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Spatial response and prediction model for blasting-induced vibration in a deep double-line tunnel 认领 引用 被引量：1
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作者 Chong Yu Yongan Ma +3 位作者 Haibo Li Changjian Wang Haibin Wang Linghao Meng 《International Journal of Mining Science and Technology》 SCIE EI CAS CSCD 2026年第1期169-186,共18页
Excessive blasting-induced vibration during drilling-and-blasting excavation of deep tunnels can trigger geological hazards and compromise the stability of both the rock mass and support structures.This study focused ... Excessive blasting-induced vibration during drilling-and-blasting excavation of deep tunnels can trigger geological hazards and compromise the stability of both the rock mass and support structures.This study focused on the deep double-line Sejila Mountain tunnel to systematically analyze the spatial response of blasting-induced vibration and to develop a prediction model through field tests and numerical simulations.The results revealed that the presence of a cross passage significantly altered propagation paths and the spatial distribution of blasting-induced vibration velocity.The peak particle velocity(PPV)at the cross-passage corner was amplified by approximately 1.92 times due to wave reflection and geometric focusing.Blasting-induced vibration waves attenuated non-uniformly across the tunnel cross-section,where PPV on the blast-face side was 1.54–6.56 times higher than that on the opposite side.We propose an improved PPV attenuation model that accounts for the propagation path effect.This model significantly improved fitting accuracy and resolved anomalous parameter(k and a)estimates in traditional equations,thereby improving prediction reliability.Furthermore,based on the observed spatial distribution of blasting-induced vibration,optimal monitoring point placement and targeted vibration control measures for tunnel blasting were discussed.These findings provide a scientific basis for designing blasting schemes and vibration mitigation strategies in deep tunnels. 展开更多
关键词 Blasting-induced vibration Spatial response Attenuation law Prediction model Double-line tunnel
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Experiment and prediction model of windage losses in rear drum cavity in secondary air system of aero-engine 认领 引用
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作者 Chuankai LIU Haotian TUO +4 位作者 Tengyue GUO Tian QIU Peng LIU Shuiting DING Lianqiang XU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第6期192-211,共20页
The increasing overall pressure ratio of aero-engines has led to considerable windage losses in the Rear Drum Cavity(RDC)of the secondary air system.These losses convert turbine power into thermal energy,resulting in ... The increasing overall pressure ratio of aero-engines has led to considerable windage losses in the Rear Drum Cavity(RDC)of the secondary air system.These losses convert turbine power into thermal energy,resulting in both energy consumption and a reduction in the rotor's operational lifetime.To expand the experimental database to engine-representative nondimensional conditions,a comprehensive experimental study was conducted,with the mass flow coefficient Cwranging from 3.54×104to 7.59×104and the rotational Reynolds number Reφranging from 3.31×106to 1.02×107.The effects of Cwand Reφon windage characteristics and swirl ratio distribution are analyzed.Furthermore,a theoretical model incorporating core swirl ratio modification and an empirical model are derived to predict windage losses.The experimental results indicate that windage losses are intensified by increasing Cwand Reф,leading to a maximum power consumption of 8 kW and a temperature rise of 54.6 K.Significant windage losses are predominantly driven by a weakened swirl ratio,which arises from the disturbance induced by the stator-mounted bolts.Particularly in the rear region of the RDC,the swirl ratio declines monotonically along the radial direction,showing minimal variation across all operating conditions,while the core swirl ratio remains consistently low,at approximately 0.2.Compared to the experimental data,the theoretical model exhibits an average error of 11%and the empirical model achieves a lower average error of 3%.These findings hold significant implications for enhancing the performance analysis of aero-engines. 展开更多
关键词 Aero-engine Bolt-induced disturbance Rear drum cavity Swirl ratio modification Windage losses Windage prediction model
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Machine learning-based prediction models for liver-related events in patients with hepatitis B-related cirrhosis and clinically significant portal hypertension 认领 引用
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作者 Yan-Qiu Li Zhuo-Jun Li +2 位作者 Yong-Qi Li Ying Feng Xian-Bo Wang 《World Journal of Gastroenterology》 SCIE CAS 2026年第4期54-67,共14页
BACKGROUND Hepatitis B-related cirrhosis represents a major contributor to liver-related events(LREs),with the development of clinically significant portal hypertension(CSPH)serving as a critical milestone in disease ... BACKGROUND Hepatitis B-related cirrhosis represents a major contributor to liver-related events(LREs),with the development of clinically significant portal hypertension(CSPH)serving as a critical milestone in disease progression.AIM To establish predictive models based on multiple machine learning algorithms to improve the accuracy and clinical utility of LREs prediction.METHODS A total of 576 patients were retrospectively enrolled and randomly divided into training(n=403)and validation(n=173)cohorts.Features were selected through least absolute shrinkage and selection operator regression,random forest(RF),and support vector machine(SVM).Based on these features,five predictive models were constructed,including SVM,RF,logistic regression,extreme gradient boosting(XGBoost),and k-nearest neighbor.Model performance was evaluated using receiver operating characteristic and decision curve analysis,and feature importance and interactions were further explored using SHapley Additive ex-Planations(SHAP).RESULTS Of the patients included,313(54.3%)developed LREs.Eight core predictive features were ultimately identified,with the liver stiffness measurement(LSM)-toplatelet ratio(LPR)contributing most significantly.The XGBoost and RF models demonstrated superior performance,achieving accuracies of 0.951 and areas under the curve of 0.975 and 0.965,respectively.SHAP analysis revealed that LPR,hemoglobin(HB),and LSM were key factors,with LPR exhibiting significant interactions with HB,international normalized ratio,and spleen thickness.CONCLUSION Machine learning-based prediction models,particularly XGBoost and RF,can effectively identify high-risk individuals among patients with compensated hepatitis B virus-related cirrhosis and CSPH.LPR that incorporates LSM is a valuable and robust predictive indicator. 展开更多
