BACKGROUND As a minimally invasive technique,endoscopic submucosal dissection(ESD)is widely used in treating early colorectal cancer(ECRC)and precancerous lesions(PCLs).However,a common postoperative complication-dela...BACKGROUND As a minimally invasive technique,endoscopic submucosal dissection(ESD)is widely used in treating early colorectal cancer(ECRC)and precancerous lesions(PCLs).However,a common postoperative complication-delayed postoperative bleeding(DPOB)-can significantly hinder patient recovery.AIM To build and validate a predictive model for assessing post-ESD DPOB risk in ECRC and PCL patients,utilizing logistic regression methodology.METHODS A retrospective review was conducted on ECRC/PCL 302 patients who received ESD at our hospital between July 2021 and July 2024.The cohort was stratified based on the incidence of DPOB following ESD,forming DPOB and non-DPOB groups.Through allocation,they were further allocated into model and validation cohorts.Clinical variables from both cohorts were collated and subjected to univariate analysis to determine potential factors associated with post-ESD DPOB.Subsequently,we constructed a predictive model for DPOB risk employing logistic regression analysis.Model performance assessment used receiver operating characteristic curves in both the training and validation cohorts,with internal validation accomplished via 10-fold cross-validation.RESULTS The occurrence rate of DPOB was 9.93%.Univariate analysis revealed that the number of lesions,lesion size,lesion location,degree of submucosal fibrosis,and intraoperative bleeding were significantly associated with DPOB.Binary logistic regression analysis identified the number of lesions,lesion size,lesion location,and degree of submucosal fibrosis as independent DPOB determinants.A nomogram that was developed to quantify the DPOB risk exhibited that an increment in the total score corresponded to an increased risk.The model achieved area under the curve values of 0.831 and 0.821 in the model and validation groups,respectively,with P values of 0.853 and 0.203 in the Hosmer-Lemeshow test.The model demonstrated robust discriminative performance,with an average area under the curve of 0.795(95%confidence interval:0.702-0.887)in 10-fold cross-validation.CONCLUSION Collectively,the presence of multiple lesions,lesion size of≥3 cm,lesion localization in the rectum,and severe fibrosis are significant independent predictors of DPOB in patients undergoing surgery for ECRC or PCLs.The proposed risk prediction model,which integrates these factors,demonstrates excellent predictive accuracy and clinical utility,thereby providing a valuable tool for risk stratification and postoperative management in this patient population.展开更多
This study discusses the analysis of various modeling approaches such as genetic algorithms, fuzzy logic and evidential reasoning, and maintenance techniques applicable to the liquefied natural gas （LNG） carrier ope...This study discusses the analysis of various modeling approaches such as genetic algorithms, fuzzy logic and evidential reasoning, and maintenance techniques applicable to the liquefied natural gas （LNG） carrier operations in the maritime environment. The usefulness of these algorithms in the LNG carrier industry in the areas of risk assessment and maintenance modeling as a standalone or hybrid algorithm are identified. This is evidenced with illustrative case studies.展开更多
BACKGROUND Research has shown that several factors can influence postoperative abnormal liver function;however,most studies on this issue have focused specifically on hepatic and cardiac surgeries,leaving limited rese...BACKGROUND Research has shown that several factors can influence postoperative abnormal liver function;however,most studies on this issue have focused specifically on hepatic and cardiac surgeries,leaving limited research on contributing factors in other types of surgeries.AIM To identify the risk factors for early postoperative abnormal liver function in multiple surgery types and construct a risk prediction model.METHODS This retrospective cohort study involved 3720 surgical patients from 5 surgical departments at Guangdong Provincial Hospital of Traditional Chinese Medicine.Patients were divided into abnormal(n=108)and normal(n=3612)groups based on liver function post-surgery.Univariate analysis and LASSO regression screened variables,followed by logistic regression to identify risk factors.A prediction model was constructed based on the variables selected via logistic re-gression.The goodness-of-fit of the model was evaluated using the Hosm-er–Lemeshow test,while discriminatory ability was measured by the area under the receiver operating characteristic curve.Calibration curves were plotted to visualize the consistency between predicted probabilities and observed outcomes.RESULTS The key factors contributing to abnormal liver function after surgery include elevated aspartate aminotransferase and alanine aminotransferase levels and reduced platelet counts pre-surgery,as well as the sevoflurane use during the procedure,among others.CONCLUSION The above factors collectively represent notable risk factors for postoperative liver function injury,and the prediction model developed based on these factors demonstrates strong predictive efficacy.展开更多
BACKGROUND Aortic adverse remodeling remains a critical complication following thoracic endovascular aortic repair(TEVAR)for Stanford type B aortic dissection(TBAD),significantly impacting long-term survival.Accurate ...BACKGROUND Aortic adverse remodeling remains a critical complication following thoracic endovascular aortic repair(TEVAR)for Stanford type B aortic dissection(TBAD),significantly impacting long-term survival.Accurate risk prediction is essential for optimized clinical management.AIM To develop and validate a logistic regression-based risk prediction model for aortic adverse remodeling following TEVAR in patients with TBAD.METHODS This retrospective observational cohort study analyzed 140 TBAD patients undergoing TEVAR at a tertiary center(2019–2024).Based on European guidelines,patients were categorized into adverse remodeling(aortic growth rate>2.9 mm/year,n=45)and favorable remodeling groups(n=95).Comprehensive variables(clinical/imaging/surgical)were analyzed using multivariable logistic regression to develop a predictive model.Model performance was assessed via receiver operating characteristic-area under the curve(AUC)and Hosmer-Lemeshow tests.RESULTS Multivariable analysis identified several strong independent predictors of negative aortic remodeling.Larger false lumen diameter at the primary entry tear[odds ratio(OR):1.561,95%CI:1.197–2.035;P=0.001]and patency of the false lumen(OR:5.639,95%CI:4.372-8.181;P=0.004)were significant risk factors.False lumen involvement extending to the thoracoabdominal aorta was identified as the strongest predictor,significantly increasing the risk of adverse remodeling(OR:11.751,95%CI:9.841-15.612;P=0.001).Conversely,false lumen involvement confined to the thoracic aorta demonstrated a significant protective effect(OR:0.925,95%CI:0.614–0.831;P=0.015).The prediction model exhibited excellent discrimination(AUC=0.968)and calibration(Hosmer-Lemeshow P=0.824).CONCLUSION This validated risk prediction model identifies aortic adverse remodeling with high accuracy using routinely available clinical parameters.False lumen involvement thoracoabdominal aorta is the strongest predictor(11.751-fold increased risk).The tool enables preoperative risk stratification to guide tailored TEVAR strategies and improve long-term outcomes.展开更多
This article summarizes a joint research projec undertaken under the Risk Management Solutions, Inc(RMS) banner to investigate some of the possible approaches for agricultural risk modeling in China. Two modeling appr...This article summarizes a joint research projec undertaken under the Risk Management Solutions, Inc(RMS) banner to investigate some of the possible approaches for agricultural risk modeling in China. Two modeling approaches were investigated—the simulated weather crop index and the burn yield analysis approach. The study was limited to Hunan Province and a single crop—rice. Both modeling approaches were dealt with probabilistically and were able to produce probabilistic risk metrics. Illustrative model outputs are also presented. The article discusses the robustness of the modeling approaches and their dependence on the availability, access to, and quality of weather and yield data. We offer our perspective on the requirements for models and platforms for agricultural risk quantification in China in order to respond to the needs of all stakeholders in agricultural risk transfer.展开更多
