Using Fourier inversion transform, P.D.E. and Feynman-Kac formula, the closedform solution for price on European call option is given in a double exponential jump-diffusion model with two different market structure ri...Using Fourier inversion transform, P.D.E. and Feynman-Kac formula, the closedform solution for price on European call option is given in a double exponential jump-diffusion model with two different market structure risks that there exist CIR stochastic volatility of stock return and Vasicek or CIR stochastic interest rate in the market. In the end, the result of the model in the paper is compared with those in other models, including BS model with numerical experiment. These results show that the double exponential jump-diffusion model with CIR-market structure risks is suitable for modelling the real-market changes and very useful.展开更多
This paper studies the critical exercise price of American floating strike lookback options under the mixed jump-diffusion model. By using It formula and Wick-It-Skorohod integral, a new market pricing model estab...This paper studies the critical exercise price of American floating strike lookback options under the mixed jump-diffusion model. By using It formula and Wick-It-Skorohod integral, a new market pricing model established under the environment of mixed jumpdiffusion fractional Brownian motion. The fundamental solutions of stochastic parabolic partial differential equations are estimated under the condition of Merton assumptions. The explicit integral representation of early exercise premium and the critical exercise price are also given, then the American floating strike lookback options factorization formula is obtained, the results is generalized the classical Black-Scholes market pricing model.展开更多
Due to complex geological structures and a narrow safe mud density window,offshore fractured formations frequently encounter severe lost circulation(LC)during drilling,significantly hindering oil and gas exploration a...Due to complex geological structures and a narrow safe mud density window,offshore fractured formations frequently encounter severe lost circulation(LC)during drilling,significantly hindering oil and gas exploration and development.Predicting LC risks enables the targeted implementation of mitigation strategies,thereby reducing the frequency of such incidents.To address the limitations of existing 3D geomechanical modeling in predicting LC,such as arbitrary factor selection,subjective weight assignment,and the inability to achieve pre-drilling prediction along the entire well section,an improved prediction method is proposed.This method integrates multi-source data and incorporates three LC-related sensitivity factors:fracture characteristics,rock brittleness,and in-situ stress conditions.A quantitative risk assessment model for LC is developed by combining the subjective analytic hierarchy process with the objective entropy weight method(EWM)to assign weights.Subsequently,3D geomechanical modeling is applied to identify regional risk zones,enabling digital visualization for pre-drilling risk prediction.The developed 3D LC risk prediction model was validated using actual LC incidents from drilled wells.Results were generally consistent with field-identified LC zones,with an average relative error of 19.08%,confirming its reliability.This method provides practical guidance for mitigating potential LC risks and optimizing drilling program designs in fractured formations.展开更多
China’s healthcare system faces increasing challenges,including surging medical costs,resource allocation imbalances favoring large hospitals,and ineffective referral mechanisms.The lack of a unified strategy integra...China’s healthcare system faces increasing challenges,including surging medical costs,resource allocation imbalances favoring large hospitals,and ineffective referral mechanisms.The lack of a unified strategy integrating standardized coverage with personalized payment compounds these issues.To this end,this study proposes a risk-sharing reform strategy that combines equal coverage for the same disease(ECSD)with an individualized out-of-pocket(I-OOP)model.Specifically,the study employs a Markov model to capture patient transitions across health states and care levels.The findings show that ECSD and I-OOP enhance equity by standardizing disease coverage while tailoring costs to patient income and facility type.This approach alleviates demand on high-tier hospitals,promoting primary care utilization and enabling balanced resource distribution.The study’s findings provide a reference for policymakers and healthcare administrators by presenting a scalable framework that is aligned with China’s development goals with the aim of fostering an efficient,sustainable healthcare system that is adaptable to regional needs.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
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
