Wheat is a critical crop,extensively consumed worldwide,and its production enhancement is essential to meet escalating demand.The presence of diseases like stem rust,leaf rust,yellow rust,and tan spot significantly di...Wheat is a critical crop,extensively consumed worldwide,and its production enhancement is essential to meet escalating demand.The presence of diseases like stem rust,leaf rust,yellow rust,and tan spot significantly diminishes wheat yield,making the early and precise identification of these diseases vital for effective disease management.With advancements in deep learning algorithms,researchers have proposed many methods for the automated detection of disease pathogens;however,accurately detectingmultiple disease pathogens simultaneously remains a challenge.This challenge arises due to the scarcity of RGB images for multiple diseases,class imbalance in existing public datasets,and the difficulty in extracting features that discriminate between multiple classes of disease pathogens.In this research,a novel method is proposed based on Transfer Generative Adversarial Networks for augmenting existing data,thereby overcoming the problems of class imbalance and data scarcity.This study proposes a customized architecture of Vision Transformers(ViT),where the feature vector is obtained by concatenating features extracted from the custom ViT and Graph Neural Networks.This paper also proposes a Model AgnosticMeta Learning(MAML)based ensemble classifier for accurate classification.The proposedmodel,validated on public datasets for wheat disease pathogen classification,achieved a test accuracy of 99.20%and an F1-score of 97.95%.Compared with existing state-of-the-art methods,this proposed model outperforms in terms of accuracy,F1-score,and the number of disease pathogens detection.In future,more diseases can be included for detection along with some other modalities like pests and weed.展开更多
Activity based costing (ABC) is a method which can solve many limitations of the traditional cost systems in manufacturing management. In this paper, we investigate how to integrate ABC with workflow technology, and ...Activity based costing (ABC) is a method which can solve many limitations of the traditional cost systems in manufacturing management. In this paper, we investigate how to integrate ABC with workflow technology, and build a workflow meta model supporting ABC. Firstly, the concept and concept model of activity based costing (ABC) are introduced. Next, the meta model of P -PROCE (Process, Product, Resource, Organization, and Cost & Evaluation) is presented. Then the cost meta model is defined by adding ABC to P -PROCE model. Object constraint language (OCL) is used to express meta model and constraints. Finally, we show an enterprise modeling and simulation tool based on the workflow meta model. We can systematically construct an enterprise model and easily and efficiently conduct simulation. Moreover it enables us to analyze and evaluate business processes and its costs.展开更多
Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity ana...Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on （1） a screening method （Morris） for qualitative ranking of parameters, and （2） a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model （RSMSobol）. First, the Morris screening method was used to qualitatively identify the parameters＇ sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model （RSM） were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.展开更多
To investigate the application of meta-model for finite element( FE) model updating of structures,the performance of two popular meta-model,i. e.,Kriging model and response surface model( RSM),were compared in detail....To investigate the application of meta-model for finite element( FE) model updating of structures,the performance of two popular meta-model,i. e.,Kriging model and response surface model( RSM),were compared in detail. Firstly,above two kinds of meta-model were introduced briefly. Secondly,some key issues of the application of meta-model to FE model updating of structures were proposed and discussed,and then some advices were presented in order to select a reasonable meta-model for the purpose of updating the FE model of structures. Finally,the procedure of FE model updating based on meta-model was implemented by updating the FE model of a truss bridge model with the measured modal parameters. The results showed that the Kriging model was more proper for FE model updating of complex structures.展开更多
