This paper presents a tool for managing, reusing and analysing C software code based on database techniques. The abstract information of entire software code is stored in a program database that is the conceptual sche...This paper presents a tool for managing, reusing and analysing C software code based on database techniques. The abstract information of entire software code is stored in a program database that is the conceptual scheme of the entire software, whereas the reuse component is a subscheme. Relational algebra can be conveniently used to manage, analyse and reuse C code. In the tool, we can manage, analyse and reuse any components in the program database and rapidly extract source code of any components or construct the program code of a new system. The rule system is introduced in reusing source code.展开更多
BACKGROUND Gastric cancer(GC)is prevalent and aggressive,especially when patients have distant lung metastases,which often places patients into advanced stages.By identifying prognostic variables for lung metastasis i...BACKGROUND Gastric cancer(GC)is prevalent and aggressive,especially when patients have distant lung metastases,which often places patients into advanced stages.By identifying prognostic variables for lung metastasis in GC patients,it may be po-ssible to construct a good prediction model for both overall survival(OS)and the cumulative incidence prediction(CIP)plot of the tumour.AIM To investigate the predictors of GC with lung metastasis(GCLM)to produce nomograms for OS and generate CIP by using cancer-specific survival(CSS)data.METHODS Data from January 2000 to December 2020 involving 1652 patients with GCLM were obtained from the Surveillance,epidemiology,and end results program database.The major observational endpoint was OS;hence,patients were se-parated into training and validation groups.Correlation analysis determined va-rious connections.Univariate and multivariate Cox analyses validated the independent predictive factors.Nomogram distinction and calibration were performed with the time-dependent area under the curve(AUC)and calibration curves.To evaluate the accuracy and clinical usefulness of the nomograms,decision curve analysis(DCA)was performed.The clinical utility of the novel prognostic model was compared to that of the 7th edition of the American Joint Committee on Cancer(AJCC)staging system by utilizing Net Reclassification Improvement(NRI)and Integrated Discrimination Improvement(IDI).Finally,the OS prognostic model and Cox-AJCC risk stratification model modified for the AJCC system were compared.RESULTS For the purpose of creating the OS nomogram,a CIP plot based on CSS was generated.Cox multivariate regression analysis identified eleven significant prognostic factors(P<0.05)related to liver metastasis,bone metastasis,primary site,surgery,regional surgery,treatment sequence,chemotherapy,radiotherapy,positive lymph node count,N staging,and time from diagnosis to treatment.It was clear from the DCA(net benefit>0),time-de-pendent ROC curve(training/validation set AUC>0.7),and calibration curve(reliability slope closer to 45 degrees)results that the OS nomogram demonstrated a high level of predictive efficiency.The OS prediction model(New Model AUC=0.83)also performed much better than the old Cox-AJCC model(AUC difference between the new model and the old model greater than 0)in terms of risk stratification(P<0.0001)and verification using the IDI and NRI.CONCLUSION The OS nomogram for GCLM successfully predicts 1-and 3-year OS.Moreover,this approach can help to ap-propriately classify patients into high-risk and low-risk groups,thereby guiding treatment.展开更多
Objectives:Appropriate scenarios of lumbar drain(LD)use in endonasal skull base surgery is an active area of investigation.However,existing data is limited.The purpose of this study is to evaluate the robustness of th...Objectives:Appropriate scenarios of lumbar drain(LD)use in endonasal skull base surgery is an active area of investigation.However,existing data is limited.The purpose of this study is to evaluate the robustness of the NSQIP database to characterize morbidity and complications associated with LD usage concurrent to minimally invasive resection of pituitary tumors.Methods:A cross-sectional analysis of the American College of Surgeons National Surgical Quality Improvement Program database was used to query patients undergoing transnasal resection of pituitary tumor.Patients were stratified by concurrent perioperative use of LD and outcomes were compared.Results:A total of 1714 patients underwent minimally invasive endonasal(microscopic or endoscopic)pituitary tumor resection,of which LD was concurrently placed in 98(5.7%)cases.Operative time was significantly longer for patients who had LD placed compared to those without(176.5 min(IQR 114.8-229.5)vs.137 min[IQR 100-185]),(p<0.001)with a significantly longer length of stay(5 days[IQR 4-6]vs.3 days[IQR 2-5]),(p<0.001).Multivariate regression demonstrated LD placement was an independent predictor of postoperative medical complication(OR 2.41,95%CI 1.15-5.03,p=0.020)and unplanned readmission(OR 2.06,95%CI 1.02-4.16,p=0.044),but not CSF leak(OR 2.30,95%CI 0.51-10.26;p=0.276).Temporal analysis during the study period demonstrated a decrease in LD use from 8%to 5%(R2=0.60;p=0.025).Conclusions:The NSQIP database provides a large patient population for examining LD use in endoscopic pituitary adenoma resection.LD use for minimally invasive pituitary surgery is associated with postoperative medical complications and unplanned readmissions,with no apparent impact on reconstructive outcomes,and there is overall decreasing usage.Clinical judgment should be exercised in selecting appropriate scenarios for use.展开更多
文摘This paper presents a tool for managing, reusing and analysing C software code based on database techniques. The abstract information of entire software code is stored in a program database that is the conceptual scheme of the entire software, whereas the reuse component is a subscheme. Relational algebra can be conveniently used to manage, analyse and reuse C code. In the tool, we can manage, analyse and reuse any components in the program database and rapidly extract source code of any components or construct the program code of a new system. The rule system is introduced in reusing source code.