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 Liver transplantation aims to increase the survival of patients with end-stage liver diseases and improve their quality of life.The number of organs available for transplantation is lower than the demand.To...BACKGROUND Liver transplantation aims to increase the survival of patients with end-stage liver diseases and improve their quality of life.The number of organs available for transplantation is lower than the demand.To provide fair organ distribution,predictive mortality scores have been developed.AIM To compare the Acute Physiology and Chronic Health Evaluation IV(APACHE IV),balance of risk(BAR),and model for end-stage liver disease(MELD)scores as predictors of mortality.METHODS Retrospective cohort study,which included 283 adult patients in the postoperative period of deceased donor liver transplantation from 2014 to 2018.RESULTS The transplant recipients were mainly male,with a mean age of 58.1 years.Donors were mostly male,with a mean age of 41.6 years.The median cold ischemia time was 3.1 hours,and the median intensive care unit stay was 5 days.For APACHE IV,a mean of 59.6 was found,BAR 10.7,and MELD 24.2.The 28-day mortality rate was 9.5%,and at 90 days,it was 3.5%.The 28-day mortality prediction for APACHE IV was very good[area under the curve(AUC):0.85,P<0.001,95%CI:0.76-0.94],P<0.001,BAR(AUC:0.70,P<0.001,95%CI:0.58–0.81),and MELD(AUC:0.66,P<0.006,95%CI:0.55-0.78),P<0.008.At 90 days,the data for APACHE IV were very good(AUC:0.80,P<0.001,95%CI:0.71–0.90)and moderate for BAR and MELD,respectively,(AUC:0.66,P<0.004,95%CI:0.55–0.77),(AUC:0.62,P<0.026,95%CI:0.51–0.72).All showed good discrimination between deaths and survivors.As for the best value for liver transplantation,it was significant only for APACHE IV(P<0.001).CONCLUSION The APACHE IV assessment score was more accurate than BAR and MELD in predicting mortality in deceased donor liver transplant recipients.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 Sepsis is a severe complication in hospitalized patients with diabetic foot(DF),often associated with high morbidity and mortality.Despite its clinical significance,limited tools exist for early risk predic...BACKGROUND Sepsis is a severe complication in hospitalized patients with diabetic foot(DF),often associated with high morbidity and mortality.Despite its clinical significance,limited tools exist for early risk prediction.AIM To identify key risk factors and evaluate the predictive value of a nomogram model for sepsis in this population.METHODS This retrospective study included 216 patients with DF admitted from January 2022 to June 2024.Patients were classified into sepsis(n=31)and non-sepsis(n=185)groups.Baseline characteristics,clinical parameters,and laboratory data were analyzed.Independent risk factors were identified through multivariable logistic regression,and a nomogram model was developed and validated.The model's performance was assessed by its discrimination(AUC),calibration(Hosmer-Lemeshow test,calibration plots),and clinical utility[decision curve analysis(DCA)].RESULTS The multivariable analysis identified six independent predictors of sepsis:Diabetes duration,DF Texas grade,white blood cell count,glycated hemoglobin,Creactive protein,and albumin.A nomogram integrating these factors achieved excellent diagnostic performance,with an AUC of 0.908(95%CI:0.865-0.956)and robust internal validation(AUC:0.906).Calibration results showed strong agreement between predicted and observed probabilities(Hosmer-Lemeshow P=0.926).DCA demonstrated superior net benefit compared to extreme intervention scenarios,highlighting its clinical utility.CONCLUSION The nomogram prediction model,based on six key risk factors,demonstrates strong predictive value,calibration,and clinical utility for sepsis in patients with DF.This tool offers a practical approach for early risk stratification,enabling timely interventions and improved clinical management in this high-risk population.展开更多
BACKGROUND Colorectal polyps(CPs)are important precursor lesions of colorectal cancer,and endoscopic surgery remains the primary treatment option.However,the shortterm recurrence rate post-surgery is high,and the risk...BACKGROUND Colorectal polyps(CPs)are important precursor lesions of colorectal cancer,and endoscopic surgery remains the primary treatment option.However,the shortterm recurrence rate post-surgery is high,and the risk factors for recurrence remain unknown.AIM To comprehensively explore risk factors for short-term recurrence of CPs after endoscopic surgery and develop a nomogram prediction model.METHODS Overall,362 patients who underwent endoscopic polypectomy between January 2022 and January 2024 at Nanjing Jiangbei Hospital were included.We screened basic demographic data,clinical and polyp characteristics,surgery-related information,and independent risk factors for CPs recurrence using univariate and multivariate logistic regression analyses.The multivariate analysis results were used to construct a nomogram prediction model,internally validated using Bootstrapping,with performance evaluated using area under the curve(AUC),calibration curve,and decision curve analysis.RESULTS CP re-occurred in 166(45.86%)of the 362 patients within 1 year post-surgery.Multivariate logistic regression analysis showed that age(OR=1.04,P=0.002),alcohol consumption(OR=2.07,P=0.012),Helicobacter pylori infection(OR=2.34,P<0.001),polyp number>2(OR=1.98,P=0.005),sessile polyps(OR=2.10,P=0.006),and adenomatous pathological type(OR=3.02,P<0.001)were independent risk factors for post-surgery recurrence.The nomogram prediction model showed good discriminatory(AUC=0.73)and calibrating power,and decision curve analysis showed that the model had good clinical benefit at risk probabilities>20%.CONCLUSION We identified multiple independent risk factors for short-term recurrence after endoscopic surgery.The nomogram prediction model showed a certain degree of differentiation,calibration,and potential clinical applicability.展开更多