In this study, a new method for conversion of solid finite element solution to beam finite element solution is developed based on the meta-modeling theory which constructs a model consistent with continuum mechanics. ...In this study, a new method for conversion of solid finite element solution to beam finite element solution is developed based on the meta-modeling theory which constructs a model consistent with continuum mechanics. The proposed method is rigorous and efficient compared to a typical conversion method which merely computes surface integration of solid element nodal stresses to obtain cross-sectional forces. The meta-modeling theory ensures the rigorousness of proposed method by defining a proper distance between beam element and solid element solutions in a function space of continuum mechanics. Results of numerical verification test that is conducted with a simple cantilever beam are used to find the proper distance function for this conversion. Time history analysis of the main tunnel structure of a real ramp tunnel is considered as a numerical example for the proposed conversion method. It is shown that cross-sectional forces are readily computed for solid element solution of the main tunnel structure when it is converted to a beam element solution using the proposed method. Further, envelopes of resultant forces which are of primary importance for the purpose of design, are developed for a given ground motion at the end.展开更多
Engineering data are separately organized and their schemas are increasingly complex and variable. Engineering data management systems are needed to be able to manage the unified data and to be both customizable and e...Engineering data are separately organized and their schemas are increasingly complex and variable. Engineering data management systems are needed to be able to manage the unified data and to be both customizable and extensible. The design of the systems is heavily dependent on the flexibility and self-description of the data model. The characteristics of engineering data and their management facts are analyzed. Then engineering data warehouse (EDW) architecture and multi-layer metamodels are presented. Also an approach to manage anduse engineering data by a meta object is proposed. Finally, an application flight test EDW system (FTEDWS) is described and meta-objects to manage engineering data in the data warehouse are used. It shows that adopting a meta-modeling approach provides a support for interchangeability and a sufficiently flexible environment in which the system evolution and the reusability can be handled.展开更多
Neural networks are being used to construct meta-models in numerical simulation of structures.In addition to network structures and training algorithms,training samples also greatly affect the accuracy of neural netwo...Neural networks are being used to construct meta-models in numerical simulation of structures.In addition to network structures and training algorithms,training samples also greatly affect the accuracy of neural network models.In this paper,some existing main sampling techniques are evaluated,including techniques based on experimental design theory, random selection,and rotating sampling.First,advantages and disadvantages of each technique are reviewed.Then,seven techniques are used to generate samples for training radial neural networks models for two benchmarks:an antenna model and an aircraft model.Results show that the uniform design,in which the number of samples and mean square error network models are considered,is the best sampling technique for neural network based meta-model building.展开更多
Our research focuses on creating a meta-model for generating a web mapping application. It was difficult for non-geomatics developers to implement a webmapping application. Indeed, this type of application uses geospa...Our research focuses on creating a meta-model for generating a web mapping application. It was difficult for non-geomatics developers to implement a webmapping application. Indeed, this type of application uses geospatial data that require geomatics skills. For this reason, in order to help non-geomatics developers to set up a webmapping application, we have designed a meta-model that automatically generates a webmapping application using model-driven engineering. The created meta-model is used by non-geomatics developers to explicitly write the concrete syntax specific to the webmapping application using the xtext tool. This concrete syntax is automatically converted into source code using the xtend tool without the intervention of the non-geomatics developers.展开更多