Energy storage batteries can smooth the volatility of renewable energy sources.The operating conditions during power grid integration of renewable energy can affect the performance and failure risk of battery energy s...Energy storage batteries can smooth the volatility of renewable energy sources.The operating conditions during power grid integration of renewable energy can affect the performance and failure risk of battery energy storage system(BESS).However,the current modeling of grid-connected BESS is overly simplistic,typically only considering state of charge(SOC)and power constraints.Detailed lithium(Li)-ion battery cell models are computationally intensive and impractical for real-time applications and may not be suitable for power grid operating conditions.Additionally,there is a lack of real-time batteries risk assessment frameworks.To address these issues,in this study,we establish a thermal-electric-performance(TEP)coupling model based on a multitime scale BESS model,incorporating the electrical and thermal characteristics of Li-ion batteries along with their performance degradation to achieve detailed simulation of grid-connected BESS.Additionally,considering the operating characteristics of energy storage batteries and electrical and thermal abuse factors,we developed a battery pack operational riskmodel,which takes into account SOCand charge-discharge rate(Cr),using amodified failure rate to represent the BESS risk.By integrating detailed simulation of energy storage with predictive failure risk analysis,we obtained a detailed model for BESS risk analysis.This model offers a multi-time scale integrated simulation that spans month-level energy storage simulation times,day-level performance degradation,minutescale failure rate,and second-level BESS characteristics.It offers a critical tool for the study of BESS.Finally,the performance and risk of energy storage batteries under three scenarios—microgrid energy storage,wind power smoothing,and power grid failure response—are simulated,achieving a real-time state-dependent operational risk analysis of the BESS.展开更多
Cyber-physical systems(CPSs)are becoming increasingly important in safety-critical systems.Particular risk analysis(PRA)is an essential step in the safety assessment process to guarantee the quality of a system in the...Cyber-physical systems(CPSs)are becoming increasingly important in safety-critical systems.Particular risk analysis(PRA)is an essential step in the safety assessment process to guarantee the quality of a system in the early phase of system development.Human factors like the physical environment are the most important part of particular risk assessment.Therefore,it is necessary to analyze the safety of the system considering human factor and physical factor.In this paper,we propose a new particular risk model(PRM)to improve the modeling ability of the Architecture Analysis and Design Language(AADL).An architecture-based PRA method is presented to support safety assessment for the AADL model of a cyber-physical system.To simulate the PRM with the proposed PRA method,model transformation from PRM to a deterministic and stochastic Petri net model is implemented.Finally,a case study on the power grid system of CPS is modeled and analyzed using the proposed method.展开更多
This paper investigates ruin,capital injection,and dividends for a two-dimensional risk model.The model posits that surplus levels of insurance companies are governed by a perturbed composite Poisson risk model.This m...This paper investigates ruin,capital injection,and dividends for a two-dimensional risk model.The model posits that surplus levels of insurance companies are governed by a perturbed composite Poisson risk model.This model introduces a dependence between the two surplus levels,present in both the associated perturbations and the claims resulting from common shocks.Critical levels of capital injection and dividends are established for each of the two risks.The surplus levels are observed discretely at fixed intervals,guiding decisions on capital injection,dividends,and ruin at these junctures.This study employs a two-dimensional Fourier cosine series expansion method to approximate the finite time expected discounted operating cost until ruin.The ensuing approximation error is also quantified.The validity and accuracy of the method are corroborated through numerical examples.Furthermore,the research delves into the optimal capital allocation problem.展开更多
Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8^(+)T cell immune infiltration and immune suppression.We constructed a CD8^(+)T cells related risk score model to predic...Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8^(+)T cell immune infiltration and immune suppression.We constructed a CD8^(+)T cells related risk score model to predict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8^(+)T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS 2,and TNFRSF1B was constructed.The risk score model was well validated through an independent external validation cohort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P<0.0001)and lower CD8^(+)T cells infiltration(P<0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P<0.01).Drug sensitivity analysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene model was verified by immunohistochemistry.In summary,the establishment and validation of a CD8^(+)T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.展开更多
BACKGROUND Colorectal cancer(CRC)is one of the most prevalent and lethal malignant tumors worldwide.Currently,surgical intervention was the primary treatment modality for CRC.However,increasing studies have revealed t...BACKGROUND Colorectal cancer(CRC)is one of the most prevalent and lethal malignant tumors worldwide.Currently,surgical intervention was the primary treatment modality for CRC.However,increasing studies have revealed that CRC patients may experience postoperative cognitive dysfunction(POCD).AIM To establish a risk prediction model for POCD in CRC patients and investigate the preventive value of dexmedetomidine(DEX).METHODS A retrospective analysis was conducted on clinical data from 140 CRC patients who underwent surgery at the People’s Hospital of Qian Nan from February 2020 to May 2024.Patients were allocated into a modeling group(n=98)and a validation group(n=42)in a 7:3 ratio.General clinical data were collected.Additionally,in the modeling group,patients who received DEX preoperatively were incorporated into the observation group(n=54),while those who did not were placed in the control group(n=44).The incidence of POCD was recorded for both cohorts.Data analysis was performed using statistical product and service solutions 20.0,with t-tests orχ^(2) tests employed for group comparisons based on the data type.Least absolute shrinkage and selection operator regression was applied to identify influencing factors and reduce the impact of multicollinear predictors among variables.Multivariate analysis was carried out using Logistic regression.Based on the identified risk factors,a risk prediction model for POCD in CRC patients was developed,and the predictive value of these risk factors was evaluated.RESULTS Significant differences were observed between the cognitive dysfunction group and the non-cognitive dysfunction group in diabetes status,alcohol consumption,years of education,anesthesia duration,intraoperative blood loss,intraoperative hypoxemia,use of DEX during surgery,intraoperative use of vasoactive drugs,surgical time,systemic inflammatory response syndrome(SIRS)score(P<0.05).Multivariate Logistic regression analysis identified that diabetes[odds ratio(OR)=4.679,95%confidence interval(CI)=1.382-15.833],alcohol consumption(OR=5.058,95%CI:1.255-20.380),intraoperative hypoxemia(OR=4.697,95%CI:1.380-15.991),no use of DEX during surgery(OR=3.931,95%CI:1.383-11.175),surgery duration≥90 minutes(OR=4.894,95%CI:1.377-17.394),and a SIRS score≥3(OR=4.133,95%CI:1.323-12.907)were independent risk factors for POCD in CRC patients(P<0.05).A risk prediction model for POCD was constructed using diabetes,alcohol consumption,intraoperative hypoxemia,non-use of DEX during surgery,surgery duration,and SIRS score as factors.A receiver operator characteristic curve analysis of these factors revealed the model’s predictive sensitivity(88.56%),specificity(70.64%),and area under the curve(AUC)(AUC=0.852,95%CI:0.773-0.919).The model was validated using 42 CRC patients who met the inclusion criteria,demonstrating sensitivity(80.77%),specificity(81.25%),and accuracy(80.95%),and AUC(0.805)in diagnosing cognitive impairment,with a 95%CI:0.635-0.896.CONCLUSION Logistic regression analysis identified that diabetes,alcohol consumption,intraoperative hypoxemia,non-use of DEX during surgery,surgery duration,and SIRS score vigorously influenced the occurrence of POCD.The risk prediction model based on these factors demonstrated good predictive performance for POCD in CRC individuals.This study offers valuable insights for clinical practice and contributes to the prevention and management of POCD under CRC circumstances.展开更多