Scale effects and evaluation models are crucial to the accuracy of landscape ecological risk evaluation.However,most studies conduct these evaluations at a single scale or with a single model,ignoring potential scale ...Scale effects and evaluation models are crucial to the accuracy of landscape ecological risk evaluation.However,most studies conduct these evaluations at a single scale or with a single model,ignoring potential scale effects and changes in landscape patterns.To address this,we took the Leshan City in Sichuan Province of China as a study case.We determined that the optimal spatial granularity for the study area is 150 m by analyzing the sensitivities of eight landscape pattern indices such as landscape fragmentation,landscape spreading,and Shannon's diversity at different spatial granularities,and employing the inflection point identification method.Building on this,we constructed a landscape pattern index model(ERI model)and a landscape pattern index model coupled with the ecological process of soil erosion(SI-ERI model)by incorporating the natural geographic factors of the study area.We used the ERI and SI-ERI models to evaluate the landscape ecological risk of Leshan City across multiple scales,including ecological,administrative,and sample scales.After conducting overlay and spatial autocorrelation analyses of the multi-scale evaluation results,we determined that the administrative scale is optimal for evaluating landscape ecological risk in the study area.At this scale,we verified the accuracy and reliability of the two models'evaluation results against the actual ecological environment in typical areas within the study area.The findings indicated that the SI-ERI model provided more precise and accurate spatial characterization,effectively reflecting the actual landscape ecological risk of Leshan City.According to the SI-ERI model's evaluation results at the administrative scale,Leshan City's overall risk level is relatively low,with good ecological environmental quality.Low-risk areas constitute 56.16%and medium-low-risk areas make up 23.81%,aligning closely with the city's actual situation.This study thus offers a scientific basis and theoretical reference for managing ecological risks and planning urban development in Leshan City.展开更多
BACKGROUND Type 2 diabetes mellitus(T2DM)is a prevalent metabolic disorder increasingly linked with hypertension,posing significant health risks.The need for a predictive model tailored for T2DM patients is evident,as...BACKGROUND Type 2 diabetes mellitus(T2DM)is a prevalent metabolic disorder increasingly linked with hypertension,posing significant health risks.The need for a predictive model tailored for T2DM patients is evident,as current tools may not fully capture the unique risks in this population.This study hypothesizes that a nomogram incorporating specific risk factors will improve hypertension risk prediction in T2DM patients.AIM To develop and validate a nomogram prediction model for hypertension in T2DM patients.METHODS A retrospective observational study was conducted using data from 26850 T2DM patients from the Anhui Provincial Primary Medical and Health Information Management System(2022 to 2024).The study included patients aged 18 and above with available data on key variables.Exclusion criteria were type 1 diabetes,gestational diabetes,insufficient data,secondary hypertension,and abnormal liver and kidney function.The Least Absolute Shrinkage and Selection Operator regression and multivariate logistic regression were used to construct the nomogram,which was validated on separate datasets.RESULTS The developed nomogram for T2DM patients incorporated age,low-density lipoprotein,body mass index,diabetes duration,and urine protein levels as key predictive factors.In the training dataset,the model demonstrated a high discriminative power with an area under the receiver operating characteristic curve(AUC)of 0.823,indicating strong predictive accuracy.The validation dataset confirmed these findings with an AUC of 0.812.The calibration curve analysis showed excellent agreement between predicted and observed outcomes,with absolute errors of 0.017 for the training set and 0.031 for the validation set.The Hosmer-Lemeshow test yielded non-significant results for both sets(χ^(2)=7.066,P=0.562 for training;χ^(2)=6.122,P=0.709 for validation),suggesting good model fit.CONCLUSION The nomogram effectively predicts hypertension risk in T2DM patients,offering a valuable tool for personalized risk assessment and guiding targeted interventions.This model provides a significant advancement in the management of T2DM and hypertension comorbidity.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
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 The computed tomography(CT)-based preoperative risk score was developed to predict recurrence after upfront surgery in patients with resectable pancreatic ductal adenocarcinoma(PDAC)in South Korea.However,w...BACKGROUND The computed tomography(CT)-based preoperative risk score was developed to predict recurrence after upfront surgery in patients with resectable pancreatic ductal adenocarcinoma(PDAC)in South Korea.However,whether it performs well in other countries remains unknown.AIM To externally validate the CT-based preoperative risk score for PDAC in a country outside South Korea.METHODS Consecutive patients with PDAC who underwent upfront surgery from January 2016 to December 2019 at our institute in a country outside South Korea were retrospectively included.The study utilized the CT-based risk scoring system,which incorporates tumor size,portal venous phase density,tumor necrosis,peripancreatic infiltration,and suspicious metastatic lymph nodes.Patients were categorized into prognosis groups based on their risk score,as good(risk