基金Supported by Peng-Cheng Talent-Medical Young Reserve Talent Training Program,No.XWRCHT20220002Xuzhou City Health and Health Commission Technology Project Contract,No.XWKYHT20230081and Key Research and Development Plan Project of Xuzhou City,No.KC22179.
文摘BACKGROUND Gastric cancer(GC)is prevalent and aggressive,especially when patients have distant lung metastases,which often places patients into advanced stages.By identifying prognostic variables for lung metastasis in GC patients,it may be po-ssible to construct a good prediction model for both overall survival(OS)and the cumulative incidence prediction(CIP)plot of the tumour.AIM To investigate the predictors of GC with lung metastasis(GCLM)to produce nomograms for OS and generate CIP by using cancer-specific survival(CSS)data.METHODS Data from January 2000 to December 2020 involving 1652 patients with GCLM were obtained from the Surveillance,epidemiology,and end results program database.The major observational endpoint was OS;hence,patients were se-parated into training and validation groups.Correlation analysis determined va-rious connections.Univariate and multivariate Cox analyses validated the independent predictive factors.Nomogram distinction and calibration were performed with the time-dependent area under the curve(AUC)and calibration curves.To evaluate the accuracy and clinical usefulness of the nomograms,decision curve analysis(DCA)was performed.The clinical utility of the novel prognostic model was compared to that of the 7th edition of the American Joint Committee on Cancer(AJCC)staging system by utilizing Net Reclassification Improvement(NRI)and Integrated Discrimination Improvement(IDI).Finally,the OS prognostic model and Cox-AJCC risk stratification model modified for the AJCC system were compared.RESULTS For the purpose of creating the OS nomogram,a CIP plot based on CSS was generated.Cox multivariate regression analysis identified eleven significant prognostic factors(P<0.05)related to liver metastasis,bone metastasis,primary site,surgery,regional surgery,treatment sequence,chemotherapy,radiotherapy,positive lymph node count,N staging,and time from diagnosis to treatment.It was clear from the DCA(net benefit>0),time-de-pendent ROC curve(training/validation set AUC>0.7),and calibration curve(reliability slope closer to 45 degrees)results that the OS nomogram demonstrated a high level of predictive efficiency.The OS prediction model(New Model AUC=0.83)also performed much better than the old Cox-AJCC model(AUC difference between the new model and the old model greater than 0)in terms of risk stratification(P<0.0001)and verification using the IDI and NRI.CONCLUSION The OS nomogram for GCLM successfully predicts 1-and 3-year OS.Moreover,this approach can help to ap-propriately classify patients into high-risk and low-risk groups,thereby guiding treatment.
文摘Objectives:Appropriate scenarios of lumbar drain(LD)use in endonasal skull base surgery is an active area of investigation.However,existing data is limited.The purpose of this study is to evaluate the robustness of the NSQIP database to characterize morbidity and complications associated with LD usage concurrent to minimally invasive resection of pituitary tumors.Methods:A cross-sectional analysis of the American College of Surgeons National Surgical Quality Improvement Program database was used to query patients undergoing transnasal resection of pituitary tumor.Patients were stratified by concurrent perioperative use of LD and outcomes were compared.Results:A total of 1714 patients underwent minimally invasive endonasal(microscopic or endoscopic)pituitary tumor resection,of which LD was concurrently placed in 98(5.7%)cases.Operative time was significantly longer for patients who had LD placed compared to those without(176.5 min(IQR 114.8-229.5)vs.137 min[IQR 100-185]),(p<0.001)with a significantly longer length of stay(5 days[IQR 4-6]vs.3 days[IQR 2-5]),(p<0.001).Multivariate regression demonstrated LD placement was an independent predictor of postoperative medical complication(OR 2.41,95%CI 1.15-5.03,p=0.020)and unplanned readmission(OR 2.06,95%CI 1.02-4.16,p=0.044),but not CSF leak(OR 2.30,95%CI 0.51-10.26;p=0.276).Temporal analysis during the study period demonstrated a decrease in LD use from 8%to 5%(R2=0.60;p=0.025).Conclusions:The NSQIP database provides a large patient population for examining LD use in endoscopic pituitary adenoma resection.LD use for minimally invasive pituitary surgery is associated with postoperative medical complications and unplanned readmissions,with no apparent impact on reconstructive outcomes,and there is overall decreasing usage.Clinical judgment should be exercised in selecting appropriate scenarios for use.