BACKGROUND Rabies is a zoonotic viral disease affecting the central nervous system,caused by the rabies virus,with a case-fatality rate of 100%once symptoms appear.AIM To analyze high-risk factors associated with ment...BACKGROUND Rabies is a zoonotic viral disease affecting the central nervous system,caused by the rabies virus,with a case-fatality rate of 100%once symptoms appear.AIM To analyze high-risk factors associated with mental disorders induced by rabies vaccination and to construct a risk prediction model to inform strategies for improving patients’mental health.METHODS Patients who received rabies vaccinations at the Department of Infusion Yiwu Central Hospital between August 2024 and July 2025 were included,totaling 384 cases.Data were collected from medical records and included demographic characteristics(age,gender,occupation),lifestyle habits,and details regarding vaccine type,dosage,and injection site.The incidence of psychiatric disorders following vaccination was assessed using standardized anxiety and depression rating scales.Patients were categorized into two groups based on the presence or absence of anxiety and depression symptoms:The psychiatric disorder group and the non-psychiatric disorder group.Differences between the two groups were compared,and high-risk factors were identified using multivariate logistic regression analysis.A predictive model was then developed based on these factors to evaluate its predictive performance.RESULTS Among the 384 patients who received rabies vaccinations,36 cases(9.38%)were diagnosed with anxiety,52 cases(13.54%)with depression,and 88 cases(22.92%)with either condition.Logistic regression analysis identified the following signi ficant risk factors for psychiatric disorders:Education level of primary school or below,exposure site at the head and neck,exposure classified as grade III,family status of divorced/widowed/unmarried/living alone,number of wounds greater than one,and low awareness of rabies prevention and control(P<0.05).The risk prediction model demonstrated good performance,with an area under the receiver operating characteristic curve of 0.859,a specificity of 74.42%,and a sensitivity of 93.02%.CONCLUSION In real-world settings,psychiatric disorders following rabies vaccination are relatively common and are associated with factors such as lower education level,higher exposure severity,vulnerable family status,and limited awareness of rabies prevention and control.The developed risk prediction model may aid in early identification of high-risk individuals and support timely clinical intervention.展开更多
BACKGROUND This study aimed to compare and analyze risk factors for pancreatic fistula following pancreaticoduodenectomy(PD)using different definition criteria,and to develop a predictive model for standardized pancre...BACKGROUND This study aimed to compare and analyze risk factors for pancreatic fistula following pancreaticoduodenectomy(PD)using different definition criteria,and to develop a predictive model for standardized pancreatic fistula risk assessment.AIM To identify and compare risk factors for postoperative pancreatic fistula(POPF)following PD using both the 2005 International Study Group of Pancreatic Fistula and updated 2016 International Study Group on Pancreatic Surgery diagnostic criteria,and to develop a clinically applicable predictive model based on objective preoperative parameters for standardized pancreatic fistula risk assessment and perioperative management optimization.METHODS We conducted a retrospective analysis of 303 patients who underwent PD at CR&WISCO General Hospital between January 2017 and May 2023.POPF cases were classified according to both previous and updated diagnostic standards.For statistical analysis,we employed t-tests or Mann-Whitney U tests for continuous variables andχ^(2) tests for categorical data.To identify risk factors associated with POPF under both classification systems,we performed univariate and multivariate logistic regression analyses.RESULTS Univariate analysis identified several factors associated with POPF:Main pancreatic duct diameter(χ^(2)=31.641,P<0.001),main pancreatic duct index(χ^(2)=52.777,P<0.001),portal vein invasion(χ^(2)=6.259,P=0.012),intra-abdominal fat thickness(χ^(2)=7.665,P=0.006),preoperative biliary drainage(χ^(2)=5.999,P=0.014),pancreatic characteristics(χ^(2)=5.544,P=0.019),pancreatic resection margin thickness(t=2.055,P=0.032),pancreatic computed tomography(CT)value(t=-3.224,P=0.002),and preoperative blood amylase level(Z=-2.099,P=0.036).Multivariate logistic regression identified three independent risk factors:Main pancreatic duct index[odds ratio(OR)=0.000,95%confidence interval(CI):0.000-0.011],pancreatic cancer[OR=4.843,95%CI:1.285-18.254],and pancreatic CT value[OR=0.869,95%CI:0.806-0.937](all P<0.05).CONCLUSION The main pancreatic duct index and pancreatic CT value are strongly correlated with pancreatic fistula development after PD.展开更多
This article introduces and compares risk assessment models for venous thromboembolism in gynecological patients at home and abroad.The models assessed included the Caprini risk assessment model,the G-Caprini risk ass...This article introduces and compares risk assessment models for venous thromboembolism in gynecological patients at home and abroad.The models assessed included the Caprini risk assessment model,the G-Caprini risk assessment model,the Rogers risk assessment model,the Autar risk assessment model,the gynecological patient surgical venous thrombosis risk assessment scale,the Wells score,the COMPASS-CAT thrombus risk assessment model,the Khorana risk assessment model,the Padua risk assessment model,and the Chaoyang model.The purpose of this study is to provide a foundation for developing a risk assessment tool for gynecological venous thromboembolism tailored to Chinese patients and to assist clinical health care workers in selecting appropriate risk assessment tools and guiding individualized prevention measures.展开更多
Snowmelt runoffis an important component of water resources in the Northwest China(NWC).With global cli-mate warming and the increasing frequency of extreme events,snowmelt floods have caused significant damage.Howeve...Snowmelt runoffis an important component of water resources in the Northwest China(NWC).With global cli-mate warming and the increasing frequency of extreme events,snowmelt floods have caused significant damage.However,current studies lack comprehensive research and systematic risk assessments of snowmelt floods across the NWC.Based on the snowmelt runoffsimulated by GLDAS-NOAH model(1948-2022),the multiple indicators of snowmelt floods were retrieved by Peaks Over Threshold(POT)model in the NWC,and comprehensive risk assessment was conducted by integrating socio-economic data.The results indicated that the snowmelt runoffin the NWC shows a significant increasing trend and exhibits a spatial pattern of being more abundant in the northwest and southwest edges while less in the central and eastern regions.In Northern Xinjiang,snowmelt floods occurred relatively infrequently but with large magnitudes,while around the Qilian Mountains,snowmelt floods were more frequent but of smaller magnitudes.The longest duration of snowmelt floods was observed in the Kashgar and Yarkant River.Basins near mountainous areas are prone to snowmelt floods,especially the Tongtian and Lancang River basins,as well as the Ebinur Lake,Ili River basin,and the rivers south of the Altai Mountains,which face the highest risk of snowmelt floods.Based on comprehensive assessment of hazard,expo-sure,vulnerability and adaptability,high and very high-risk areas account for 15.5%of the NWC.It is urgent to enhance monitoring,early warning systems,and implement corresponding disaster prevention and mitigation measures in large mountainous basins.展开更多
BACKGROUND Unplanned extubation(UE)after endoscopic retrograde cholangiopancreatography plus endoscopic nasobiliary drainage(ENBD)increases patient morbidity and prolongs hospitalization duration.AIM To construct a ri...BACKGROUND Unplanned extubation(UE)after endoscopic retrograde cholangiopancreatography plus endoscopic nasobiliary drainage(ENBD)increases patient morbidity and prolongs hospitalization duration.AIM To construct a risk prediction model for UE in patients undergoing ENBD to provide evidence for clinical nursing.METHODS A multicenter retrospective study was conducted,collecting data from 981 patients undergoing ENBD from three hospitals in Chongqing from January 2018 to June 2024,randomly allocated to modeling and validation groups in a 7:3 ratio.Logistic regression analysis was used to screen independent risk factors,construct prediction models,and draw nomograms.RESULTS The overall incidence of UE was 6.12%(60/981).The majority(70.00%)of extubations occurred within 24-72 h postoperatively.Multivariate logistic regression analysis identified age≥61 years[odds ratio(OR)=2.341,95%confidence interval(CI):1.28-4.27],smoking history(OR=2.876,95%CI:1.54-5.37),prolonged fasting time(OR=1.124,95%CI:1.05-1.20),prolonged catheter duration(OR=1.286,95%CI:1.09-1.52),and consciousness changes(OR=3.152,95%CI:1.69-5.89)were independent risk factors while serum albumin was a protective factor(OR=0.912,95%CI:0.87-0.95).The model receiver operating characteristic area under curve was 0.881 with accuracy of 80.36%,sensitivity of 83.59%,and specificity of 74.88%.A nomogram total score≥199 points corresponded to a high-risk threshold.CONCLUSION The six-factor risk prediction model had good discrimination and accuracy,which can provide clinical nursing staff with scientific evidence to identify patients at high risk and help reduce the incidence of UE.展开更多