关键词 Hepatitis B Liver cirrhosis Clinically significant portal hypertension Machine learning Liver-related events Prediction model
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Application of Prostate-Specific Antigen Density and Related Indicators in the Diagnosis of Prostate Cancer and Construction of a Risk Prediction Model 认领 引用
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作者 Yuanfu Qiu Lisi Huang +2 位作者 Longqiaozi Sun Jianfen Lei Chaohui Duan 《Journal of Bio-X Research》 2026年第2期137-148,共12页
Objectives:To investigate the diagnostic value of prostate-specific antigen density(PSAD),prostate volume(PV),free prostate-specific antigen(fPSA),total prostate-specific antigen(tPSA),and fPSAPSA in prostate cancer(P... Objectives:To investigate the diagnostic value of prostate-specific antigen density(PSAD),prostate volume(PV),free prostate-specific antigen(fPSA),total prostate-specific antigen(tPSA),and fPSAPSA in prostate cancer(PCa)and to construct a risk prediction model based on analyzed risk factors.Methods:Age,Gleason score of pathological biopsy,PV,fPSA,tPSA,fPSAPSA,and PSAD were retrospectively analyzed,and accuracy of the predictive model was evaluated using receiver operating characteristic curve and logistic regression analyses.An age×PSAD product term was introduced to test the interaction between age and PSAD,and the predictive efficacy of PSAD stratified by age was evaluated.Results:Multivariate logistic regression analysis suggested that PV,fPSA,tPSA,fPSAPSA,and PSAD were independent risk factors for PCa(P70-year-old group(OR=33.54,95%CI:19.38 to 58.05)(all P<0.001).Conclusion:The nomogram model constructed based on PV,fPSA,tPSA,fPSAPSA,and PSAD can effectively predict the probability of PCa occurrence.Among these factors,the predictive value of PSAD is age dependent and particularly prominent in individuals aged 60 to 70 years. 展开更多
关键词 construct risk prediction model total prostate specific antigen predictive model prostate specific antigen density analyzed risk factorsmethods agegleason free prostate specific antigen receiver operating characteristic curve prostate volume
Glucocorticoid therapy in acute liver failure:Survival outcomes,predictors,and a response prediction model 认领 引用
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作者 Yu-Lan He Xue-Hong Yin +2 位作者 Xiao-Tong Xu Juan Li Qing-Hua Meng 《World Journal of Hepatology》 2026年第4期91-102,共12页
BACKGROUND Glucocorticoids(GC)are a potential therapy for acute liver failure(ALF).However,their clinical efficacy remains controversial,with significant interpatient heterogeneity.AIM To assess the impact of GC thera... BACKGROUND Glucocorticoids(GC)are a potential therapy for acute liver failure(ALF).However,their clinical efficacy remains controversial,with significant interpatient heterogeneity.AIM To assess the impact of GC therapy on 28-day survival of patients with ALF and identify early treatment-response factors.METHODS In this single-centre retrospective cohort study,179 patients with ALF from the past 12 years were included:84 received GC treatment,and 95 served as non-GC controls.The primary outcome was 28-day survival.GC-treated patients were further stratified into responders and nonresponders to analyse the determinants of efficacy.Survival distributions were compared using Kaplan-Meier curves with the log-rank test.Independent predictors of GC response were identified through multivariate logistic regression.Statistical significance was set at P<0.05.RESULTS The 28-day survival rate was significantly greater in the GC group than in the control group(58.3%vs 30.5%,P<0.001).An early increase in prothrombin activity(PTA≥4.5%by day 3),along with baseline model for end-stage liver disease(MELD)score<28.5 and blood ammonia concentration<135.5μg/dL,was independently associated with GC response.A model combining these factors predicted GC responsiveness with an accuracy of 95.2%.CONCLUSION GC therapy improves 28-day ALF survival.An early increase in the PTA,combined with baseline MELD score and blood ammonia level,effectively identifies patients who are most likely to benefit. 展开更多
关键词 Acute liver failure Glucocorticoids Prediction model Survival Efficacy
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Risk factors and prediction model for acute respiratory distress syndrome in patients with digestive tumor after surgery 认领 引用
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作者 Jie Zhen Wei Chen +1 位作者 Yi-Fei Xu Ying-Min Ma 《World Journal of Gastrointestinal Surgery》 SCIE 2026年第1期99-110,共12页
BACKGROUND Postoperative acute respiratory distress syndrome(ARDS)after digestive tumors is a serious complication that severely affects patients’prognosis;however,systematic studies assessing its risk factors are la... BACKGROUND Postoperative acute respiratory distress syndrome(ARDS)after digestive tumors is a serious complication that severely affects patients’prognosis;however,systematic studies assessing its risk factors are lacking,and effective prediction models are urgently required.AIM To investigate the risk factors for postoperative ARDS in patients with digestive tumors and construct a prediction model.METHODS Overall,42 of the 176 patients developed ARDS,with an incidence rate of 23.86%.Multifactorial logistic regression analysis identified advanced age[odds ratio(OR)=1.24,P<0.001],smoking history(OR=3.17,P=0.012),preoperative lung infection(OR=3.07,P=0.015),low preoperative albumin level(OR=0.71,P=0.003),preoperative percentage of forced expiratory volume in 1 second,(OR=0.96,P=0.006),preoperative percentage of forced vital capacity(OR=0.94,P=0.012),and postoperative anastomotic