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Predictive Value Of Stress Hyperglycemia Ratio On The Prognosis Of Patients With Acute Myocardial Infarction

Posted on:2024-09-02Degree:MasterType:Thesis
Country:ChinaCandidate:Y L SunFull Text:PDF
GTID:2544307082450324Subject:Clinical Medicine
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Objective The purpose of this study was to elucidate the relationship between the stress hyperglycemia ratio(SHR)and the short-term major adverse cardiac and cerebrovascular event(MACCE)risk and all-cause mortality risk in patients with acute myocardial infarction(AMI)and to explore the relationship between SHR and multivessel coronary artery disease(MVCAD).cerebrovascular event(MACCE)risk and all-cause mortality risk in patients with acute myocardial infarction(AMI),and to explore the relationship between SHR and short-term prognosis in patients with multivessel coronary artery disease(MVCAD)and MVCAD,and finally to investigate the feasibility of using SHR to construct a short-term prognostic model for AMI Finally,we investigated the feasibility of using SHR to construct a short-term prognostic model for patients with AMI.Methods A total of 2268 patients with AMI who visited the First Hospital of Lanzhou University from July 2017 to January 2021 were collected in this study,and after excluding patients with incomplete data,1612 patients were finally included in the final analysis.Patients were divided into ST segment elevation myocardial infarction(STEMI)and non-ST segment elevation myocardial infarction(NSTEMI)groups according to their diagnosis The study was further stratified by SHR tertile(SHR1,SHR2,and SHR3),diabetes status,and severity of coronary artery disease,respectively.The study endpoints were MACCE and all-cause death.Predictors with non-zero coefficients were screened using LASSO regression,independent predictors of the occurrence of MACCE within 30 days in AMI patients were analyzed using multifactor Cox regression,a column line graph model predicting the risk of MACCE within 30 days in AMI patients was constructed with predictors,the predictive efficacy of the predictive model was assessed using the C-index,and internal validation of the model was performed using the Bootstrap method.Results 1.The incidence of MACCE was highest in patients with STEMI in the SHR3 group with diabetes(20.4%)and the mortality rate was highest in the SHR3 group without diabetes(9.9%).the incidence of MACCE was highest in patients with NSTEMI in the SHR3 group without diabetes(25.3%)and the mortality rate was highest in the SHR3 group without diabetes(15.2%).2.SHR was significantly associated with the risk of MACCE and the risk of death in STEMI patients without diabetes(MACCE: HR=3.358,95%CI:2.323~4.855,P<0.001;all-cause death: HR=5.099,95%CI:2.900~8.965,P<0.001).For every 1-SD increase in SHR in STEMI patients with diabetes,the risk of MACCE increased 1.234-fold(HR=2.234,95%CI:1.472~3.391,P<0.001)and the risk of death increased1.529-fold(HR=2.529,95%CI : 1.366~4.683,P=0.003).SHR was associated with MVCAD in STEMI patients was significantly associated(OR=1.764,95%CI :1.112~2.799,P=0.016).The C-index of MACCE risk prediction model constructed by relying on SHR for STEMI patients was 0.766(95% CI:0.753~0.779),which had good predictive efficacy.3.SHR was significantly associated with MACCE risk and all-cause mortality risk in NSTEMI patients without diabetes(MACCE: HR=5.257,95% CI: 2.926 to 9.444,P<0.001;all-cause mortality: HR=9.238,95% CI: 3.822 to 22.322,P<0.001).The Cindex of the MACCE risk prediction model constructed by relying on SHR for NSTEMI patients was 0.818(95% CI: 0.792-0.843),which also had good predictive efficacy.Conclusions SHR was associated with short-term MACCE risk and mortality risk in STEMI patients and NSTEMI patients without diabetes;SHR was associated with MVCAD in STEMI patients,and SHR was an independent predictor of short-term MACCE and all-cause mortality in AMI-MVCAD patients;it was feasible to construct a line graph prediction model relying on SHR as short-term MACCE risk in AMI patients.
Keywords/Search Tags:Acute myocardial infarction, Stress hyperglycemia ratio, Diabetes mellitus, Multivessel coronary artery disease, Columnar graph prediction model
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