This editorial critically evaluated the recent study by Wang et al,which systematically investigated the efficacy of perioperative disinfection and isolation measures(including preoperative povidone-iodine disinfectio...This editorial critically evaluated the recent study by Wang et al,which systematically investigated the efficacy of perioperative disinfection and isolation measures(including preoperative povidone-iodine disinfection,intraoperative sterile barrier techniques,and postoperative intensive care)in reducing infection rates.The study further incorporated the surgical site infection risk prediction model(constructed via the least absolute shrinkage and selection operator al-gorithm,integrating patients'baseline characteristics,surgical indicators,and regional antibiotic-resistant bacterial data),and proposed a dynamic prevention and control system termed“disinfection protocols-predictive models–real-time monitoring”.The article highlighted that preoperative risk stratification,intraoperative personalized antibiotic selection,and postoperative multidimensional monitoring(encompassing inflammatory biomarkers,imaging,and microbiological testing)enabled the precise identification of high-risk patients and optimized intervention thresholds.Future research is deemed necessary to validate the synergistic effects of disinfection protocols and predictive models through large-scale multicenter studies,combined with advanced intraoperative rapid microbial detection technologies.This approach aims to establish standardized infection control protocols tailored for precision medicine and regional adaptability.Future research should prioritize validating the synergistic effects of disinfection protocols and predictive models via multi-center studies,while incorporating advanced rapid intraoperative microbial detection technologies to develop standardized infection prevention and control procedures.Such efforts will enhance the implementation of precise and regionally adaptive infection control strategies.展开更多
BACKGROUND Coronary heart disease(CHD)is a prevalent type 2 diabetes mellitus(T2DM)complication.Further,the risk stratification before angiography may help diagnose T2DM with CHD early.However,few studies have investi...BACKGROUND Coronary heart disease(CHD)is a prevalent type 2 diabetes mellitus(T2DM)complication.Further,the risk stratification before angiography may help diagnose T2DM with CHD early.However,few studies have investigated the coronary imaging characteristics and risk factors of patients with T2DM complicated with CHD.AIM To compare the differences in coronary imaging between patients with T2DM with and without CHD,determine the risk factors of T2DM complicated with CHD,and establish a predictive tool for diagnosing CHD in T2DM.METHODS This study retrospectively analyzed 103 patients with T2DM from January 2022 to May 2024.They are categorized based on CHD occurrence into:(1)The control group,consisting of patients with T2DM without CHD;and(2)The observation group,which includes patients with T2MD with CHD.Age,sex,smoking and drinking history,CHD family history,metformin(MET)treatment pre-admission,body mass index,fasting blood glucose(FBG),triglyceride(TG),total cholesterol,high-density lipoprotein cholesterol,low-density lipoprotein cholesterol(LDL-C),serum creatinine,blood urea nitrogen(BUN),alanine aminotransferase,aspartate aminotransferase,glycosylated hemoglobin(HbA1c),and coronary imaging data of both groups were collected from the medical record system.Logistic risk analysis was conducted to screen risk factors.The prediction model’s prediction efficiency was evaluated with receiver operating characteristic curves.RESULTS The control and observation groups consisted of 48 and 55 cases,respectively.The two groups were statistically different in terms of age(t=2.006,P=0.048),FBG(t=6.038,P=0.000),TG(t=2.015,P=0.047),LDL-C(t=2.017,P=0.046),and BUN(t=2.035,P=0.044).The observation group demonstrated lower proportions of patients receiving MET(χ^(2)=5.073,P=0.024)and higher proportions of patients with HbA1c of>7.0%(χ^(2)=6.980,P=0.008)than the control group.The observation group consisted of 15,17,and 23 cases of moderate stenosis,severe stenosis,and occlusion,respectively,with a greater number of coronary artery occlusion cases than the control group(χ^(2)=6.399,P=0.041).The observation group consisted significantly higher number of diffuse lesion cases at 35 compared with the control group(χ^(2)=15.420,P=0.000).The observation group demonstrated a higher right coronary artery(RCA)stenosis index(t=6.730,P=0.000),circumflex coronary artery(LCX)stenosis index(t=5.738,P=0.000),and total stenosis index(t=7.049,P=0.000)than the control group.FBG[odds ratio(OR)=1.472;95%confidence interval(CI):1.234-1.755;P=0.000]and HbA1c(OR=3.197;95%CI:1.149-8.896;P=0.026)were independent risk factors for T2DM complicated with CHD,whereas MET(OR=0.350;95%CI:0.129-0.952;P=0.040)was considered a protective factor for CHD in T2DM.CONCLUSION Coronary artery occlusion is a prevalent complication in patients with T2DM.Patients with T2MD with CHD demonstrated a higher degree of RCA and LCX stenosis than those with T2DM without CHD.FBG,HbA1c,and MET treatment history are risk factors for T2DM complicated with CHD.展开更多
Based on the objective reality that audit risk responsibility has mainly been attributed to certified public accountants in the past,and audit standards have not specifically divided the entities responsible for audit...Based on the objective reality that audit risk responsibility has mainly been attributed to certified public accountants in the past,and audit standards have not specifically divided the entities responsible for audit risk responsibility,combined with the understanding of the types of audit risk elements related to audit standards,the differences in the understanding of audit risk and its relationship model application caused by the different audit cultures in China and the West have led to a bias of Chinese certified public accountants to bear inspection risks,which affects their professional enthusiasm and continues to cause accounting firms to be lazy in audit quality management.Based on this,literature research,case analysis,and logical deduction methods were used to redefine the concept of audit risk from the perspective of risk responsibility subjects.The traditional audit risk elements and their relationship models were briefly introduced,and the identification of audit risk elements and optimization of audit risk relationship models were systematically demonstrated.展开更多
Objective:To study the risk prediction model for multiple bronchoalveolar lavage in children with mycoplasma pneumoniae pneumonia(MPP).Methods:151 pediatric patients with MPP admitted in our hospital from July to Dece...Objective:To study the risk prediction model for multiple bronchoalveolar lavage in children with mycoplasma pneumoniae pneumonia(MPP).Methods:151 pediatric patients with MPP admitted in our hospital from July to December 2023 were selected,the incidence rate of multiple bronchoalveolar lavage was recorded.A logistic multivariate regression model was employed to analyze relevant factors and construct a risk prediction model for multiple bronchoalveolar lavage in children with MPP.Results:Among 151 children with MPP,64 cases underwent multiple bronchoalveolar lavage,accounting for 42.38%.The Logistic multivariate model analysis revealed that the pleural effusion,sepsis,and abnormally elevated serum levels of LDH and D-D were independent influence factors for multiple bronchoalveolar lavage in children with MPP(p<0.05),based on this,a Nomogram prediction model can be established.The ROC analysis results showed that the AUC of the model to judge the multiple bronchoalveolar lavage in MPP patients was 0.828(SE=0.035,95%CI=0.760-0.896,p<0.001),the sensitivity was 0.813 and the specificity was 0.759.Conclusion:The multiple bronchoscopic bronchoalveolar lavage in MPP patients are associated with the levels of LDH and D-D,as well as the presence of pleural effusion and sepsis complications,the risk prediction model established,which based on this has high accuracy.展开更多
