Establishment And Validation Of A Risk Model For Prediction Of In-hospital Mortality In Patients With Acute ST-elevation Myocardial Infarction After Primary PCI

With the rapid aging of our society and the prevalence of unhealthy life style,cardiovascular disease(CVD)of our country presents a rapid growth trend in the low-aged and low-income groups.According to China Cardiovascular Disease Report 2017,the number of CVD patients in China is estimated to be 290 million,and the number of CVD patients will still increase rapidly in the next 10 years.Acute Myocardial Infarction(AMI)is the leading killer of cardiovascular diseases.Its pathophysiological mechanism is due to unstable coronary atherosclerotic plaque,local thrombosis caused by rupture of intima,and finally acute occlusion of coronary artery,clinical manifestations of myocardial ischemia and anoxic necrosis.At present,the most effective method is to open the occluded blood vessel in the shortest time,so that the myocardial cells in the ischemic site can get the blood supply again,and save the dying myocardial cells.According to the national health and Family Planning Commission(NHFPC),55,833 patients with acute ST-segment Elevation Myocardial Infarction(STEMI)underwent emergency percutaneous coronary intervention(PCI)in China in 2016,with a mortality rate of 0.21%.Although emergency PCI technology is becoming more and more mature,there are still some STEMI patients with high mortality even after emergency PCI.Which patients are at high risk,which factors determine their high risk of death,and how to identify high risk patients early pose a challenge to clinicians.In order to solve these problems,researchers have proposed a clinical predictive model scheme,that is,to predict the unknown by the known,and to calculate the unknown future by the known data through complex formulas.Its essence is regression modeling analysis,discovering patterns,predicting the future.The outcome of coronary stent implantation and coronary artery bypass grafting in patients with multiple coronary artery disease was observed by Bangalore s et al.They found that using a syntax score to determine surgical protocol improved patient outcomes.The study promotes the clinical use of syntax scores to guide clinicians’ decision-making in patients with multiple coronary artery disease.The Global Register of acute coronary events prognostic score(Grace Score)is based on age,heart rate,systolic blood pressure,creatinine level,Killip grade,presence or absence of cardiac arrest,St Segment elevation on Electrocardiogram,and presence or absence of myocardial necrosis markers,to establish a predictive model to predict the in-hospital and out-of-hospital mortality of patients with Acute Coronary Syndrome(ACS)within 6 months has been widely used in clinical practice.Chen Yundai et al used predictive model method to analyze the blood glucose of patients with age > 65 years,reperfusion time > 6 hours,collateral flow ≤ 1 Grade,Admission Blood Glucose > 13 mmol/l,preoperative Thrombus Score ≥ 4 and preoperative IABP use were independent predictors of no-reflow after PCI in patients with acute myocardial infarction.In 540 patients with acute myocardial infarction(AMI)who underwent PCI,it was found that female patients,Killip grade ≥ 2,TIMI grade ≤ 2 before PCI,Thrombus Score ≥ 4 before PCI,the time from onset to balloon dilatation(>6 hours)was the risk factor of no-reflow during operation,prospective study of 94 patients with acute myocardial infarction undergoing emergency PCI confirmed the validity of the model.At present,there is no report on the prediction and evaluation of in-hospital mortality in patients with acute ST-segment elevation myocardial infarction after emergency PCI.In recent 2 years,the construction of chest pain center in China has effectively treated more patients with acute ST segment elevation myocardial infarction,but there are still some patients with higher risk of death in hospital,based on the large data of chest pain center in Hebei Province in recent 2 years,this study aims to establish a high-risk predictive model for patients with acute ST-segment elevation myocardial infarction after emergency PCI,to provide the basis for clinical workers to find the patients with high-risk emergency PCI.Part One Screening for in-hospital death risk factors in patients with acute ST-elevation myocardial infarction after primary PCIObjective: Emergency percutaneous coronary intervention(PCI),improves the prognosis of patients with acute ST-segment elevation myocardial infarction(STEMI).However,for some acute STEMI cases the risk of death in hospital remains relatively high.The aim of this study was to investigate risk factors for in-hospital death after PCI for acute STEMI.Methods: Patients with acute STEMI treated with emergency PCI at Hebei General Hospital,Baoding First Central Hospital and Cangzhou Central Hospital,China from January 2016 to June 2018 were included retrospectively.The patients’ general data,previous medical history,clinical data,and medication were collected and compared between the survival and mortality groups.Results: Of 1169 patients(876 males and 293 females),95(8.13%)died during hospitalization.Multivariate logistic regression analysis showed that being female(OR=5.86,95%CI:2.03-16.92,P=0.001),Killip class=2(OR=8.13,95%CI:2.03-32.61,P=0.003),Killip class=4(OR=17.31,95%CI:3.69-81.27,P=0.001),left main coronary artery lesion(OR=44.25,95%CI:3.96-494.05,P=0.002),final TIMI flow=1(OR=171.83,95%CI:28.46-1037.51,P=0.001),final TIMI