Evaluation Value Of Multiple Auxiliary Diagnostic Indexes And Combined Diagnosis In Patients With Pulmonary Embolism

Objective:Through the statistical analysis of the routine indexes of suspected pulmonary embolism patients in the people's Hospital of the autonomous region,the predictive model of suspected pulmonary embolism was established to improve the accuracy and specificity of diagnosis and reduce the delayed diagnosis and misdiagnosis rate of suspected pulmonary embolism patients.And make the routine relevant indicators play their own role in the diagnosis of pulmonary embolism,so that the medical staffs can better understand the indicators with specific value for the diagnosis of pulmonary embolism,reduce unnecessary examination items to reduce the burden of patients,and provide theoretical basis for the diagnosis of pulmonary embolism in basic medical institutions.Methods:361 patients with risk factors and clinical manifestations of pulmonary thromboembolism(PTE)who were treated in the people's Hospital of the autonomous region from May 2017 to December 2019 were randomly selected,and the computed pulmonary angiography(CTPA)was improved.According to the results of CTPA,the patients were divided into positive case group and negative control group.The results of relevant indexes of the two groups were recorded,and the indexes related to pulmonary embolism were selected by statistical method.In this paper,the routine indexes are analyzed by many factors and the prediction model is established.Then,the ROC process is used to analyze the ROC curve,and the prediction model is compared with the ROC curve of each index.Finally,the predictive equation of suspected pulmonary embolism patients was established.Results:Statistical analysis was made on several auxiliary examination indexes between the positive case group and the negative control group:1.The results of single-factor analysis showed that BMI,caprini score,Wells score,Geneva score,PO2,pH,D-dimer,CRP,ECG,lower limb vascular color doppler ultrasound were significantly different from negative control group(P<0.05),while pCO2,cholesterol,triglyceride,HDL,LDL,PCT Results there was no significant difference(P>0.05).2.The results of multiple-factor analysis showed that BMI,caprini score,Wells score,Geneva score,PO2,ECG,lower limb vascular color doppler ultrasound,PCO2 results of the positive case group and the negative control group were significantly different(P<0.05).3.After logistic regression,the predictive diagnosis model of pulmonary embolism.The accuracy of this model in diagnosing pulmonary embolism is higher than other indexes.Conclusion:The results of BMI,caprini,wells,Geneva,PO2,plasma pH,D-dimer,CRP,ECG,and lower limb vascular color doppler ultrasound examination have good accuracy in the diagnosis of pulmonary embolism.The predictive diagnosis model of pulmonary embolism has a high coincidence rate for the diagnosis of pulmonary embolism,which can provide a theoretical basis for the rapid clinical diagnosis and the diagnosis of pulmonary embolism in primary medical institutions.