fistula(OR=4.55,P=0.022)as independent risk factors for postoperative ARDS.The nomogram prediction model showed good discriminatory power[area under the curve(AUC)=0.86]and goodness of fit(Hosmer-Lemeshow,P=0.729).The internal validation demonstrated an AUC of 0.86 and a good calibration curve fit(Hosmer-Lemeshow,P=0.914).Prospective clinical validation confirmed the reliability and clinical value of the model(AUC=0.91,accuracy=82.35%).RESULTS Overall,42 of the 176 patients developed ARDS,with an incidence rate of 23.86%.Multifactorial logistic regression analysis identified advanced age(OR=1.24,P<0.001),smoking history(OR=3.17,P=0.012),preoperative lung infection(OR=3.07,P=0.015),low preoperative albumin level(OR=0.71,P=0.003),preoperative percentage of forced expiratory volume in 1 second,(OR=0.96,P=0.006),preoperative percentage of forced vital capacity(OR=0.94,P=0.012),and postoperative anastomotic fistula(OR=4.55,P=0.022)as independent risk factors for postoperative ARDS.The nomogram prediction model showed good discriminatory power(AUC=0.86)and goodness of fit(Hosmer-Lemeshow,P=0.729).The internal validation demonstrated an AUC of 0.86 and a good calibration curve fit(Hosmer-Lemeshow,P=0.914).Prospective clinical validation confirmed the reliability and clinical value of the model(AUC=0.91,accuracy=82.35%).CONCLUSION The nomogram prediction model based on independent risk factors for postoperative ARDS in patients with digestive tumors demonstrated good differentiation,calibration,and clinical utility and helped identify high-risk patients early. 展开更多
关键词 Digestive tumor Acute respiratory distress syndrome Risk factors Prediction model Surgery Clinical value
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Risk prediction models for re-fractures following hip fracture in older adults:A methodological evaluation 认领 引用
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作者 Min Qian Yi-Xiao Chen +2 位作者 Jia-Jia Liu Hua-Jie Yang Guo-Qing Li 《World Journal of Orthopedics》 2026年第5期154-163,共10页
BACKGROUND Hip fracture in elderly patients is often termed“the last fracture in life“.The incidence of hip re-fractures is high,but prognosis is poor,significantly impairing patients’quality of life and imposing a... BACKGROUND Hip fracture in elderly patients is often termed“the last fracture in life“.The incidence of hip re-fractures is high,but prognosis is poor,significantly impairing patients’quality of life and imposing a substantial burden on healthcare systems.A reliable prediction model for re-fractures could play a crucial role in guiding preventive strategies.AIM To conduct a critical appraisal of existing prediction models for re-fractures in hip fracture patients.METHODS A systematic search was conducted across five databases,PubMed,EMBASE,the Cochrane Library,Web of Science,and the China National Knowledge Infrastructure,from inception to January 1,2025.Eligible studies included those that developed prediction models for postoperative re-fractures following hip fractures.The Prediction Model Risk of Bias Assessment Tool was employed to evaluate the risk of bias and clinical applicability.A narrative synthesis summarised the characteristics,methodological quality,and predictive performance of the identified studies.Additionally,a meta-analysis was performed to quantitatively assess the performance of prediction models.RESULTS Of the 6056 studies retrieved,8 studies with 28 predictive models were ultimately identified.Internal and external validation was performed for five(62.5%,internal),two(25.0%,external),and one(12.5%,internal and external)models.The number of predictors per model ranged from four to nineteen.The most frequently included predictors were age,rehabilitation exercise,osteoporosis,heart disease,and Alzheimer's disease.The models demonstrated area under the curve values of 0.69-0.98 in internal validation and 0.76-0.98 in external validation.Pooled analysis of the area under the curves yielded values of 0.970(95%CI:0.960-0.980)and 0.932(95%CI:0.907-0.959)for the model development and validation,respectively.All included models had a high risk of bias,while only two(25.0%)showed low concerns regarding applicability.CONCLUSION Current risk prediction models for postoperative re-fracture after hip fractures surgery lack robust validation and comprehensive evaluation.Future studies should prioritise refining model development,improving generalizability,and assessing clinical utility.Collaborative initiatives involving researchers,clinicians,and policymakers are crucial to transforming these models into effective tools for mitigating the burden of re-fractures in elderly populations. 展开更多
关键词 Older adults Prediction model Hip re-fracture Meta-analysis Systematic review
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Prediction model for quality of life in sepsis survivors one year after discharge 认领 引用 被引量：1
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作者 Yi Yao Wenjin Li +3 位作者 Dejiang Hong Ze Chen Kai Peng Guangju Zhao 《World Journal of Emergency Medicine》 SCIE CAS CSCD 2026年第2期105-112,共8页
BACKGROUND:Sepsis survivors experience poor long-term quality of life post-discharge.The aim of this study was to analyze the factors that impact the long-term quality of life of sepsis survivors and develop a clinica... BACKGROUND:Sepsis survivors experience poor long-term quality of life post-discharge.The aim of this study was to analyze the factors that impact the long-term quality of life of sepsis survivors and develop a clinical prediction model.METHODS:A total of 442 sepsis patients from the Emergency Intensive Care Unit of a tertiary hospital in Wenzhou were included.These patients were assigned to the training set or the validation set at a ratio of 7:3.The European Quality of Life 5 Dimensions 5 Level Version(EQ-5D-5L) questionnaire was used to evaluate the quality of life in sepsis survivors one year after discharge.Multivariate logistic regression analysis was used to identify predictors,which were then used to develop the prediction model and subsequently derive a scoring system.The model's effectiveness was assessed using an area under the receiver operating characteristic curve,calibration curves,and clinical decision analysis.RESULTS:Of the 442 patients included,70 died one year after discharge,and 372 completed the questionnaire.A total of 46.6% of sepsis survivors have poor quality of life one year after discharge in the training set.Multivariate logistic regression revealed that age,platelet,serum albumin,serum urea,and C-reactive protein were independent risk factors for poor quality of life in sepsis survivors.The area under the curve of the scoring system was 0.777(95% CI:0.726–0.828).The calibration curves showed that it was well calibrated.Decision curve analysis indicated that the scoring system provided good clinical usefulness.The internal validation also demonstrated its effectiveness.CONCLUSION:The prediction model incorporating five risk factors may predict quality of life one year after discharge in sepsis survivors,which provides a measure to develop post-discharge rehabilitation and follow-up plans for this patient population. 展开更多