flow=2(OR=72.93,95%CI:38.54-138.00,P=0.001),onset to first medical contact time(OR=1.01,95%CI:1.00-1.02,P=0.001),onset to balloon dilatation time(OR=1.01,95%CI:1.00-1.02,P=0.001),SYNTAX score(OR=1.07,95% CI:1.01-1.12,P=0.019)and CK-MB peak(OR=1.01,95% CI:1.00-1.02,P=0.043)were risk factors;while postoperative β-receptor blockers(OR=0.10,95%CI:0.03-0.30,P=0.001)postoperative ACEI/ARB(OR=0.13,95%CI:0.04-0.44,P=0.001),BMI(OR=0.85,95% CI:0.74-0.98,P=0.024),percentage of ejection fraction(OR=0.81,95% CI:0.75-0.86,P=0.001),and low-density lipoprotein cholesterol(OR=0.44,95% CI:0.21-0.91,P=0.027)were protective factors for in-hospital mortality.Summary: This study identified a number of factors related to the risk of in hospital mortality after PCI for acute STEMI.female,Killip class,left main coronary artery lesion,final TIMI flow,symptom to door time,symptom to balloon dilatation time,SYNTAX score and CK-MB peak were risk factors;while postoperative β-receptor blockers,postoperative ACEI/ARB,BMI,ejection fraction,and low-density lipoprotein cholesterol were protective factors for in-hospital mortality.Part Two Relationship between in-hospital death and total ischemic time in patients with acute ST-segment elevation myocardial infarction after primary PCIObjective: In the first part of the study,we analyzed the data and found that the time fromsymptom to balloon dilation(total ischemic time)was a risk factor for in-hospital death in patients with acute ST-segment elevation myocardial infarction undergoing primary PCI.The purpose of this part of study was to further determine the relationship between total ischemic time and in-hospital death in patients with acute ST-segment elevation myocardial infarction by adjusting for confounding factors.Methods: This was a multicenter,observational study of patients with acute STEMI who underwent primary PCI.The patients’ demographic data,clinical characteristics,coronary angiography and intervention results,and chest pain related data were collected.The presence or absence of in-hospital death was taken as the dependent variable and total ischemic time as the independent variable.The relationship between total ischemic time and the risk of in-hospital death was determined by Logistic regression analysis after adjusting for the potential confounding factors obtained in Part I.Results: First,we divided the total ischemia time into four grades: ≤120minutes,121-240 minutes,241-360 minutes,and ≥361 minutes.Then,we tested whether there was an interaction between the risk factors identified in the first part and the total ischemic time.We found an interaction between EF and total ischemia time(P=0.01),but no interaction between other risk factors and total ischemia time(P>0.17).We stratified the data according to whether EF was normal or not.Finally,we found that the ORs(95% confidence interval)of in-hospital death and total ischemic time were 1.00(reference),1.02(1.01,1.16),1.04(1.02,1.39),1.49(1.16,1.64)(P for trend=0.02)in patients with EF<50%.But,For patients with EF>50%,the ORs(95% confidence interval)of in-hospital death and total ischemic time were1.00(reference),1.04(0.84,1.27),2.45(1.09,3.41),1.25(1.08,2.02)(P for trend=0.14).Summary: After adjusting for confounding factors,patients with acute ST-elevation myocardial infarction with EF<50% who underwent primary PCI had a 49% higher risk of in-hospital death in patients with total ischemic time≥361 minutes than in patients with total ischemic time ≤120 minutes.However,no association was found between total ischemic time and in-hospital death in patients with EF<50%.Part Three Establishment and validation of a risk model for prediction of in-hospital mortality in patients with acute ST-elevation myocardial infarction after primary PCIObjective: Currently,how to accurately determine the patient prognosis after a percutaneous coronary intervention(PCI)remains unclear and may vary among populations,hospitals,and datasets.The aim of this study was to establish a prediction model of in-hospital mortality risk after primary PCI in patients with acute ST-elevated myocardial infarction(STEMI).Methods: This was a multicenter,observational study of patients with acute STEMI who underwent primary PCI.The outcome was in-hospital mortality.The least absolute shrinkage and selection operator(LASSO)method was used to select the features that were the most significantly associated with the outcome.A regression model was built using the selected variables to select the significant predictors of mortality.Receiver operating characteristic(ROC)curve and decision curve analysis(DCA)were used to evaluate the performance of the nomogram.Results: Totally,1169 and 316 patients were enrolled in the training and validation sets,respectively.Fourteen predictors were identified by the LASSO analysis: sex,Killip classification,left main coronary artery disease(LMCAD),grading of thrombus,TIMI classification,slow flow,application of IABP,administration of β-blocker,ACEI/ARB,symptom-to-door time(SDT),symptom-to-balloon time(SBT),syntax score,left ventricular ejection fraction(LVEF),and CK-MB peak.The mortality risk prediction nomogram achieved good discrimination and good calibration for in-hospital mortality(training set: AUC=0.987,95% CI: 0.981–0.994,P=0.003;model calibration:P=0.722;validation set: AUC=0.990,95% CI: 0.987–0.998,P=0.007).DCA shows that the nomogram can achieve good net benefit.Summary: A novel nomogram was developed and is a simple and accurate tool for predicting the risk of in-hospital mortality in patients with acute STEMI who underwent primary PCI.