AIM: To study the validity of the fixed, random, and multivariate meta-analytical models applied in meta-analyses in artificial reproduction technique. METHODS: Based on common characteristics of in vitro fertilizatio...AIM: To study the validity of the fixed, random, and multivariate meta-analytical models applied in meta-analyses in artificial reproduction technique. METHODS: Based on common characteristics of in vitro fertilization(IVF) meta-analyses, we simulated a large number of data to compare results issued from the fixed model(FM) with the random model(RM). For multiple endpoints meta-analysis(MA), we compared the univariate RM with the multivariate model(MM). Finally, we illustrate our findings in re-analyzing a recent MA. RESULTS: In our review, although a homogeneous effect was excluded in 89% of the MAs(11%), FM was utilized in 41 studies(82%). From simulations, a concordance of 59% ± 6% was found between the two tests, with up to 65% of falsely significant results with FM. The Q-test on studies characterized by substantial heterogeneity falsely accepted homogeneity in 46% of studies. Comparing separate univariate RM and MM on multiple endpoints studies, MM reduces the between endpoint discrepancy(BED) of 68%, and increases the power of 57% ± 8%. In the example dealing with the controversial effect of luteneizing hormone supplementation to follicle stimulating hormone during ovarian stimulation in IVF cycles, MM reduced BED by 66%, and consistent effects were found for all the endpoints, irrespective of partial reporting. CONCLUSION: The FM generally may produce falsely significant differences. The RM should always be used. For multiple endpoints, the MM constitutes the best option.展开更多
目的基于贝叶斯网状Meta分析(Bayesian Network Meta-analysis,BNMA)方法,评价临床常用的口服或鼻饲中成药治疗脑出血(Intracerebral haemorrhage,ICH)术后的有效性及安全性。方法检索中国知网(CNKI)、万方数据知识服务平台(Wanfang)、...目的基于贝叶斯网状Meta分析(Bayesian Network Meta-analysis,BNMA)方法,评价临床常用的口服或鼻饲中成药治疗脑出血(Intracerebral haemorrhage,ICH)术后的有效性及安全性。方法检索中国知网(CNKI)、万方数据知识服务平台(Wanfang)、维普中文期刊(VIP)、中国生物医学文献服务系统(SinoMed)、PubMed、Embase、Cochrane Library、Web of Science建库至2023年8月25日有关中成药干预ICH术后的随机对照试验(randomized controlled trial,RCT);使用ROB 2.0进行偏倚风险评估,运用R 4.2.2加载BUGSnet 1.1.0程序包进行BNMA。结果共纳入28项RCT,总样本量2530例,涵盖9种口服中成药[安宫牛黄丸(AGNH)、苏合香丸(SHX)、脑血疏口服液(NXS)、脑心通胶囊(NXT)、脑血康片(NXK)、消瘀康胶囊(XYK)、养血清脑颗粒(YXQN)、通天口服液(TT)、三七通舒胶囊(SQTS)],所有患者均行手术治疗和术后常规西医治疗(conventional western medicine treatment,CWMT),试验组加用口服或鼻饲中成药。BNMA结果显示,AGNH+CWMT组在降低短期病死率、美国国立卫生研究院卒中量表评分(National Institute of Health stroke scale,NIHSS)和脑血肿周围水肿量方面排第1位,与CWMT组比较P<0.05;SHX+CWMT组在提高总有效率方面排第1位,与CWMT组比较P<0.05;TT+CWMT组在增加格拉斯哥昏迷评分(Glasgow Coma Scale,GCS)方面排第1位,与CWMT组比较P<0.05;YXQN+CWMT组在提高巴塞尔指数(Barthel index,BI)方面排第1位,与CWMT组比较P<0.05;NXS+CWMT组在促进脑血肿吸收量方面排第1位,与CWMT组比较P>0.05;NXT+CWMT组在缩短平均住院时间方面排第1位,与CWMT组比较P>0.05。结论与CWMT组比较,脑出血术后患者在CWMT基础上联用中成药治疗在提高总有效率,降低病死率、NIHSS评分,提高GCS评分、BI指数方面疗效确切,但在促进血肿吸收和缩短平均住院时间方面差异无统计学意义。AGNH综合疗效较好,可能为治疗ICH术后综合疗效最优的中成药。但由于纳入研究质量和方法学的局限性,所得结论仍需进一步验证。展开更多
目的系统评价胰十二指肠切除术后胰瘘(POPF)风险预测模型,为临床筛选应用POPF相关风险模型提供参考。方法本研究根据PRISMA指南完成,PROSPERO注册号:CRD42023437672。计算机检索PubMed、Scopus、Embase、Web of Science、Cochrane Libr...目的系统评价胰十二指肠切除术后胰瘘(POPF)风险预测模型,为临床筛选应用POPF相关风险模型提供参考。方法本研究根据PRISMA指南完成,PROSPERO注册号:CRD42023437672。计算机检索PubMed、Scopus、Embase、Web of Science、Cochrane Library、中国知网、维普网、万方、中华医学期刊全文数据库和中国生物医学文献数据库公开发表的胰十二指肠切除POPF风险预测模型构建的研究文献,检索时限为建库至2024年4月26日。采用PROBAST工具评价文献质量,RevMan 5.4、MedCalc软件进行Meta分析。结果共纳入36篇文献、20119例患者,胰十二指肠切除POPF发生率为7.4%~47.8%。36篇文献中,共构建55个风险预测模型,受试者工作特征曲线下面积(AUC)为0.690~0.952,其中52个模型AUC>0.7。文献质量评价结果均为高偏倚风险和适用性好。采用MedCalc软件对模型预测性能AUC进行统计学分析,合并的AUC为0.833(95%CI:0.808~0.857)。Meta分析显示:BMI、术后第1天引流液淀粉酶、术前血清白蛋白、胰管直径、胰腺质地、脂肪评分、肿瘤位置、失血量、性别、手术时间、主胰管指数、胰腺CT值是POPF的预测因子(P值均<0.05)。结论目前胰十二指肠切除POPF风险预测模型仍处于探索阶段,大部分预测模型的校准方法缺失,缺少外部验证,仅仅采用单因素分析筛选变量,偏倚风险较高,未来还需完善模型构建方法,以开发出预测准确度更高的风险预测模型。展开更多
基金Researchers Supporting Project Number(RSPD2024R 553),King Saud University,Riyadh,Saudi Arabia.