关键词 Sepsis Sepsis survivors Quality of life EQ-5D-5L Prediction model
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A relay-based probabilistic prediction model for multi-fidelity scenarios in total pressure loss of a compressor cascade with micro-textured surfaces 认领 引用
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作者 Liyue WANG Cong WANG +2 位作者 Xinyue LAN Haochen ZHANG Gang SUN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第1期55-65,共11页
The micro-riblet structures have been demonstrated effective in controlling the Total Pressure Loss(TPL)of aero-engine blades.However,due to the considerable scale gap between micro-texture and an actual aero-engine b... The micro-riblet structures have been demonstrated effective in controlling the Total Pressure Loss(TPL)of aero-engine blades.However,due to the considerable scale gap between micro-texture and an actual aero-engine blade,wind tunnel tests and numerical simulations with massive grids directly describing the global flow field are costly for aerodynamic evaluation.Furthermore,the fine micro surface structure brings unavoidable manufacturing errors,and the probability prediction contributes to gaining the confidence interval of the results.Therefore,a novel relay-based probabilistic model for multi-fidelity scenarios in the TPL prediction of a compressor cascade with micro-riblet surfaces is proposed to trade off accuracy and efficiency.Combined with the low-fidelity flow data generated by an aerodynamic solution strategy using the boundary surrogate model and the high-fidelity flow data from the experiment,the relay-based modeling has been achieved through knowledge transferring,and the confidence interval can be provided by the Gaussian Process Regression(GPR)model.The TPL of compressor cascades with micro-riblet surfaces under different surface structures at March number Ma=0.64,0.74,0.84 have been evaluated using the Relay-Based Probabilistic(RBP)model.The results illustrate that the RBP model could provide higher accuracy than the Single-Fidelity-Data-Driven(SFDD)prediction model,which show the promising potential of multi-fidelity scenarios data fusion in the aerodynamic evaluation of multi-scale configurations. 展开更多
关键词 Knowledge transfer Micro-riblet Multi-fidelity surrogate Probability prediction model Total pressure loss
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Assessment of the value of complication risk prediction models following interventional therapy for hepatocellular carcinoma in nursing decision-making 认领 引用
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作者 Hui Wang Hao-Tian Guo +3 位作者 Jing Shen Fei Zhang Yue-Jiao Jiang Zhen-Xing Liu 《World Journal of Gastroenterology》 SCIE CAS 2026年第24期44-53,共10页
BACKGROUND Transcatheter arterial chemoembolization(TACE)is a primary interventional modality for intermediate-to-advanced hepatocellular carcinoma(HCC).However,the high incidence of post-procedural complications sign... BACKGROUND Transcatheter arterial chemoembolization(TACE)is a primary interventional modality for intermediate-to-advanced hepatocellular carcinoma(HCC).However,the high incidence of post-procedural complications significantly compromises patient recovery and prognosis.Currently,clinical nursing assessment lacks a multifaceted risk prediction tool that integrates multiple risk factors.AIM To establish a predictive model for postoperative complications in patients with HCC undergoing TACE.METHODS A retrospective analysis was conducted on 386 patients with HCC who underwent interventional therapy at our hospital from January 2023 to December 2024.Patients were divided into a complication group(n=104)and a control group(n=282)based on postoperative complication occurrence.General clinical data and nursing-related indicators were collected and compared between groups.Multivariate logistic regression analysis was used to identify independent risk factors,construct a risk prediction model,and validate its discriminatory power and calibration by using receiver operating characteristic curve and Hosmer-Lemeshow test.RESULTS The incidence of complications following interventional therapy for HCC in this study was 26.94%.Factors associated with complications included age≥60 years,liver cirrhosis,vascular invasion,procedure duration≥2 hours,TACE sessions>2,Child-Pugh grade B,tumor diameter≥5 cm,nutritional risk(Nutritional Risk Screening 2002≥3),anxiety(Self-Rating Anxiety Scale≥50),depression(Self-Rating Depression Scale≥53),caregiver burden(high Zarit Burden Interview Score),functional independence(low Exercise of Self-Care Agency Scale Score),quality of life(low Quality of Life Instruments for Cancer Patients-General Module Score),and low compliance with early postoperative activity and exercise were all independent risk factors(P<0.05).The predictive model demonstrated a C-index of 0.773,an area under the curve of 0.936,sensitivity of 93.25%,specificity of 84.96%,and good calibration(Hosmer-Lemeshow test,P=0.382).CONCLUSION The TACE postoperative complication prediction model derived during the research combines multidimensional clinical and nursing predictors,which proves a high predictive quality and clinical usefulness.It provides healthcare professionals with a scientifically grounded assessment tool to facilitate risk stratification management and precision nursing. 展开更多
关键词 Hepatocellular carcinoma Interventional therapy Transcatheter arterial chemoembolization Complication risk Risk prediction model Nursing decision-making