The urgent necessity for enhanced risk stratification to improve the efficiency of colonoscopy screening is underscored by the fact that colorectal cancer(CRC)continues to be a primary cause of global cancer mortality...The urgent necessity for enhanced risk stratification to improve the efficiency of colonoscopy screening is underscored by the fact that colorectal cancer(CRC)continues to be a primary cause of global cancer mortality.Conventional models mostly rely on generalized obesity markers including body mass index(BMI),which does not effectively represent oncogenic risk linked with abdominal obesity.Liu et al undertook a large-scale case-control study comprising 6484 firsttime colonoscopy patients at a prominent Chinese hospital between 2020 and 2023 to overcome this restriction.Age,male sex,smoking status,and raised waist-hip ratio(WHR)were found by multivariate logistic regression as independent predictors of advanced colorectal neoplasia(ACN).In a validation cohort of 1891 individuals,a new 7-point risk scoring model was created and stratified into low-(5.0%)ACN prevalence,moderate-(10.3%)and high-risk(17.6%).With C-statistic=0.66 the model showed better discriminating ability than the Asia-Pacific Colorectal Screening(APCS)score(C-statistic=0.63)and the BMI-modified APCS model.These results fit newly published data showing central obesity as a major carcinogenic driver via pro-inflammatory visceral adipokine channels.With the use of WHR,patient risk classification is greatly improved,providing a practical tool to make the most of screening resources in the face of rising CRC incidence rates.Finally,multi-ethnic validation is necessary for the WHR-based scoring model to be considered for integration into global CRC preventive frameworks,since it improves the accuracy of ACN risk prediction.展开更多
文摘BACKGROUND As a minimally invasive technique,endoscopic submucosal dissection(ESD)is widely used in treating early colorectal cancer(ECRC)and precancerous lesions(PCLs).However,a common postoperative complication-delayed postoperative bleeding(DPOB)-can significantly hinder patient recovery.AIM To build and validate a predictive model for assessing post-ESD DPOB risk in ECRC and PCL patients,utilizing logistic regression methodology.METHODS A retrospective review was conducted on ECRC/PCL 302 patients who received ESD at our hospital between July 2021 and July 2024.The cohort was stratified based on the incidence of DPOB following ESD,forming DPOB and non-DPOB groups.Through allocation,they were further allocated into model and validation cohorts.Clinical variables from both cohorts were collated and subjected to univariate analysis to determine potential factors associated with post-ESD DPOB.Subsequently,we constructed a predictive model for DPOB risk employing logistic regression analysis.Model performance assessment used receiver operating characteristic curves in both the training and validation cohorts,with internal validation accomplished via 10-fold cross-validation.RESULTS The occurrence rate of DPOB was 9.93%.Univariate analysis revealed that the number of lesions,lesion size,lesion location,degree of submucosal fibrosis,and intraoperative bleeding were significantly associated with DPOB.Binary logistic regression analysis identified the number of lesions,lesion size,lesion location,and degree of submucosal fibrosis as independent DPOB determinants.A nomogram that was developed to quantify the DPOB risk exhibited that an increment in the total score corresponded to an increased risk.The model achieved area under the curve values of 0.831 and 0.821 in the model and validation groups,respectively,with P values of 0.853 and 0.203 in the Hosmer-Lemeshow test.The model demonstrated robust discriminative performance,with an average area under the curve of 0.795(95%confidence interval:0.702-0.887)in 10-fold cross-validation.CONCLUSION Collectively,the presence of multiple lesions,lesion size of≥3 cm,lesion localization in the rectum,and severe fibrosis are significant independent predictors of DPOB in patients undergoing surgery for ECRC or PCLs.The proposed risk prediction model,which integrates these factors,demonstrates excellent predictive accuracy and clinical utility,thereby providing a valuable tool for risk stratification and postoperative management in this patient population.
文摘This study discusses the analysis of various modeling approaches such as genetic algorithms, fuzzy logic and evidential reasoning, and maintenance techniques applicable to the liquefied natural gas （LNG） carrier operations in the maritime environment. The usefulness of these algorithms in the LNG carrier industry in the areas of risk assessment and maintenance modeling as a standalone or hybrid algorithm are identified. This is evidenced with illustrative case studies.
基金Supported by Guangdong Provincial Hospital of Chinese Medicine Science and Technology Research Special Project,No.YN2023WSSQ01State Key Laboratory of Traditional Chinese Medicine Syndrome.
文摘BACKGROUND Research has shown that several factors can influence postoperative abnormal liver function;however,most studies on this issue have focused specifically on hepatic and cardiac surgeries,leaving limited research on contributing factors in other types of surgeries.AIM To identify the risk factors for early postoperative abnormal liver function in multiple surgery types and construct a risk prediction model.METHODS This retrospective cohort study involved 3720 surgical patients from 5 surgical departments at Guangdong Provincial Hospital of Traditional Chinese Medicine.Patients were divided into abnormal(n=108)and normal(n=3612)groups based on liver function post-surgery.Univariate analysis and LASSO regression screened variables,followed by logistic regression to identify risk factors.A prediction model was constructed based on the variables selected via logistic re-gression.The goodness-of-fit of the model was evaluated using the Hosm-er–Lemeshow test,while discriminatory ability was measured by the area under the receiver operating characteristic curve.Calibration curves were plotted to visualize the consistency between predicted probabilities and observed outcomes.RESULTS The key factors contributing to abnormal liver function after surgery include elevated aspartate aminotransferase and alanine aminotransferase levels and reduced platelet counts pre-surgery,as well as the sevoflurane use during the procedure,among others.CONCLUSION The above factors collectively represent notable risk factors for postoperative liver function injury,and the prediction model developed based on these factors demonstrates strong predictive efficacy.
基金Supported by Zhangjiajie"Xiao He(Young Talent)"Project,No.2024XHRC03Jishou University School-Level Research Project.
文摘BACKGROUND Aortic adverse remodeling remains a critical complication following thoracic endovascular aortic repair(TEVAR)for Stanford type B aortic dissection(TBAD),significantly impacting long-term survival.Accurate risk prediction is essential for optimized clinical management.AIM To develop and validate a logistic regression-based risk prediction model for aortic adverse remodeling following TEVAR in patients with TBAD.METHODS This retrospective observational cohort study analyzed 140 TBAD patients undergoing TEVAR at a tertiary center(2019–2024).Based on European guidelines,patients were categorized into adverse remodeling(aortic growth rate>2.9 mm/year,n=45)and favorable remodeling groups(n=95).Comprehensive variables(clinical/imaging/surgical)were analyzed using multivariable logistic regression to develop a predictive model.Model performance was assessed via receiver operating characteristic-area under the curve(AUC)and Hosmer-Lemeshow tests.RESULTS Multivariable analysis identified several strong independent predictors of negative aortic remodeling.Larger false lumen diameter at the primary entry tear[odds ratio(OR):1.561,95%CI:1.197–2.035;P=0.001]and patency of the false lumen(OR:5.639,95%CI:4.372-8.181;P=0.004)were significant risk factors.False lumen involvement extending to the thoracoabdominal aorta was identified as the strongest predictor,significantly increasing the risk of adverse remodeling(OR:11.751,95%CI:9.841-15.612;P=0.001).Conversely,false lumen involvement confined to the thoracic aorta demonstrated a significant protective effect(OR:0.925,95%CI:0.614–0.831;P=0.015).The prediction model exhibited excellent discrimination(AUC=0.968)and calibration(Hosmer-Lemeshow P=0.824).CONCLUSION This validated risk prediction model identifies aortic adverse remodeling with high accuracy using routinely available clinical parameters.False lumen involvement thoracoabdominal aorta is the strongest predictor(11.751-fold increased risk).The tool enables preoperative risk stratification to guide tailored TEVAR strategies and improve long-term outcomes.
文摘This article summarizes a joint research projec undertaken under the Risk Management Solutions, Inc(RMS) banner to investigate some of the possible approaches for agricultural risk modeling in China. Two modeling approaches were investigated—the simulated weather crop index and the burn yield analysis approach. The study was limited to Hunan Province and a single crop—rice. Both modeling approaches were dealt with probabilistically and were able to produce probabilistic risk metrics. Illustrative model outputs are also presented. The article discusses the robustness of the modeling approaches and their dependence on the availability, access to, and quality of weather and yield data. We offer our perspective on the requirements for models and platforms for agricultural risk quantification in China in order to respond to the needs of all stakeholders in agricultural risk transfer.
基金Supported by Open Fund of National Key Laboratory of Power Grid Safety(No.XTB51202301386).