文摘Wheat is a critical crop,extensively consumed worldwide,and its production enhancement is essential to meet escalating demand.The presence of diseases like stem rust,leaf rust,yellow rust,and tan spot significantly diminishes wheat yield,making the early and precise identification of these diseases vital for effective disease management.With advancements in deep learning algorithms,researchers have proposed many methods for the automated detection of disease pathogens;however,accurately detectingmultiple disease pathogens simultaneously remains a challenge.This challenge arises due to the scarcity of RGB images for multiple diseases,class imbalance in existing public datasets,and the difficulty in extracting features that discriminate between multiple classes of disease pathogens.In this research,a novel method is proposed based on Transfer Generative Adversarial Networks for augmenting existing data,thereby overcoming the problems of class imbalance and data scarcity.This study proposes a customized architecture of Vision Transformers(ViT),where the feature vector is obtained by concatenating features extracted from the custom ViT and Graph Neural Networks.This paper also proposes a Model AgnosticMeta Learning(MAML)based ensemble classifier for accurate classification.The proposedmodel,validated on public datasets for wheat disease pathogen classification,achieved a test accuracy of 99.20%and an F1-score of 97.95%.Compared with existing state-of-the-art methods,this proposed model outperforms in terms of accuracy,F1-score,and the number of disease pathogens detection.In future,more diseases can be included for detection along with some other modalities like pests and weed.
文摘Activity based costing (ABC) is a method which can solve many limitations of the traditional cost systems in manufacturing management. In this paper, we investigate how to integrate ABC with workflow technology, and build a workflow meta model supporting ABC. Firstly, the concept and concept model of activity based costing (ABC) are introduced. Next, the meta model of P -PROCE (Process, Product, Resource, Organization, and Cost & Evaluation) is presented. Then the cost meta model is defined by adding ABC to P -PROCE model. Object constraint language (OCL) is used to express meta model and constraints. Finally, we show an enterprise modeling and simulation tool based on the workflow meta model. We can systematically construct an enterprise model and easily and efficiently conduct simulation. Moreover it enables us to analyze and evaluate business processes and its costs.
基金supported by the National Natural Science Foundation of China (Grant No. 41271003)the National Basic Research Program of China (Grants No. 2010CB428403 and 2010CB951103)
文摘Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on （1） a screening method （Morris） for qualitative ranking of parameters, and （2） a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model （RSMSobol）. First, the Morris screening method was used to qualitatively identify the parameters＇ sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model （RSM） were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.
基金Sponsored by the National Key Technology Research and Development Program of China(Grant No.2011BAK02B02)
文摘To investigate the application of meta-model for finite element( FE) model updating of structures,the performance of two popular meta-model,i. e.,Kriging model and response surface model( RSM),were compared in detail. Firstly,above two kinds of meta-model were introduced briefly. Secondly,some key issues of the application of meta-model to FE model updating of structures were proposed and discussed,and then some advices were presented in order to select a reasonable meta-model for the purpose of updating the FE model of structures. Finally,the procedure of FE model updating based on meta-model was implemented by updating the FE model of a truss bridge model with the measured modal parameters. The results showed that the Kriging model was more proper for FE model updating of complex structures.