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Research on design and prediction model of tunnel safety micro-deformation radar monitoring system 认领 引用
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作者 Zi-heng Gao Gu-hua Pu +9 位作者 Jin-zhuang Wang Meng-wei Han Qiang He Xiao-long Wang Jian-bo Yang Xiao-yu Yin Jia-gui Duan Liang Bao Xi-can Zhao Wei-jian Liu 《Applied Geophysics》 SCIE CSCD 2026年第1期138-151,429,共14页
Tunnel micro-deformation is a progressive mechanical response process of geotechnical media under the influence of stress redistribution,environmental loads,material aging and other factors.Its millimeterlevel dynamic... Tunnel micro-deformation is a progressive mechanical response process of geotechnical media under the influence of stress redistribution,environmental loads,material aging and other factors.Its millimeterlevel dynamic evolution is difcult to eectively capture by traditional monitoring technologies.Based on the physical mechanism of microwave remote sensing,this paper uses Ground-Based Synthetic Aperture Radar(GB-SAR)for continuous,non-contact deformation perception of tunnel structures.The system transmits and receives coherent electromagnetic wave signals,and extracts millimeter-level even sub-millimeter-level deformation information by means of dierential interferometry technology.Combined with typical tunnel engineering cases,the study verifies the monitoring stability and reliability of the system under different geological conditions and complex environments.The results show that the system can realize real-time,highprecision monitoring of the full-section deformation eld of tunnels with high early warning accuracy and strong environmental adaptability,providing an effective geophysical technical means for tunnel structure health diagnosis and safe operation and maintenance. 展开更多
关键词 Highway Tunnel Ground-Based Synthetic Aperture Radar(GB-SAR) Prediction Model Microwave Remote Sensing Geophysical Monitoring
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Development and validation of a risk prediction model for small intestinal mucosal injury in nonsteroidal anti-inflammatory drug users 认领 引用
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作者 Ning-Hui Zhao Ling-Ran Zhao +4 位作者 Jia Yao Ling-Yun Niu Long-Jun Yang Yu-Jia Lin Mei Liu 《World Journal of Gastrointestinal Surgery》 SCIE 2026年第2期279-289,共11页
BACKGROUND Despite the enhanced detection capability of capsule endoscopy for small intestinal lesions,the independent risk factors and distinct clinical-endoscopic characteristics in high-risk populations remain inco... BACKGROUND Despite the enhanced detection capability of capsule endoscopy for small intestinal lesions,the independent risk factors and distinct clinical-endoscopic characteristics in high-risk populations remain incompletely elucidated.AIM To investigate the risk factors for small intestinal mucosal injury(SIMI)in nonsteroidal anti-inflammatory drug(NSAID)users and to establish a corresponding predictive model.METHODS We conducted a retrospective analysis of clinical data from patients undergoing capsule endoscopy at our institution and Shanxi Bethune Hospital from August 2012 to January 2025.Multivariate analysis was performed to identify independent risk factors for SIMI.A nomogram was subsequently developed to predict the risk of SIMI in NSAID users.Receiver operating characteristic curve analysis,calibration curve and decision curve analysis were performed to evaluate the predictive accuracy of the nomogram.RESULTS In the primary cohort,SIMI was identified in 114 out of 181 NSAID users.Multivariate analysis revealed that advanced age,smoking,proton pump inhibitor use,elevated body mass index,high triglyceride levels,and increased low-density lipoprotein were independent risk factors for SIMI.The research team developed a risk prediction model for estimating the risk of mucosal injury,which achieved an area under the curve of 0.775(95%confidence interval:0.700-0.849)in the derivation set.The model exhibited an area under the curve of 0.797(95%confidence interval:0.643-0.952)in the validation cohort.CONCLUSION We identified risk factors for SIMI in NSAID users and established a predictive model,which may facilitate early identification of high-risk populations and guide clinical interventions. 展开更多
关键词 Small intestinal mucosal injury Nonsteroidal anti-inflammatory drug Capsule endoscopy Risk factors Prediction model
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A prediction model for axial installation force of interference-fit bolt in CFRP bolted joint and its deformation mechanism of contact interface at bolt-hole under static loading 认领 引用
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作者 Duquan ZUO Jie LIU +4 位作者 Yuejie CAO Minghao ZHANG Shaoqing JIN Yaoming FU Zengqiang CAO 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第3期631-642,共12页
This paper investigates the “brush-like”deformation phenomenon of the contact interface at the bolt-hole during the interference-fit installation of high-locking bolts under static loading in CFRP connection structu... This paper investigates the “brush-like”deformation phenomenon of the contact interface at the bolt-hole during the interference-fit installation of high-locking bolts under static loading in CFRP connection structures.An innovative theoretical model is proposed to predict axial installation force,specifically designed for moderate interference-fit.This model is based on the “brush-like”deformation of the hole wall,with the axial installation force predicted through force analysis and theoretical calculations,effectively overcoming the limitations of prior models that idealized the contact interface at the bolt-hole.The predictions generated by this theoretical model align closely with experimental data,confirming its efficacy in accurately forecasting the curve of installation force for interferencefit bolts during the static installation within the moderate interference-fit range.Additionally,a comprehensive analysis of the relationship between deformation of the hole wall and curves of installation force across small,moderate,and large interference-fit levels are presented.It is demonstrated that the degree of deformation within the moderate interference-fit range is more suitable than that in the small and large interference-fit ranges,making it a reliable alternative for installation force tests within this range during static installation.The moderate interference-fit domain[1.00%,1.24%]is established as a validated and optimal range of interference-fit bolts for the static installation. 展开更多