文摘Energy storage batteries can smooth the volatility of renewable energy sources.The operating conditions during power grid integration of renewable energy can affect the performance and failure risk of battery energy storage system(BESS).However,the current modeling of grid-connected BESS is overly simplistic,typically only considering state of charge(SOC)and power constraints.Detailed lithium(Li)-ion battery cell models are computationally intensive and impractical for real-time applications and may not be suitable for power grid operating conditions.Additionally,there is a lack of real-time batteries risk assessment frameworks.To address these issues,in this study,we establish a thermal-electric-performance(TEP)coupling model based on a multitime scale BESS model,incorporating the electrical and thermal characteristics of Li-ion batteries along with their performance degradation to achieve detailed simulation of grid-connected BESS.Additionally,considering the operating characteristics of energy storage batteries and electrical and thermal abuse factors,we developed a battery pack operational riskmodel,which takes into account SOCand charge-discharge rate(Cr),using amodified failure rate to represent the BESS risk.By integrating detailed simulation of energy storage with predictive failure risk analysis,we obtained a detailed model for BESS risk analysis.This model offers a multi-time scale integrated simulation that spans month-level energy storage simulation times,day-level performance degradation,minutescale failure rate,and second-level BESS characteristics.It offers a critical tool for the study of BESS.Finally,the performance and risk of energy storage batteries under three scenarios—microgrid energy storage,wind power smoothing,and power grid failure response—are simulated,achieving a real-time state-dependent operational risk analysis of the BESS.
基金the State Power Grid Company Science and Technical Plan Project,China(No.5100-201940008A-0-0-00)。
文摘Cyber-physical systems(CPSs)are becoming increasingly important in safety-critical systems.Particular risk analysis(PRA)is an essential step in the safety assessment process to guarantee the quality of a system in the early phase of system development.Human factors like the physical environment are the most important part of particular risk assessment.Therefore,it is necessary to analyze the safety of the system considering human factor and physical factor.In this paper,we propose a new particular risk model(PRM)to improve the modeling ability of the Architecture Analysis and Design Language(AADL).An architecture-based PRA method is presented to support safety assessment for the AADL model of a cyber-physical system.To simulate the PRM with the proposed PRA method,model transformation from PRM to a deterministic and stochastic Petri net model is implemented.Finally,a case study on the power grid system of CPS is modeled and analyzed using the proposed method.
基金supported by the Shihezi University High-Level Talents Research Startup Project(Project No.RCZK202521)the National Natural Science Foundation of China(Grant Nos.12271066,11871121,12171405)+1 种基金the Chongqing Natural Science Foundation Joint Fund for Innovation and Development Project(Project No.CSTB2024NSCQLZX0085)the Chongqing Normal University Foundation(Grant No.23XLB018).
文摘This paper investigates ruin,capital injection,and dividends for a two-dimensional risk model.The model posits that surplus levels of insurance companies are governed by a perturbed composite Poisson risk model.This model introduces a dependence between the two surplus levels,present in both the associated perturbations and the claims resulting from common shocks.Critical levels of capital injection and dividends are established for each of the two risks.The surplus levels are observed discretely at fixed intervals,guiding decisions on capital injection,dividends,and ruin at these junctures.This study employs a two-dimensional Fourier cosine series expansion method to approximate the finite time expected discounted operating cost until ruin.The ensuing approximation error is also quantified.The validity and accuracy of the method are corroborated through numerical examples.Furthermore,the research delves into the optimal capital allocation problem.
基金国家自然科学基金项目(No.81902513)山西省应用基础研究计划项目(No.202303021211114 and 202103021224228)山西省高等教育百亿工程“科技引导”专项(No.BYJL047)资助。
文摘Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8^(+)T cell immune infiltration and immune suppression.We constructed a CD8^(+)T cells related risk score model to predict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8^(+)T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS 2,and TNFRSF1B was constructed.The risk score model was well validated through an independent external validation cohort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P<0.0001)and lower CD8^(+)T cells infiltration(P<0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P<0.01).Drug sensitivity analysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene model was verified by immunohistochemistry.In summary,the establishment and validation of a CD8^(+)T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.
基金Supported by the Research Fund of Qiannan Medical College for Nationalities,No.Qnyz202222.
文摘BACKGROUND Colorectal cancer(CRC)is one of the most prevalent and lethal malignant tumors worldwide.Currently,surgical intervention was the primary treatment modality for CRC.However,increasing studies have revealed that CRC patients may experience postoperative cognitive dysfunction(POCD).AIM To establish a risk prediction model for POCD in CRC patients and investigate the preventive value of dexmedetomidine(DEX).METHODS A retrospective analysis was conducted on clinical data from 140 CRC patients who underwent surgery at the People’s Hospital of Qian Nan from February 2020 to May 2024.Patients were allocated into a modeling group(n=98)and a validation group(n=42)in a 7:3 ratio.General clinical data were collected.Additionally,in the modeling group,patients who received DEX preoperatively were incorporated into the observation group(n=54),while those who did not were placed in the control group(n=44).The incidence of POCD was recorded for both cohorts.Data analysis was performed using statistical product and service solutions 20.0,with t-tests orχ^(2) tests employed for group comparisons based on the data type.Least absolute shrinkage and selection operator regression was applied to identify influencing factors and reduce the impact of multicollinear predictors among variables.Multivariate analysis was carried out using Logistic regression.Based on the identified risk factors,a risk prediction model for POCD in CRC patients was developed,and the predictive value of these risk factors was evaluated.RESULTS Significant differences were observed between the cognitive dysfunction group and the non-cognitive dysfunction group in diabetes status,alcohol consumption,years of education,anesthesia duration,intraoperative blood loss,intraoperative hypoxemia,use of DEX during surgery,intraoperative use of vasoactive drugs,surgical time,systemic inflammatory response syndrome(SIRS)score(P<0.05).Multivariate Logistic regression analysis identified that diabetes[odds ratio(OR)=4.679,95%confidence interval(CI)=1.382-15.833],alcohol consumption(OR=5.058,95%CI:1.255-20.380),intraoperative hypoxemia(OR=4.697,95%CI:1.380-15.991),no use of DEX during surgery(OR=3.931,95%CI:1.383-11.175),surgery duration≥90 minutes(OR=4.894,95%CI:1.377-17.394),and a SIRS score≥3(OR=4.133,95%CI:1.323-12.907)were independent risk factors for POCD in CRC patients(P<0.05).A risk prediction model for POCD was constructed using diabetes,alcohol consumption,intraoperative hypoxemia,non-use of DEX during surgery,surgery duration,and SIRS score as factors.A receiver operator characteristic curve analysis of these factors revealed the model’s predictive sensitivity(88.56%),specificity(70.64%),and area under the curve(AUC)(AUC=0.852,95%CI:0.773-0.919).The model was validated using 42 CRC patients who met the inclusion criteria,demonstrating sensitivity(80.77%),specificity(81.25%),and accuracy(80.95%),and AUC(0.805)in diagnosing cognitive impairment,with a 95%CI:0.635-0.896.CONCLUSION Logistic regression analysis identified that diabetes,alcohol consumption,intraoperative hypoxemia,non-use of DEX during surgery,surgery duration,and SIRS score vigorously influenced the occurrence of POCD.The risk prediction model based on these factors demonstrated good predictive performance for POCD in CRC individuals.This study offers valuable insights for clinical practice and contributes to the prevention and management of POCD under CRC circumstances.
基金Supported by the 2024 Yiwu City Research Plan Project,No.24-3-102.