score<2),moderate(risk score 2-4),and poor(risk score≥5).RESULTS A total of 283 patients were evaluated,comprising 170 males and 113 females,with an average age of 63.52±8.71 years.Follow-up was conducted until May 2023,and 76%of patients experienced tumor recurrence with median recurrence-free survival(RFS)of 29.1±1.9 months.According to the evaluation results of Reader 1,the recurrence rates were 39.0%in the good prognosis group,82.1%in the moderate group,and 84.5%in the poor group.In comparison,Reader 2 reported recurrence rates of 50.0%,79.5%,and 88.9%,respectively,across the same prognostic categories.The study validated the effectiveness of the risk scoring system,demonstrating better RFS in the good prognosis group.CONCLUSION This research validated that the CT-based preoperative risk scoring system can effectively predict RFS in patients with PDAC,suggesting that it may be valuable in diverse populations.展开更多
BACKGROUND:Acute kidney injury(AKI)is a severe and fatal complication of acute heart failure(AHF).Existing studies on AKI following AHF in the Chinese population have scarce insights available from the emergency depar...BACKGROUND:Acute kidney injury(AKI)is a severe and fatal complication of acute heart failure(AHF).Existing studies on AKI following AHF in the Chinese population have scarce insights available from the emergency department(ED).This study aimed to investigate the predictive factors of patients with AHF complicated with AKI in a Chinese ED cohort,and to establish a risk prediction model.METHODS:Hospitalized patients diagnosed with AHF in the ED from December 2016 to September 2023 were included.The overall dataset were divided into the training set and the testing set at a 7:3 ratio.Univariate and multivariate logistic regression analyses were performed to identify the risk factors for AKI in patients with AHF in the training set,leading to the development of a risk prediction model.The performance of the model was further assessed.RESULTS:A total of 789 patients with AHF were enrolled,with an AKI incidence of 29.7%.The mortality rates of the AKI and non-AKI groups were 23.1%and 7.6%,respectively.Logistic regression analysis showed that the levels of white blood cell(OR=2.368;95%CI:1.502-3.733,P<0.001),albumin(OR=2.669;95%CI:1.601-4.451,P<0.001),serum creatinine(OR=3.221;95%CI:1.935-5.363,P<0.001),and hemoglobin(OR=2.009;95%CI:1.259-3.205,P=0.003),maximum 24-h furosemide dosage(OR=2.196;95%CI:1.346-3.582,P=0.002),the use of non-invasive ventilation(OR=2.419;95%CI:1.454-4.024,P=0.001),and diabetes mellitus(OR=3.192;95%CI:2.014-5.059,P<0.001)were independent risk factors for AKI after AHF.These factors were subsequently incorporated into a risk prediction model.The area under the receiver operating characteristic(AUROC)curve for the predictive model was 0.815(95%CI:0.776-0.854)and 0.802(95%CI:0.776-0.854)in the training set and the testing set,respectively.CONCLUSION:This risk prediction model might assist physician to predict AKI following AHF effectively in the emergency setting.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
BACKGROUND Breast cancer(BC)is the second most common malignancy globally.Young and middle-aged patients face more pressures from diagnosis,treatment,costs,and psychological issues like self-image concerns,social barr...BACKGROUND Breast cancer(BC)is the second most common malignancy globally.Young and middle-aged patients face more pressures from diagnosis,treatment,costs,and psychological issues like self-image concerns,social barriers,and professional challenges.Compared to other age groups,they have higher recurrence rates,lower survival rates,and increased risk of depression.Research is lacking on factors influencing depressive symptoms and predictive models for this age group.AIM To analyze factors influencing depressive symptoms in young/middle-aged BC patients and construct a depression risk predictive model.METHODS A total of 360 patients undergoing BC treatment at two tertiary hospitals in Jiangsu Province,China from November 2023 to April 2024 were included in the study.Participants were surveyed using a general information questionnaire,the patient health questionnaire depression scale,the visual analog scale for pain,the revised family support scale,and the long form of the international physical activity questionnaire.Univariate and multivariate analyses were conducted to identify the factors affecting depression in middle-aged and young BC patients,and a predictive model for depression risk was developed based on these findings.RESULTS Among the 360 middle-aged and young BC patients,the incidence rate of depressive symptoms was 38.61%(139/360).Multivariate analysis revealed that tumor grade,patient’s monthly income,pain score,family support score,and physical activity score were factors influencing depression in this patient group(P<0.05).The risk prediction model constructed based on these factors yielded an area under the receiver operating characteristic curve of 0.852,with a maximum Youden index of 0.973,sensitivity of 86.80%,specificity of 89.50%,and a diagnostic odds ratio of 0.552.The Hosmer-Lemeshow test for goodness of fit indicated an adequate model fit(χ^(2)=0.360,P=0.981).CONCLUSION The constructed predictive model demonstrates good predictive performance and can serve as a reference for medical professionals to early identify high-risk patients and implement corresponding preventive measures to decrease the incidence of depressive symptoms in this population.展开更多
基金Supported by the NNSF of China(40675023)the PHD Foundation of Guangxi Normal University.