关键词 Axial installation force CFRP Contact interface Interference-fit bolt Predictive model
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Development and validation of a risk prediction model for tigecycline-induced thrombocytopenia 认领 引用
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作者 Haiying Chen Shiya Wu +2 位作者 Jianje Ju Feifei Zhou Qi Lin 《Journal of Chinese Pharmaceutical Sciences》 CAS CSCD 2026年第5期491-501,共11页
The study aimed to construct and validate a logistic regression—based prediction model for tigecycline(TGC)—induced thrombocytopenia,to delineate its principal risk determinants,and to develop a clinically applicabl... The study aimed to construct and validate a logistic regression—based prediction model for tigecycline(TGC)—induced thrombocytopenia,to delineate its principal risk determinants,and to develop a clinically applicable tool for early risk stratification.A retrospective cohort study was performed using data from hospitalized patients who received TGC therapy at a tertiary medical center between January 2020 and January 2024.A total of 64 candidate clinical variables were initially considered and subsequently selected using a hybrid LASSO-Boruta algorithm.Model performance was assessed through 10-fold cross-validation,receiver operating characteristic(ROC)analysis,and calibration curve evaluation.A dynamic nomogram was further developed to facilitate bedside implementation.Of the 919 eligible patients,224 experienced thrombocytopenia,corresponding to an incidence rate of 24.37%.Nine variables emerged as independent predictors,including age,intensive care unit admission,mechanical ventilation,maintenance dose of TGC,baseline platelet count,red blood cell count,serum creatinine,potassium,and blood urea nitrogen.The model achieved an area under the curve(AUC)of 0.744 in the training cohort and 0.736 in the validation cohort,with a Brier score of 0.149,indicating favorable discriminative ability and calibration.Decision curve analysis(DCA)demonstrated a meaningful clinical net benefit across threshold probabilities ranging from 18%to 63%.Overall,the proposed logistic regression model and its accompanying dynamic nomogram exhibited robust predictive performance and clinical utility,offering a practical and interpretable approach for the early identification of patients at elevated risk of TGC-induced thrombocytopenia. 展开更多
关键词 Tigecycline Thrombocytopenia LASSO-Boruta algorithm Risk factors Prediction model
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Risk factors analysis and prediction model construction of micafungin-induced hypomagnesemia in critically ill patients 认领 引用
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作者 Xiuying Zhang Ming Gong +2 位作者 Haili Zhong Zhihua Yang Xiaoling Song 《Journal of Chinese Pharmaceutical Sciences》 CAS CSCD 2026年第6期574-582,共9页
This retrospective study included 139 critically ill patients who received micafungin therapy at the First Affiliated Hospital of Nanchang University between January 2020 and December 2023.Patients were classified int... This retrospective study included 139 critically ill patients who received micafungin therapy at the First Affiliated Hospital of Nanchang University between January 2020 and December 2023.Patients were classified into a hypomagnesemia group(serum magnesium<0.75 mmol/L)and a non-hypomagnesemia group.Demographic characteristics,laboratory data,and concomitant medications were collected.Univariate and multivariate logistic regression analyses were performed to identify independent risk factors.A predictive nomogram was subsequently developed using the rms package in R software and underwent internal validation.The incidence of hypomagnesemia in this cohort was 33.8%(47/139).Univariate analysis revealed significant between-group differences in SOFA score,duration of micafungin therapy,baseline serum creatinine,baseline serum magnesium,and post-treatment serum creatinine(all P<0.05).Multivariate analysis further identified micafungin treatment duration(OR=1.117,95%CI:1.056-1.181;P<0.001),post-treatment albumin(OR=0.889,95%CI:0.807-0.979;P=0.017),and baseline serum creatinine(OR=0.992,95%CI:0.987-0.997;P=0.001)as independent predictors of hypomagnesemia.The nomogram demonstrated strong discriminatory ability(AUC=0.807,95%CI:0.728-0.886),with corresponding sensitivity and specificity of 66.0%and 87.0%,respectively.The calibration curve showed a mean absolute error of 0.027,and the Hosmer-Lemeshow test confirmed satisfactory model calibration(χ2=13.12,P=0.11).Overall,this study revealed a notably high incidence of micafungin-induced hypomagnesemia among critically ill patients.Treatment duration,post-treatment albumin level,and baseline serum creatinine emerged as independent risk factors.The proposed nomogram offered a practical and reliable tool for predicting the risk of micafungin-related hypomagnesemia in the critically ill population. 展开更多
关键词 Critically ill patients Micafungin Hypomagnesemia Risk factors Prediction model
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Development and validation of a prediction model for non-suicidal self-injury in adolescents based on functional near-infrared spectroscopy and neuropsychological assessment 认领 引用
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作者 Wan-Gen Liu Huan-Zhen Liu +3 位作者 Hou-Qiang Fu Hao Lv Chang Liu Cheng-Xi Li 《World Journal of Psychiatry》 SCIE 2026年第8期256-266,共11页