文摘BACKGROUND Rabies is a zoonotic viral disease affecting the central nervous system,caused by the rabies virus,with a case-fatality rate of 100%once symptoms appear.AIM To analyze high-risk factors associated with mental disorders induced by rabies vaccination and to construct a risk prediction model to inform strategies for improving patients’mental health.METHODS Patients who received rabies vaccinations at the Department of Infusion Yiwu Central Hospital between August 2024 and July 2025 were included,totaling 384 cases.Data were collected from medical records and included demographic characteristics(age,gender,occupation),lifestyle habits,and details regarding vaccine type,dosage,and injection site.The incidence of psychiatric disorders following vaccination was assessed using standardized anxiety and depression rating scales.Patients were categorized into two groups based on the presence or absence of anxiety and depression symptoms:The psychiatric disorder group and the non-psychiatric disorder group.Differences between the two groups were compared,and high-risk factors were identified using multivariate logistic regression analysis.A predictive model was then developed based on these factors to evaluate its predictive performance.RESULTS Among the 384 patients who received rabies vaccinations,36 cases(9.38%)were diagnosed with anxiety,52 cases(13.54%)with depression,and 88 cases(22.92%)with either condition.Logistic regression analysis identified the following signi ficant risk factors for psychiatric disorders:Education level of primary school or below,exposure site at the head and neck,exposure classified as grade III,family status of divorced/widowed/unmarried/living alone,number of wounds greater than one,and low awareness of rabies prevention and control(P<0.05).The risk prediction model demonstrated good performance,with an area under the receiver operating characteristic curve of 0.859,a specificity of 74.42%,and a sensitivity of 93.02%.CONCLUSION In real-world settings,psychiatric disorders following rabies vaccination are relatively common and are associated with factors such as lower education level,higher exposure severity,vulnerable family status,and limited awareness of rabies prevention and control.The developed risk prediction model may aid in early identification of high-risk individuals and support timely clinical intervention.
文摘BACKGROUND This study aimed to compare and analyze risk factors for pancreatic fistula following pancreaticoduodenectomy(PD)using different definition criteria,and to develop a predictive model for standardized pancreatic fistula risk assessment.AIM To identify and compare risk factors for postoperative pancreatic fistula(POPF)following PD using both the 2005 International Study Group of Pancreatic Fistula and updated 2016 International Study Group on Pancreatic Surgery diagnostic criteria,and to develop a clinically applicable predictive model based on objective preoperative parameters for standardized pancreatic fistula risk assessment and perioperative management optimization.METHODS We conducted a retrospective analysis of 303 patients who underwent PD at CR&WISCO General Hospital between January 2017 and May 2023.POPF cases were classified according to both previous and updated diagnostic standards.For statistical analysis,we employed t-tests or Mann-Whitney U tests for continuous variables andχ^(2) tests for categorical data.To identify risk factors associated with POPF under both classification systems,we performed univariate and multivariate logistic regression analyses.RESULTS Univariate analysis identified several factors associated with POPF:Main pancreatic duct diameter(χ^(2)=31.641,P<0.001),main pancreatic duct index(χ^(2)=52.777,P<0.001),portal vein invasion(χ^(2)=6.259,P=0.012),intra-abdominal fat thickness(χ^(2)=7.665,P=0.006),preoperative biliary drainage(χ^(2)=5.999,P=0.014),pancreatic characteristics(χ^(2)=5.544,P=0.019),pancreatic resection margin thickness(t=2.055,P=0.032),pancreatic computed tomography(CT)value(t=-3.224,P=0.002),and preoperative blood amylase level(Z=-2.099,P=0.036).Multivariate logistic regression identified three independent risk factors:Main pancreatic duct index[odds ratio(OR)=0.000,95%confidence interval(CI):0.000-0.011],pancreatic cancer[OR=4.843,95%CI:1.285-18.254],and pancreatic CT value[OR=0.869,95%CI:0.806-0.937](all P<0.05).CONCLUSION The main pancreatic duct index and pancreatic CT value are strongly correlated with pancreatic fistula development after PD.
基金funded by the National College Students Innovation and Entrepreneurship Training Program(S202310760049).
文摘This article introduces and compares risk assessment models for venous thromboembolism in gynecological patients at home and abroad.The models assessed included the Caprini risk assessment model,the G-Caprini risk assessment model,the Rogers risk assessment model,the Autar risk assessment model,the gynecological patient surgical venous thrombosis risk assessment scale,the Wells score,the COMPASS-CAT thrombus risk assessment model,the Khorana risk assessment model,the Padua risk assessment model,and the Chaoyang model.The purpose of this study is to provide a foundation for developing a risk assessment tool for gynecological venous thromboembolism tailored to Chinese patients and to assist clinical health care workers in selecting appropriate risk assessment tools and guiding individualized prevention measures.
基金supported by China-Pakistan joint program of the Chi-nese Academy of Sciences(Grant No.046GJHZ2023069MI)National Natural Science Foundation of China(Grant No.42371145)the program of the Key Laboratory of Cryospheric Science and Frozen Soil Engineering,CAS(Grant No.CSFSE-ZZ-2402).
文摘Snowmelt runoffis an important component of water resources in the Northwest China(NWC).With global cli-mate warming and the increasing frequency of extreme events,snowmelt floods have caused significant damage.However,current studies lack comprehensive research and systematic risk assessments of snowmelt floods across the NWC.Based on the snowmelt runoffsimulated by GLDAS-NOAH model(1948-2022),the multiple indicators of snowmelt floods were retrieved by Peaks Over Threshold(POT)model in the NWC,and comprehensive risk assessment was conducted by integrating socio-economic data.The results indicated that the snowmelt runoffin the NWC shows a significant increasing trend and exhibits a spatial pattern of being more abundant in the northwest and southwest edges while less in the central and eastern regions.In Northern Xinjiang,snowmelt floods occurred relatively infrequently but with large magnitudes,while around the Qilian Mountains,snowmelt floods were more frequent but of smaller magnitudes.The longest duration of snowmelt floods was observed in the Kashgar and Yarkant River.Basins near mountainous areas are prone to snowmelt floods,especially the Tongtian and Lancang River basins,as well as the Ebinur Lake,Ili River basin,and the rivers south of the Altai Mountains,which face the highest risk of snowmelt floods.Based on comprehensive assessment of hazard,expo-sure,vulnerability and adaptability,high and very high-risk areas account for 15.5%of the NWC.It is urgent to enhance monitoring,early warning systems,and implement corresponding disaster prevention and mitigation measures in large mountainous basins.
基金Supported by the Chongqing Municipal Health Commission Project,No.2024WSJK017.
文摘BACKGROUND Unplanned extubation(UE)after endoscopic retrograde cholangiopancreatography plus endoscopic nasobiliary drainage(ENBD)increases patient morbidity and prolongs hospitalization duration.AIM To construct a risk prediction model for UE in patients undergoing ENBD to provide evidence for clinical nursing.METHODS A multicenter retrospective study was conducted,collecting data from 981 patients undergoing ENBD from three hospitals in Chongqing from January 2018 to June 2024,randomly allocated to modeling and validation groups in a 7:3 ratio.Logistic regression analysis was used to screen independent risk factors,construct prediction models,and draw nomograms.RESULTS The overall incidence of UE was 6.12%(60/981).The majority(70.00%)of extubations occurred within 24-72 h postoperatively.Multivariate logistic regression analysis identified age≥61 years[odds ratio(OR)=2.341,95%confidence interval(CI):1.28-4.27],smoking history(OR=2.876,95%CI:1.54-5.37),prolonged fasting time(OR=1.124,95%CI:1.05-1.20),prolonged catheter duration(OR=1.286,95%CI:1.09-1.52),and consciousness changes(OR=3.152,95%CI:1.69-5.89)were independent risk factors while serum albumin was a protective factor(OR=0.912,95%CI:0.87-0.95).The model receiver operating characteristic area under curve was 0.881 with accuracy of 80.36%,sensitivity of 83.59%,and specificity of 74.88%.A nomogram total score≥199 points corresponded to a high-risk threshold.CONCLUSION The six-factor risk prediction model had good discrimination and accuracy,which can provide clinical nursing staff with scientific evidence to identify patients at high risk and help reduce the incidence of UE.