文摘Using Fourier inversion transform, P.D.E. and Feynman-Kac formula, the closedform solution for price on European call option is given in a double exponential jump-diffusion model with two different market structure risks that there exist CIR stochastic volatility of stock return and Vasicek or CIR stochastic interest rate in the market. In the end, the result of the model in the paper is compared with those in other models, including BS model with numerical experiment. These results show that the double exponential jump-diffusion model with CIR-market structure risks is suitable for modelling the real-market changes and very useful.
基金Supported by the Fundamental Research Funds of Lanzhou University of Finance and Economics(Lzufe2017C-09)
文摘This paper studies the critical exercise price of American floating strike lookback options under the mixed jump-diffusion model. By using It formula and Wick-It-Skorohod integral, a new market pricing model established under the environment of mixed jumpdiffusion fractional Brownian motion. The fundamental solutions of stochastic parabolic partial differential equations are estimated under the condition of Merton assumptions. The explicit integral representation of early exercise premium and the critical exercise price are also given, then the American floating strike lookback options factorization formula is obtained, the results is generalized the classical Black-Scholes market pricing model.
基金supported by the National Natural Science Foundation of China(No.52074312)the CNPC Science and Technology Innovation Foundation(No.2021DQ02-0505)+1 种基金the Open Fund Project of the National Key Laboratory for the Enrichment Mechanism and Efficient Development of Shale Oil and Gas(No.36650000-24-ZC0609-0006)the Major Science and Technology Project of Karamay City(No.20232023zdzx0003).
文摘Due to complex geological structures and a narrow safe mud density window,offshore fractured formations frequently encounter severe lost circulation(LC)during drilling,significantly hindering oil and gas exploration and development.Predicting LC risks enables the targeted implementation of mitigation strategies,thereby reducing the frequency of such incidents.To address the limitations of existing 3D geomechanical modeling in predicting LC,such as arbitrary factor selection,subjective weight assignment,and the inability to achieve pre-drilling prediction along the entire well section,an improved prediction method is proposed.This method integrates multi-source data and incorporates three LC-related sensitivity factors:fracture characteristics,rock brittleness,and in-situ stress conditions.A quantitative risk assessment model for LC is developed by combining the subjective analytic hierarchy process with the objective entropy weight method(EWM)to assign weights.Subsequently,3D geomechanical modeling is applied to identify regional risk zones,enabling digital visualization for pre-drilling risk prediction.The developed 3D LC risk prediction model was validated using actual LC incidents from drilled wells.Results were generally consistent with field-identified LC zones,with an average relative error of 19.08%,confirming its reliability.This method provides practical guidance for mitigating potential LC risks and optimizing drilling program designs in fractured formations.
基金The National Natural Science Foundation of China(No.72071042)。
文摘China’s healthcare system faces increasing challenges,including surging medical costs,resource allocation imbalances favoring large hospitals,and ineffective referral mechanisms.The lack of a unified strategy integrating standardized coverage with personalized payment compounds these issues.To this end,this study proposes a risk-sharing reform strategy that combines equal coverage for the same disease(ECSD)with an individualized out-of-pocket(I-OOP)model.Specifically,the study employs a Markov model to capture patient transitions across health states and care levels.The findings show that ECSD and I-OOP enhance equity by standardizing disease coverage while tailoring costs to patient income and facility type.This approach alleviates demand on high-tier hospitals,promoting primary care utilization and enabling balanced resource distribution.The study’s findings provide a reference for policymakers and healthcare administrators by presenting a scalable framework that is aligned with China’s development goals with the aim of fostering an efficient,sustainable healthcare system that is adaptable to regional needs.
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.
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 Liver transplantation aims to increase the survival of patients with end-stage liver diseases and improve their quality of life.The number of organs available for transplantation is lower than the demand.To provide fair organ distribution,predictive mortality scores have been developed.AIM To compare the Acute Physiology and Chronic Health Evaluation IV(APACHE IV),balance of risk(BAR),and model for end-stage liver disease(MELD)scores as predictors of mortality.METHODS Retrospective cohort study,which included 283 adult patients in the postoperative period of deceased donor liver transplantation from 2014 to 2018.RESULTS The transplant recipients were mainly male,with a mean age of 58.1 years.Donors were mostly male,with a mean age of 41.6 years.The median cold ischemia time was 3.1 hours,and the median intensive care unit stay was 5 days.For APACHE IV,a mean of 59.6 was found,BAR 10.7,and MELD 24.2.The 28-day mortality rate was 9.5%,and at 90 days,it was 3.5%.The 28-day mortality prediction for APACHE IV was very good[area under the curve(AUC):0.85,P<0.001,95%CI:0.76-0.94],P<0.001,BAR(AUC:0.70,P<0.001,95%CI:0.58–0.81),and MELD(AUC:0.66,P<0.006,95%CI:0.55-0.78),P<0.008.At 90 days,the data for APACHE IV were very good(AUC:0.80,P<0.001,95%CI:0.71–0.90)and moderate for BAR and MELD,respectively,(AUC:0.66,P<0.004,95%CI:0.55–0.77),(AUC:0.62,P<0.026,95%CI:0.51–0.72).All showed good discrimination between deaths and survivors.As for the best value for liver transplantation,it was significant only for APACHE IV(P<0.001).CONCLUSION The APACHE IV assessment score was more accurate than BAR and MELD in predicting mortality in deceased donor liver transplant recipients.