BACKGROUND Non-suicidal self-injury(NSSI)is prevalent among adolescents worldwide,yet current identification methods rely heavily on subjective self-report tools that are prone to concealment and fail to capture the n... BACKGROUND Non-suicidal self-injury(NSSI)is prevalent among adolescents worldwide,yet current identification methods rely heavily on subjective self-report tools that are prone to concealment and fail to capture the neurobiological underpinnings of the behavior.Integrating objective neuroimaging markers with neuropsychological assessment may improve early identification and risk stratification of NSSI.AIM To develop and validate a prediction model for NSSI behavior in adolescents based on functional near-infrared spectroscopy(fNIRS)and neuropsychological assessment indicators.METHODS A retrospective study was conducted,including 312 adolescents(156 NSSI cases and 156 controls)who visited the psychology department of a tertiary hospital from March 2021 to March 2024.All participants completed fNIRS assessment(verbal fluency task)and neuropsychological evaluation[Difficulties in Emotion Regulation Scale(DERS),Childhood Trauma Questionnaire(CTQ),Barratt Impulsiveness Scale-11(BIS-11),Adolescent Self-Rating Life Events Check List(ASLEC)].Univariate analysis was used to screen variables,and multivariate logistic regression was employed to establish the prediction model.A nomogram was constructed,and internal validation was performed using the Bootstrap method.The model’s performance was evaluated using the area under the receiver operating characteristic curve(AUC),calibration curve,and decision curve analysis(DCA).RESULTS The NSSI group showed significantly lower prefrontal oxyhemoglobin concentration changes and activation integral values compared to the control group(P<0.001).Multivariate logistic regression revealed that left dorsolateral prefrontal cortex activation integral value[odds ratio(OR)=0.72,95%CI:0.58-0.89],DERS nonacceptance of emotional responses dimension(OR=1.15,95%CI:1.08-1.23),CTQ emotional neglect dimension(OR=1.12,95%CI:1.05-1.19),BIS-11 motor impulsiveness dimension(OR=1.18,95%CI:1.09-1.28),and ASLEC interpersonal relationship dimension(OR=1.09,95%CI:1.03-1.16)were independent predictors of NSSI.The prediction model based on these factors achieved an AUC of 0.891(95%CI:0.854-0.928),with sensitivity of 82.7%and specificity of 81.4%.Bootstrap internal validation showed a corrected AUC of 0.876.The calibration curve demonstrated good consistency between predicted and actual probabilities,and DCA indicated favorable clinical net benefit.CONCLUSION The prediction model based on fNIRS prefrontal activation indicators and neuropsychological assessment demonstrates good predictive performance for adolescent NSSI and can provide objective evidence for early identification and risk stratification of NSSI. 展开更多
关键词 Non-suicidal self-injury Adolescent Functional near-infrared spectroscopy Prediction model Nomogram Prefrontal cortex
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Prediction model for rapid estimated glomerular filtration rate decline in type 2 diabetes mellitus 认领 引用
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作者 Peng Huang Xue-Qiong Qin +4 位作者 Qing Huang Si-Dan Wang Yuan-Yuan Wu Xiu-Rong Huang Xu Lin 《World Journal of Diabetes》 SCIE 2026年第4期116-130,共15页
BACKGROUND Diabetic kidney disease is the most common microvascular complication of type 2 diabetes mellitus(T2DM)and a leading cause of end-stage renal disease.Rapid estimated glomerular filtration rate(eGFR)decline(... BACKGROUND Diabetic kidney disease is the most common microvascular complication of type 2 diabetes mellitus(T2DM)and a leading cause of end-stage renal disease.Rapid estimated glomerular filtration rate(eGFR)decline(annual decline rate≥5 mL/minute/1.73 m2)is a strong predictor of end-stage renal disease and cardiovascular events,yet effective risk stratification tools are currently lacking in clinical practice.AIM To establish a comprehensive and accurate risk stratification system for patients with T2DM and kidney complications is of crucial importance for clinical decision-making.METHODS This retrospective cohort study enrolled 302 T2DM patients who attended our hospital from January 2021 to August 2024,with a minimum follow-up period of 12 months.Patients were divided into rapid decline group(≥5 mL/minute/1.73 m2,n=89)and non-rapid decline group(0.4).Compared with existing kidney failure risk equation 4,kidney failure risk equation 8,and Kidney Disease:Improving Global Outcomes stratification systems,our model showed significant advantages(P<0.05)with net reclassification improvement of 0.385-0.428 and integrated discrimination improvement of 0.076-0.156 in external validation.CONCLUSION This work effectively developed a nomogram model with good discrimination,calibration,and clinical applicability for risk stratification of rapid eGFR drop among T2DM patients with indications of kidney involvement.The model integrates both established risk variables and new risk markers. 展开更多
关键词 Type 2 diabetes mellitus Estimated glomerular filtration rate Rapid decline Risk factors Prediction model Nomogram Machine learning
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Letter to the Editor:From glycemia to mood:Exploration of a postpartum depression prediction model in gestational diabetes 认领 引用
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作者 Wei-Li Zhang Huang-Ling Gao +1 位作者 Miao-Miao Yang Quan-Feng Zhu 《World Journal of Psychiatry》 SCIE 2026年第8期461-466,共6页
This letter discusses a recent study by Wu JX and Wu FF which published in World Journal of Psychiatry that examined factors influencing postpartum depression(PPD)in patients with gestational diabetes mellitus(GDM),an... This letter discusses a recent study by Wu JX and Wu FF which published in World Journal of Psychiatry that examined factors influencing postpartum depression(PPD)in patients with gestational diabetes mellitus(GDM),and constructed a risk prediction model.The study enrolled 204 GDM patients,dividing them into PPD(n=52)and non-PPD(n=152)groups based on Edinburgh Postnatal Depression Scale scores at 6 weeks postpartum.Multivariate logistic regression analysis revealed that elevated 2-hour postprandial glucose at diagnosis,poor glycemic control during pregnancy,postpartum mother-infant separation,low family care,and low social support were independent risk factors for PPD.The prediction model,defined as Logit(P)=0.508×2-hour postprandial blood glucose+0.687×gestational blood glucose control+1.092×postpartum mother-infant separation+0.745×low family care+0.289×low social support-4.766,demonstrated robust performance with an area under the curve of 0.840,sensitivity of 0.839,and specificity of 0.825.The