文摘This editorial critically evaluated the recent study by Wang et al,which systematically investigated the efficacy of perioperative disinfection and isolation measures(including preoperative povidone-iodine disinfection,intraoperative sterile barrier techniques,and postoperative intensive care)in reducing infection rates.The study further incorporated the surgical site infection risk prediction model(constructed via the least absolute shrinkage and selection operator al-gorithm,integrating patients'baseline characteristics,surgical indicators,and regional antibiotic-resistant bacterial data),and proposed a dynamic prevention and control system termed“disinfection protocols-predictive models–real-time monitoring”.The article highlighted that preoperative risk stratification,intraoperative personalized antibiotic selection,and postoperative multidimensional monitoring(encompassing inflammatory biomarkers,imaging,and microbiological testing)enabled the precise identification of high-risk patients and optimized intervention thresholds.Future research is deemed necessary to validate the synergistic effects of disinfection protocols and predictive models through large-scale multicenter studies,combined with advanced intraoperative rapid microbial detection technologies.This approach aims to establish standardized infection control protocols tailored for precision medicine and regional adaptability.Future research should prioritize validating the synergistic effects of disinfection protocols and predictive models via multi-center studies,while incorporating advanced rapid intraoperative microbial detection technologies to develop standardized infection prevention and control procedures.Such efforts will enhance the implementation of precise and regionally adaptive infection control strategies.
基金Supported by the Science and Technology Major Project of Changzhou Science and Technology Bureau,No.CE20205047Natural Science Foundation of Xinjiang Uygur Autonomous Region,No.2022D01F52Changzhou A Major Scientific Research Project of the Municipal Health Commission,No.ZD202220.
文摘BACKGROUND Coronary heart disease(CHD)is a prevalent type 2 diabetes mellitus(T2DM)complication.Further,the risk stratification before angiography may help diagnose T2DM with CHD early.However,few studies have investigated the coronary imaging characteristics and risk factors of patients with T2DM complicated with CHD.AIM To compare the differences in coronary imaging between patients with T2DM with and without CHD,determine the risk factors of T2DM complicated with CHD,and establish a predictive tool for diagnosing CHD in T2DM.METHODS This study retrospectively analyzed 103 patients with T2DM from January 2022 to May 2024.They are categorized based on CHD occurrence into:(1)The control group,consisting of patients with T2DM without CHD;and(2)The observation group,which includes patients with T2MD with CHD.Age,sex,smoking and drinking history,CHD family history,metformin(MET)treatment pre-admission,body mass index,fasting blood glucose(FBG),triglyceride(TG),total cholesterol,high-density lipoprotein cholesterol,low-density lipoprotein cholesterol(LDL-C),serum creatinine,blood urea nitrogen(BUN),alanine aminotransferase,aspartate aminotransferase,glycosylated hemoglobin(HbA1c),and coronary imaging data of both groups were collected from the medical record system.Logistic risk analysis was conducted to screen risk factors.The prediction model’s prediction efficiency was evaluated with receiver operating characteristic curves.RESULTS The control and observation groups consisted of 48 and 55 cases,respectively.The two groups were statistically different in terms of age(t=2.006,P=0.048),FBG(t=6.038,P=0.000),TG(t=2.015,P=0.047),LDL-C(t=2.017,P=0.046),and BUN(t=2.035,P=0.044).The observation group demonstrated lower proportions of patients receiving MET(χ^(2)=5.073,P=0.024)and higher proportions of patients with HbA1c of>7.0%(χ^(2)=6.980,P=0.008)than the control group.The observation group consisted of 15,17,and 23 cases of moderate stenosis,severe stenosis,and occlusion,respectively,with a greater number of coronary artery occlusion cases than the control group(χ^(2)=6.399,P=0.041).The observation group consisted significantly higher number of diffuse lesion cases at 35 compared with the control group(χ^(2)=15.420,P=0.000).The observation group demonstrated a higher right coronary artery(RCA)stenosis index(t=6.730,P=0.000),circumflex coronary artery(LCX)stenosis index(t=5.738,P=0.000),and total stenosis index(t=7.049,P=0.000)than the control group.FBG[odds ratio(OR)=1.472;95%confidence interval(CI):1.234-1.755;P=0.000]and HbA1c(OR=3.197;95%CI:1.149-8.896;P=0.026)were independent risk factors for T2DM complicated with CHD,whereas MET(OR=0.350;95%CI:0.129-0.952;P=0.040)was considered a protective factor for CHD in T2DM.CONCLUSION Coronary artery occlusion is a prevalent complication in patients with T2DM.Patients with T2MD with CHD demonstrated a higher degree of RCA and LCX stenosis than those with T2DM without CHD.FBG,HbA1c,and MET treatment history are risk factors for T2DM complicated with CHD.
基金Key Project of Fujian Provincial University Application Technology Engineering Center for E-commerce,“Research on Improving the Risk Relationship Model of Localized Audit Risk Factors in the Digital Economy Background”(Project number:DZSW24-3).
文摘Based on the objective reality that audit risk responsibility has mainly been attributed to certified public accountants in the past,and audit standards have not specifically divided the entities responsible for audit risk responsibility,combined with the understanding of the types of audit risk elements related to audit standards,the differences in the understanding of audit risk and its relationship model application caused by the different audit cultures in China and the West have led to a bias of Chinese certified public accountants to bear inspection risks,which affects their professional enthusiasm and continues to cause accounting firms to be lazy in audit quality management.Based on this,literature research,case analysis,and logical deduction methods were used to redefine the concept of audit risk from the perspective of risk responsibility subjects.The traditional audit risk elements and their relationship models were briefly introduced,and the identification of audit risk elements and optimization of audit risk relationship models were systematically demonstrated.
文摘Objective:To study the risk prediction model for multiple bronchoalveolar lavage in children with mycoplasma pneumoniae pneumonia(MPP).Methods:151 pediatric patients with MPP admitted in our hospital from July to December 2023 were selected,the incidence rate of multiple bronchoalveolar lavage was recorded.A logistic multivariate regression model was employed to analyze relevant factors and construct a risk prediction model for multiple bronchoalveolar lavage in children with MPP.Results:Among 151 children with MPP,64 cases underwent multiple bronchoalveolar lavage,accounting for 42.38%.The Logistic multivariate model analysis revealed that the pleural effusion,sepsis,and abnormally elevated serum levels of LDH and D-D were independent influence factors for multiple bronchoalveolar lavage in children with MPP(p<0.05),based on this,a Nomogram prediction model can be established.The ROC analysis results showed that the AUC of the model to judge the multiple bronchoalveolar lavage in MPP patients was 0.828(SE=0.035,95%CI=0.760-0.896,p<0.001),the sensitivity was 0.813 and the specificity was 0.759.Conclusion:The multiple bronchoscopic bronchoalveolar lavage in MPP patients are associated with the levels of LDH and D-D,as well as the presence of pleural effusion and sepsis complications,the risk prediction model established,which based on this has high accuracy.
文摘The urgent necessity for enhanced risk stratification to improve the efficiency of colonoscopy screening is underscored by the fact that colorectal cancer(CRC)continues to be a primary cause of global cancer mortality.Conventional models mostly rely on generalized obesity markers including body mass index(BMI),which does not effectively represent oncogenic risk linked with abdominal obesity.Liu et al undertook a large-scale case-control study comprising 6484 firsttime colonoscopy patients at a prominent Chinese hospital between 2020 and 2023 to overcome this restriction.Age,male sex,smoking status,and raised waist-hip ratio(WHR)were found by multivariate logistic regression as independent predictors of advanced colorectal neoplasia(ACN).In a validation cohort of 1891 individuals,a new 7-point risk scoring model was created and stratified into low-(5.0%)ACN prevalence,moderate-(10.3%)and high-risk(17.6%).With C-statistic=0.66 the model showed better discriminating ability than the Asia-Pacific Colorectal Screening(APCS)score(C-statistic=0.63)and the BMI-modified APCS model.These results fit newly published data showing central obesity as a major carcinogenic driver via pro-inflammatory visceral adipokine channels.With the use of WHR,patient risk classification is greatly improved,providing a practical tool to make the most of screening resources in the face of rising CRC incidence rates.Finally,multi-ethnic validation is necessary for the WHR-based scoring model to be considered for integration into global CRC preventive frameworks,since it improves the accuracy of ACN risk prediction.