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.
文摘BACKGROUND Sepsis is a severe complication in hospitalized patients with diabetic foot(DF),often associated with high morbidity and mortality.Despite its clinical significance,limited tools exist for early risk prediction.AIM To identify key risk factors and evaluate the predictive value of a nomogram model for sepsis in this population.METHODS This retrospective study included 216 patients with DF admitted from January 2022 to June 2024.Patients were classified into sepsis(n=31)and non-sepsis(n=185)groups.Baseline characteristics,clinical parameters,and laboratory data were analyzed.Independent risk factors were identified through multivariable logistic regression,and a nomogram model was developed and validated.The model's performance was assessed by its discrimination(AUC),calibration(Hosmer-Lemeshow test,calibration plots),and clinical utility[decision curve analysis(DCA)].RESULTS The multivariable analysis identified six independent predictors of sepsis:Diabetes duration,DF Texas grade,white blood cell count,glycated hemoglobin,Creactive protein,and albumin.A nomogram integrating these factors achieved excellent diagnostic performance,with an AUC of 0.908(95%CI:0.865-0.956)and robust internal validation(AUC:0.906).Calibration results showed strong agreement between predicted and observed probabilities(Hosmer-Lemeshow P=0.926).DCA demonstrated superior net benefit compared to extreme intervention scenarios,highlighting its clinical utility.CONCLUSION The nomogram prediction model,based on six key risk factors,demonstrates strong predictive value,calibration,and clinical utility for sepsis in patients with DF.This tool offers a practical approach for early risk stratification,enabling timely interventions and improved clinical management in this high-risk population.
文摘BACKGROUND Colorectal polyps(CPs)are important precursor lesions of colorectal cancer,and endoscopic surgery remains the primary treatment option.However,the shortterm recurrence rate post-surgery is high,and the risk factors for recurrence remain unknown.AIM To comprehensively explore risk factors for short-term recurrence of CPs after endoscopic surgery and develop a nomogram prediction model.METHODS Overall,362 patients who underwent endoscopic polypectomy between January 2022 and January 2024 at Nanjing Jiangbei Hospital were included.We screened basic demographic data,clinical and polyp characteristics,surgery-related information,and independent risk factors for CPs recurrence using univariate and multivariate logistic regression analyses.The multivariate analysis results were used to construct a nomogram prediction model,internally validated using Bootstrapping,with performance evaluated using area under the curve(AUC),calibration curve,and decision curve analysis.RESULTS CP re-occurred in 166(45.86%)of the 362 patients within 1 year post-surgery.Multivariate logistic regression analysis showed that age(OR=1.04,P=0.002),alcohol consumption(OR=2.07,P=0.012),Helicobacter pylori infection(OR=2.34,P<0.001),polyp number>2(OR=1.98,P=0.005),sessile polyps(OR=2.10,P=0.006),and adenomatous pathological type(OR=3.02,P<0.001)were independent risk factors for post-surgery recurrence.The nomogram prediction model showed good discriminatory(AUC=0.73)and calibrating power,and decision curve analysis showed that the model had good clinical benefit at risk probabilities>20%.CONCLUSION We identified multiple independent risk factors for short-term recurrence after endoscopic surgery.The nomogram prediction model showed a certain degree of differentiation,calibration,and potential clinical applicability.