significance of the study lies in identifying GDM-specific PPD risk factors and constructing a practical predictive tool for clinical use.It establishes a critical link between glycemic indicators and postpartum mental health,expanding our understanding of psychological issues in GDM patients.This model enables early identification of high-risk individuals,facilitating targeted interventions such as enhanced glycemic management,promotion of mother-infant contact,and mobilization of family and social support resources.By shifting from passive treatment to active prevention,this approach has important implications for improving maternal mental health outcomes,promoting mother-infant wellbeing,and reducing family and societal burden.Although this was a single-center study with a small sample,these findings provide a foundation for future multicenter research and the development of digital risk assessment tools and personalized intervention strategies. 展开更多
关键词 Gestational diabetes Postpartum depression Prediction model Blood glucose 2-hour postprandial glucose Maternal mental health Perinatal care
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Endoscopic characterization and development of a prediction model for colorectal adenomatous polyps 认领 引用
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作者 Wen-Cai Luo Yuan-Fu Yang +1 位作者 Yao Wang Zhao-Hong Zhang 《World Journal of Gastrointestinal Surgery》 SCIE 2026年第2期290-300,共11页
BACKGROUND Colorectal cancer carries a high mortality rate worldwide.Adenocarcinoma is its most common type,which is progressed following an adenoma-dysplasia-carcinoma sequence.Early accurate identification of indivi... BACKGROUND Colorectal cancer carries a high mortality rate worldwide.Adenocarcinoma is its most common type,which is progressed following an adenoma-dysplasia-carcinoma sequence.Early accurate identification of individuals with a high risk for adenomas could facilitate prompt removal of adenomas and reduce colorectal cancer incidence.AIM To investigate the endoscopic features of colorectal adenomatous polyps and develop a prediction model for their occurrence.METHODS A total of 202 individuals undergoing their first colonoscope between January 2023 and January 2024 were selected.Endoscopic characteristics,demographics,clinical information,and laboratory results were compared between individuals with or without colorectal adenomas.Logistic regression was performed to identify risk factors for colorectal adenomatous polyps and construct a prediction model.A nomogram was developed using R(v3.5.2).Internal validation was conducted with 1000 bootstrap resamples to assess calibration and discrimination.External valuation was conducted in another 240 individuals.RESULTS In 202 participants,75(37.13%)and 127(62.87%)had or had no colorectal adenomas,respectively.These adenomas varied in shape,size,and locations.Age≥60 years,smoking,alcohol,fatty liver,gallbladder polyps,and abnormal glycosylated hemoglobin(HbA1c)were risk factors and were used to construct nomogram Logit(P)=-5.602+1.791×age≥60 years+1.115×smoking+1.894×alcohol+1.727×fatty liver+1.749×gallbladder polyps+1.903×abnormal HbA1c.Internal validation demonstrated excellent agreement between apparent and bias-corrected curves,strong discriminative ability(area under the curve of 0.889,95%confidence interval:0.841-0.938),and high net clinical benefit(threshold probability range 0.1-0.9).External validation also suggested excellent model performance.CONCLUSION Colorectal adenomas exhibit diverse characteristics.A nomogram incorporating age,smoking,alcohol,fatty liver,gallbladder polyps,and HbA1c provides a robust and accurate prediction for the risk of colorectal adenomas. 展开更多
关键词 Colorectal adenomatous polyps Endoscopic characteristics Risk factors Prediction model Colorectal cancer prevention
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Construction of a risk prediction model for postoperative gastrointestinal dysfunction and prevention in patients with gastrointestinal tumors 认领 引用
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作者 Xiao-Hui Wang Yi Wang +3 位作者 Xi Liu Xiao-Lan Ouyang Fen Xie Lu Liao 《World Journal of Gastrointestinal Surgery》 SCIE 2026年第2期231-239,共9页
BACKGROUND The global incidence of gastrointestinal tumors is continuously increasing.Surgery remains the primary treatment modality.However,postoperative gastrointestinal dysfunction remains prevalent,severely impedi... BACKGROUND The global incidence of gastrointestinal tumors is continuously increasing.Surgery remains the primary treatment modality.However,postoperative gastrointestinal dysfunction remains prevalent,severely impeding patient recovery and increasing medical burden.Existing research investigating risk prediction and preventive management has some limitations.AIM To construct a risk-prediction model for postoperative gastrointestinal dysfunction in patients with gastrointestinal tumors and explore preventive management strategies.METHODS Data from 176 patients who underwent gastrointestinal tumor surgery at the authors’hospital between November 2022 and November 2024 were included.Patients were divided into groups according to Tilburg Frailty Scale scores on postoperative day 5.Risk factors were screened using univariate and multivariate logistic regression analyses to establish a model,and the effectiveness of preventive management measures was evaluated.RESULTS Seven factors including age,sex,body mass index,tumor stage,operative duration,and preoperative hemoglobin and albumin levels were identified as independent risk factors.The constructed model had an area under the receiver operating characteristic curve of 0.895.The incidence of postoperative gastrointestinal dysfunction in the intervention group was significantly lower than that in the control group using preventive management measures based on the model.CONCLUSION An effective risk-prediction model was constructed and independent risk factors were identified.Preventive management measures based on this model can reduce risk and provide a scientific basis for clinical practice. 展开更多
关键词 Gastrointestinal neoplasms Postoperative gastrointestinal dysfunction Risk prediction model Preventive management Intestinal barrier function
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