文摘In this study, a new method for conversion of solid finite element solution to beam finite element solution is developed based on the meta-modeling theory which constructs a model consistent with continuum mechanics. The proposed method is rigorous and efficient compared to a typical conversion method which merely computes surface integration of solid element nodal stresses to obtain cross-sectional forces. The meta-modeling theory ensures the rigorousness of proposed method by defining a proper distance between beam element and solid element solutions in a function space of continuum mechanics. Results of numerical verification test that is conducted with a simple cantilever beam are used to find the proper distance function for this conversion. Time history analysis of the main tunnel structure of a real ramp tunnel is considered as a numerical example for the proposed conversion method. It is shown that cross-sectional forces are readily computed for solid element solution of the main tunnel structure when it is converted to a beam element solution using the proposed method. Further, envelopes of resultant forces which are of primary importance for the purpose of design, are developed for a given ground motion at the end.
文摘Engineering data are separately organized and their schemas are increasingly complex and variable. Engineering data management systems are needed to be able to manage the unified data and to be both customizable and extensible. The design of the systems is heavily dependent on the flexibility and self-description of the data model. The characteristics of engineering data and their management facts are analyzed. Then engineering data warehouse (EDW) architecture and multi-layer metamodels are presented. Also an approach to manage anduse engineering data by a meta object is proposed. Finally, an application flight test EDW system (FTEDWS) is described and meta-objects to manage engineering data in the data warehouse are used. It shows that adopting a meta-modeling approach provides a support for interchangeability and a sufficiently flexible environment in which the system evolution and the reusability can be handled.
基金Specialized Research Fund for the Doctoral Program of Higher Education,China (No.20010227012)
文摘Neural networks are being used to construct meta-models in numerical simulation of structures.In addition to network structures and training algorithms,training samples also greatly affect the accuracy of neural network models.In this paper,some existing main sampling techniques are evaluated,including techniques based on experimental design theory, random selection,and rotating sampling.First,advantages and disadvantages of each technique are reviewed.Then,seven techniques are used to generate samples for training radial neural networks models for two benchmarks:an antenna model and an aircraft model.Results show that the uniform design,in which the number of samples and mean square error network models are considered,is the best sampling technique for neural network based meta-model building.
文摘Our research focuses on creating a meta-model for generating a web mapping application. It was difficult for non-geomatics developers to implement a webmapping application. Indeed, this type of application uses geospatial data that require geomatics skills. For this reason, in order to help non-geomatics developers to set up a webmapping application, we have designed a meta-model that automatically generates a webmapping application using model-driven engineering. The created meta-model is used by non-geomatics developers to explicitly write the concrete syntax specific to the webmapping application using the xtext tool. This concrete syntax is automatically converted into source code using the xtend tool without the intervention of the non-geomatics developers.
文摘AIM: To study the validity of the fixed, random, and multivariate meta-analytical models applied in meta-analyses in artificial reproduction technique. METHODS: Based on common characteristics of in vitro fertilization(IVF) meta-analyses, we simulated a large number of data to compare results issued from the fixed model(FM) with the random model(RM). For multiple endpoints meta-analysis(MA), we compared the univariate RM with the multivariate model(MM). Finally, we illustrate our findings in re-analyzing a recent MA. RESULTS: In our review, although a homogeneous effect was excluded in 89% of the MAs(11%), FM was utilized in 41 studies(82%). From simulations, a concordance of 59% ± 6% was found between the two tests, with up to 65% of falsely significant results with FM. The Q-test on studies characterized by substantial heterogeneity falsely accepted homogeneity in 46% of studies. Comparing separate univariate RM and MM on multiple endpoints studies, MM reduces the between endpoint discrepancy(BED) of 68%, and increases the power of 57% ± 8%. In the example dealing with the controversial effect of luteneizing hormone supplementation to follicle stimulating hormone during ovarian stimulation in IVF cycles, MM reduced BED by 66%, and consistent effects were found for all the endpoints, irrespective of partial reporting. CONCLUSION: The FM generally may produce falsely significant differences. The RM should always be used. For multiple endpoints, the MM constitutes the best option.