基金supported by grants from the Ministry of Science and Technology of the People’s Republic of China(Grant Nos.2019YFC1803500,2019YFC1803504)the Key R&D Projects of Sichuan Provincial Science and Technology Department(Grant Nos.2018SZ0298,2023YFS0390)+1 种基金the Bureau of Science and Technology Aba Qiang Tibetan Autonomous Prefecture(Grant Nos.R22YYJSYJ0004,R23YYJSYJ0010)Southwest University of Science and Technology Doctoral Program(23zx7175)。
文摘Scale effects and evaluation models are crucial to the accuracy of landscape ecological risk evaluation.However,most studies conduct these evaluations at a single scale or with a single model,ignoring potential scale effects and changes in landscape patterns.To address this,we took the Leshan City in Sichuan Province of China as a study case.We determined that the optimal spatial granularity for the study area is 150 m by analyzing the sensitivities of eight landscape pattern indices such as landscape fragmentation,landscape spreading,and Shannon's diversity at different spatial granularities,and employing the inflection point identification method.Building on this,we constructed a landscape pattern index model(ERI model)and a landscape pattern index model coupled with the ecological process of soil erosion(SI-ERI model)by incorporating the natural geographic factors of the study area.We used the ERI and SI-ERI models to evaluate the landscape ecological risk of Leshan City across multiple scales,including ecological,administrative,and sample scales.After conducting overlay and spatial autocorrelation analyses of the multi-scale evaluation results,we determined that the administrative scale is optimal for evaluating landscape ecological risk in the study area.At this scale,we verified the accuracy and reliability of the two models'evaluation results against the actual ecological environment in typical areas within the study area.The findings indicated that the SI-ERI model provided more precise and accurate spatial characterization,effectively reflecting the actual landscape ecological risk of Leshan City.According to the SI-ERI model's evaluation results at the administrative scale,Leshan City's overall risk level is relatively low,with good ecological environmental quality.Low-risk areas constitute 56.16%and medium-low-risk areas make up 23.81%,aligning closely with the city's actual situation.This study thus offers a scientific basis and theoretical reference for managing ecological risks and planning urban development in Leshan City.
文摘BACKGROUND Type 2 diabetes mellitus(T2DM)is a prevalent metabolic disorder increasingly linked with hypertension,posing significant health risks.The need for a predictive model tailored for T2DM patients is evident,as current tools may not fully capture the unique risks in this population.This study hypothesizes that a nomogram incorporating specific risk factors will improve hypertension risk prediction in T2DM patients.AIM To develop and validate a nomogram prediction model for hypertension in T2DM patients.METHODS A retrospective observational study was conducted using data from 26850 T2DM patients from the Anhui Provincial Primary Medical and Health Information Management System(2022 to 2024).The study included patients aged 18 and above with available data on key variables.Exclusion criteria were type 1 diabetes,gestational diabetes,insufficient data,secondary hypertension,and abnormal liver and kidney function.The Least Absolute Shrinkage and Selection Operator regression and multivariate logistic regression were used to construct the nomogram,which was validated on separate datasets.RESULTS The developed nomogram for T2DM patients incorporated age,low-density lipoprotein,body mass index,diabetes duration,and urine protein levels as key predictive factors.In the training dataset,the model demonstrated a high discriminative power with an area under the receiver operating characteristic curve(AUC)of 0.823,indicating strong predictive accuracy.The validation dataset confirmed these findings with an AUC of 0.812.The calibration curve analysis showed excellent agreement between predicted and observed outcomes,with absolute errors of 0.017 for the training set and 0.031 for the validation set.The Hosmer-Lemeshow test yielded non-significant results for both sets(χ^(2)=7.066,P=0.562 for training;χ^(2)=6.122,P=0.709 for validation),suggesting good model fit.CONCLUSION The nomogram effectively predicts hypertension risk in T2DM patients,offering a valuable tool for personalized risk assessment and guiding targeted interventions.This model provides a significant advancement in the management of T2DM and hypertension comorbidity.
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 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.
文摘BACKGROUND The computed tomography(CT)-based preoperative risk score was developed to predict recurrence after upfront surgery in patients with resectable pancreatic ductal adenocarcinoma(PDAC)in South Korea.However,whether it performs well in other countries remains unknown.AIM To externally validate the CT-based preoperative risk score for PDAC in a country outside South Korea.METHODS Consecutive patients with PDAC who underwent upfront surgery from January 2016 to December 2019 at our institute in a country outside South Korea were retrospectively included.The study utilized the CT-based risk scoring system,which incorporates tumor size,portal venous phase density,tumor necrosis,peripancreatic infiltration,and suspicious metastatic lymph nodes.Patients were categorized into prognosis groups based on their risk score,as good(risk score<2),moderate(risk score 2-4),and poor(risk score≥5).RESULTS A total of 283 patients were evaluated,comprising 170 males and 113 females,with an average age of 63.52±8.71 years.Follow-up was conducted until May 2023,and 76%of patients experienced tumor recurrence with median recurrence-free survival(RFS)of 29.1±1.9 months.According to the evaluation results of Reader 1,the recurrence rates were 39.0%in the good prognosis group,82.1%in the moderate group,and 84.5%in the poor group.In comparison,Reader 2 reported recurrence rates of 50.0%,79.5%,and 88.9%,respectively,across the same prognostic categories.The study validated the effectiveness of the risk scoring system,demonstrating better RFS in the good prognosis group.CONCLUSION This research validated that the CT-based preoperative risk scoring system can effectively predict RFS in patients with PDAC,suggesting that it may be valuable in diverse populations.
