk stratification of prognosis in STS patients.

Objective To analyze the clinical features of patients with coronavirus disease 2019 (COVID-19) in Shanghai and to investigate the risk factors for disease progression to severe cases. Methods The clinical data of 292 adult patients with COVID-19 hospitalized in Shanghai Public Health Clinical Center from January 20, 2020 to February 10, 2020 were retrospectively analyzed, including 21 severe patients and 271 mild patients. The demographic characteristics, epidemiological history, history of underlying diseases and laboratory examinations were compared between the two groups. Measurement data were compared using t test or Mann-Whitney U test. The count data were compared using hi-square test. The binary logistic regression equation was used to analyze the risk factors for the progression of patients to severe cases. Results Among the 292 patients, 21 were severe cases with the rate of 7.2% (21/292). One patient died, and the mortality rate was 4.8% in severe patients. The severe patients aged (65.0±15.7) years old, 19 (90.5%) were male, 11 (52.4%) had underlying diseases, 7 (33.3%) had close relatives diagnosed with COVID-19. The mild patients aged (48.7±15.7) years old, 135 (49.8%) were male, 74 (27.3%) had underlying diseases, 36 (13.3%) had close relatives diagnosed with COVID-19. The differences between two groups were all significant statistically ( t =-4.730, χ 2 =12.930, 5.938 and 4.744, respectively, all P <0.05). Compared with the mild patients, the levels of absolute numbers of neutrophils, alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase, creatinine, serum cystatin C, C reactive protein (CRP), procalcitonin , D -dimer, pro-B-type natriuretic peptide (proBNP), serum myoglobin, creatine kinase (CK), creatine kinase isoenzyme (CK-MB), serum troponin I (cTnI) in severe patients were all significantly higher ( U =2 091.5, 1 928.0, 1 215.5, 729.0, 1 580.5, 1 375.5, 917.5, 789.5, 1 209.0, 1 434.0, 638.0, 964.5, 1 258.0 and 1 747.5, respectively, all P <0.05), while the levels of lymphocyte count, albumin, transferrin, CD3 + T lymphocyte count, CD8 + T lymphocyte count and CD4 + T lymphocyte count in severe patients were all significantly lower ( U =1 263.5, t =4.716, U =1 214.0, 962.0, 1 167.5 and 988.0, respectively, all P <0.05). Further logistic regression analysis showed that the albumin (odds ratio ( OR )=0.806, 95% CI 0.675-0.961), CRP ( OR =1.016, 95% CI 1.000-1.032), serum myoglobin ( OR =1.010, 95% CI 1.004-1.016), CD3 + T lymphocyte count ( OR =0.996, 95% CI 0.991-1.000) and CD8 + T lymphocyte count ( OR =1.006, 95% CI 1.001-1.010) at admission were independent risk factors for the progression of COVID-19 patients to severe illness (all P <0.05). Conclusions Severe cases of patients with COVID-19 in Shanghai are predominantly elderly men with underlying diseases. Albumin, CRP, serum myoglobin, CD3 + T lymphocyte count and CD8 + T lymphocyte count could be used as early warning indicators for severe cases, which deserve more clinical attention.