Construction Of Nomogram Model To Predict The Risk Of In-hospital MACE In Patients With STEMI Undergoing Primary PCI Treatment

BackgroundCoronary heart disease(CHD)is a global epidemic disease,which is a serious threat to the life safety of all human beings.In China,the number of patients with coronary heart disease is about 11 million,and its mortality rate is higher than that of other diseases such as tumor,and shows an upward trend every year.Among them,acute myocardial infarction(AMI)is the main cause of death caused by CHD.STsegment elevation myocardial infarction(STEMI)is the most common type of acute myocardial infarction(AMI),with the characteristics of acute onset and critical condition.Primary percutaneous coronary intervention(PCI)can open infarct related arteries timely,effectively,completely and continuously,which has become the first choice for patients with STEMI.However,there are still a considerable number of inhospital major adverse cardiovascular events(MACE)on STEMI patients after primary PCI treatment.And once occured,it will seriously affect the prognosis of patients.According to statistics,the in-hospital mortality rate of STEMI patients undergoing primary PCI is about 4%-12%,and the 1-year mortality rate is close to 10%.It is helpful for patients to benefit from treatment by accurate risk assessment and individualized treatment strategy.At present,the available scoring systems include:TIMI risk score,GRACE risk score,PAMI risk score,Zwolle risk score and so on,among which TIMI risk score is the most widely used.The TIMI risk score was established based on the data from the TIMI-II study.The patients included in this study were all STEMI patients undergoing thrombolytic therapy,and the analysis was of clinical features affecting the risk of death.Other MACEs also predict adverse outcomes,and the incidence is higher.However,other risk scoring systems are not widely used because of the complexity of prediction variables and poor accuracy.Therefore,the establishment of a convenient and effective prediction model to assess the risk of MACE in STEMI patients receiving primary PCI treatment has a positive effect on early identification of patients with high risk of in-hospital MACE and timely intervention,which is conducive to improving the prognosis of patients.Nomogram model is a kind of statistical model which graphizes the complex regression equation and is used to individually predict the outcome of the disease,which is intuitive and easy to understand,and has been paid more and more attention and application in medical research.Nomogram has been used to predict the prognosis of patients with cardiovascular disease,and its clinical value has been preliminarily confirmed.ObjectiveThis study intends to explore the independent predictive factors of in-hospital MACE in STEMI patients undergoing primary PCI treatment by analyzing it’s preoperative clinical characteristics.A nomogram model was constructed to predict the risk of in-hospital MACE in STEMI patients receiving primary PCI treatment,which could provide a new method for clinical evaluation of patients’ condition.MethodsThe clinical data of 387 STEMI patients,who received primary PCI treatment in Henan Provincial people’s Hospital from January 2017 to January 2020,were collected retrospectively.According to the occurrence of in-hospital MACE,the patients were divided into two groups: MACE group(n = 139 cases)and non-MACE group(n = 248cases),and compare the two groups.The independent predictors of in-hospital MACE in patients with STEMI undergoing primary PCI treatment were screened out by minimum absolute contraction selection operator(LASSO)-multivariate Logistic regression,and based on those independent predictive factors,a nomogram model for predicting in-hospital MACE risk in STEMI patients undergoing primary PCI treatment was constructed.C index and area under curve(AUC)of Receiver Operating Characteristic curve(ROC)were used to evaluate model differentiation and prediction accuracy.Internal verification and calibration curve were used to evaluate model calibration and prediction efficiency.And clinical application value of the model was evaluated by clinical decision curve analysis(DCA).Besides,ROC curve analysis and DCA were used to compare the predictive value of nomogram model and TIMI risk score for the occurrence of in-hospital MACE in STEMI patients undergoing primary PCI treatment.Results1.The proportion of female,age > 60 years,body mass index(BMI)≤24,old myocardial infarction,smoking history,Killip classification Ⅱ-Ⅳ,preoperative malignant arrhythmia,systolic blood pressure(SBP)≤100mm Hg,heart rate(HR)>100 beats/min,anterior wall myocardial infarction or bundle branch block(BBB),left ventricular ejection fraction(LVEF ≤50%),and ischemia time >6h were higher in MACE group(P < 0.05).2.The independent predictors of in-hospital MACE in STEMI patients undergoing primary PCI treatment included female(OR=2.86,95%CI:1.40-5.95,P=0.004),age >60 years old(OR=3.15,95%CI:1.68-6.01,P<0.001),the history of old myocardial infarction(OR=7.22,95%CI:2.90-19.22,P<0.001),Killip Ⅱ-Ⅳ grade(OR=5.77,95%CI:2.95-11.65,P<0.001),preoperative malignant arrhythmia(OR=14.95,95%CI:6.46-37.06,P<0.001),SBP ≤ 100 mm Hg(OR=5.06,95%CI:2.20-11.96,P<0.001),HR > 100bpm(OR=3.92,95%CI:1.81-4.58,P<0.001),anterior wall myocardial infarction or BBB(OR=2.60,95%CI:1.43-4.85,P=0.002),LVEF ≤50%(OR=3.45,95%CI:1.77-6.83,P<0.001)and ischemia time > 6hours(OR=2.63,95%CI:1.43-5.01,P=0.002).3.Based on those independent predictors above,a nomogram model for predicting in-hospital MACE risk in STEMI patients undergoing primary PCI treatment was constructed.The C-index and ROC-AUC of nomogram were 0.905(95%CI:0.890-0.920).The C-index of internal verification was 0.891,and the calibration curve of nomogram was close to the ideal model.DCA showed that there was a net benefit from using the nomogram model.4.ROC curve analysis showed that the ROC-AUC of nomogram model was higher than that of TIMI(0.905 vs 0.765 P < 0.001).DCA showed that the use of nomogram model could bring higher clinical net benefit than TIMI risk score.Conclusion1.The nomogram model based on independent predictors of the in-hospital MACE for STEMI patients undergoing primary PCI can directly,conveniently and effectively predict it’s risk of in-hospital MACE.2.Compared with TIMI risk score system,the nomogram model constructed in this study has higher predictive value for predicting the risk of MACE in STEMI patients receiving primary PCI treatment,and has certain value for clinical application.