文摘目的基于贝叶斯网状Meta分析(Bayesian Network Meta-analysis,BNMA)方法,评价临床常用的口服或鼻饲中成药治疗脑出血(Intracerebral haemorrhage,ICH)术后的有效性及安全性。方法检索中国知网(CNKI)、万方数据知识服务平台(Wanfang)、维普中文期刊(VIP)、中国生物医学文献服务系统(SinoMed)、PubMed、Embase、Cochrane Library、Web of Science建库至2023年8月25日有关中成药干预ICH术后的随机对照试验(randomized controlled trial,RCT);使用ROB 2.0进行偏倚风险评估,运用R 4.2.2加载BUGSnet 1.1.0程序包进行BNMA。结果共纳入28项RCT,总样本量2530例,涵盖9种口服中成药[安宫牛黄丸(AGNH)、苏合香丸(SHX)、脑血疏口服液(NXS)、脑心通胶囊(NXT)、脑血康片(NXK)、消瘀康胶囊(XYK)、养血清脑颗粒(YXQN)、通天口服液(TT)、三七通舒胶囊(SQTS)],所有患者均行手术治疗和术后常规西医治疗(conventional western medicine treatment,CWMT),试验组加用口服或鼻饲中成药。BNMA结果显示,AGNH+CWMT组在降低短期病死率、美国国立卫生研究院卒中量表评分(National Institute of Health stroke scale,NIHSS)和脑血肿周围水肿量方面排第1位,与CWMT组比较P<0.05;SHX+CWMT组在提高总有效率方面排第1位,与CWMT组比较P<0.05;TT+CWMT组在增加格拉斯哥昏迷评分(Glasgow Coma Scale,GCS)方面排第1位,与CWMT组比较P<0.05;YXQN+CWMT组在提高巴塞尔指数(Barthel index,BI)方面排第1位,与CWMT组比较P<0.05;NXS+CWMT组在促进脑血肿吸收量方面排第1位,与CWMT组比较P>0.05;NXT+CWMT组在缩短平均住院时间方面排第1位,与CWMT组比较P>0.05。结论与CWMT组比较,脑出血术后患者在CWMT基础上联用中成药治疗在提高总有效率,降低病死率、NIHSS评分,提高GCS评分、BI指数方面疗效确切,但在促进血肿吸收和缩短平均住院时间方面差异无统计学意义。AGNH综合疗效较好,可能为治疗ICH术后综合疗效最优的中成药。但由于纳入研究质量和方法学的局限性,所得结论仍需进一步验证。
文摘目的系统评价胰十二指肠切除术后胰瘘(POPF)风险预测模型,为临床筛选应用POPF相关风险模型提供参考。方法本研究根据PRISMA指南完成,PROSPERO注册号:CRD42023437672。计算机检索PubMed、Scopus、Embase、Web of Science、Cochrane Library、中国知网、维普网、万方、中华医学期刊全文数据库和中国生物医学文献数据库公开发表的胰十二指肠切除POPF风险预测模型构建的研究文献,检索时限为建库至2024年4月26日。采用PROBAST工具评价文献质量,RevMan 5.4、MedCalc软件进行Meta分析。结果共纳入36篇文献、20119例患者,胰十二指肠切除POPF发生率为7.4%~47.8%。36篇文献中,共构建55个风险预测模型,受试者工作特征曲线下面积(AUC)为0.690~0.952,其中52个模型AUC>0.7。文献质量评价结果均为高偏倚风险和适用性好。采用MedCalc软件对模型预测性能AUC进行统计学分析,合并的AUC为0.833(95%CI:0.808~0.857)。Meta分析显示:BMI、术后第1天引流液淀粉酶、术前血清白蛋白、胰管直径、胰腺质地、脂肪评分、肿瘤位置、失血量、性别、手术时间、主胰管指数、胰腺CT值是POPF的预测因子(P值均<0.05)。结论目前胰十二指肠切除POPF风险预测模型仍处于探索阶段,大部分预测模型的校准方法缺失,缺少外部验证,仅仅采用单因素分析筛选变量,偏倚风险较高,未来还需完善模型构建方法,以开发出预测准确度更高的风险预测模型。