基金supported by the Research and Development Fund of Peking University People’s Hospital,China(No.PTU2021-02).
文摘BACKGROUND:Acute kidney injury(AKI)is a severe and fatal complication of acute heart failure(AHF).Existing studies on AKI following AHF in the Chinese population have scarce insights available from the emergency department(ED).This study aimed to investigate the predictive factors of patients with AHF complicated with AKI in a Chinese ED cohort,and to establish a risk prediction model.METHODS:Hospitalized patients diagnosed with AHF in the ED from December 2016 to September 2023 were included.The overall dataset were divided into the training set and the testing set at a 7:3 ratio.Univariate and multivariate logistic regression analyses were performed to identify the risk factors for AKI in patients with AHF in the training set,leading to the development of a risk prediction model.The performance of the model was further assessed.RESULTS:A total of 789 patients with AHF were enrolled,with an AKI incidence of 29.7%.The mortality rates of the AKI and non-AKI groups were 23.1%and 7.6%,respectively.Logistic regression analysis showed that the levels of white blood cell(OR=2.368;95%CI:1.502-3.733,P<0.001),albumin(OR=2.669;95%CI:1.601-4.451,P<0.001),serum creatinine(OR=3.221;95%CI:1.935-5.363,P<0.001),and hemoglobin(OR=2.009;95%CI:1.259-3.205,P=0.003),maximum 24-h furosemide dosage(OR=2.196;95%CI:1.346-3.582,P=0.002),the use of non-invasive ventilation(OR=2.419;95%CI:1.454-4.024,P=0.001),and diabetes mellitus(OR=3.192;95%CI:2.014-5.059,P<0.001)were independent risk factors for AKI after AHF.These factors were subsequently incorporated into a risk prediction model.The area under the receiver operating characteristic(AUROC)curve for the predictive model was 0.815(95%CI:0.776-0.854)and 0.802(95%CI:0.776-0.854)in the training set and the testing set,respectively.CONCLUSION:This risk prediction model might assist physician to predict AKI following AHF effectively in the emergency setting.
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.
基金Supported by Jiangsu Provincial Cadre Healthcare Scientific Research Grant Project,No.BJ23019Jiangsu Provincial Association of Maternal and Child Healthcare Scientific Research Grant Project,No.FYX202350+2 种基金Special Fund for the Project of Enhancing Academic Capability of Integrative Nursing,No.ZXYJHHL-K-2023-M20Jiangsu Provincial Graduate Student Practice and Innovation Program Project,No.SJCX24_0833the Training Project for Backbone Talents in Traditional Chinese Medicine Nursing in Nanjing Region,No.Ningwei Zhongyi[2023]No.8.
文摘BACKGROUND Breast cancer(BC)is the second most common malignancy globally.Young and middle-aged patients face more pressures from diagnosis,treatment,costs,and psychological issues like self-image concerns,social barriers,and professional challenges.Compared to other age groups,they have higher recurrence rates,lower survival rates,and increased risk of depression.Research is lacking on factors influencing depressive symptoms and predictive models for this age group.AIM To analyze factors influencing depressive symptoms in young/middle-aged BC patients and construct a depression risk predictive model.METHODS A total of 360 patients undergoing BC treatment at two tertiary hospitals in Jiangsu Province,China from November 2023 to April 2024 were included in the study.Participants were surveyed using a general information questionnaire,the patient health questionnaire depression scale,the visual analog scale for pain,the revised family support scale,and the long form of the international physical activity questionnaire.Univariate and multivariate analyses were conducted to identify the factors affecting depression in middle-aged and young BC patients,and a predictive model for depression risk was developed based on these findings.RESULTS Among the 360 middle-aged and young BC patients,the incidence rate of depressive symptoms was 38.61%(139/360).Multivariate analysis revealed that tumor grade,patient’s monthly income,pain score,family support score,and physical activity score were factors influencing depression in this patient group(P<0.05).The risk prediction model constructed based on these factors yielded an area under the receiver operating characteristic curve of 0.852,with a maximum Youden index of 0.973,sensitivity of 86.80%,specificity of 89.50%,and a diagnostic odds ratio of 0.552.The Hosmer-Lemeshow test for goodness of fit indicated an adequate model fit(χ^(2)=0.360,P=0.981).CONCLUSION The constructed predictive model demonstrates good predictive performance and can serve as a reference for medical professionals to early identify high-risk patients and implement corresponding preventive measures to decrease the incidence of depressive symptoms in this population.
