PSTEMI Model: Exploration Of A New Perioperative Risk Evaluation Model In Patients Treated With Primary Percutaneous Coronary Intervention

BackgroundThere are about 290 million cardiovascular patients in China.About 2.5 million patients suffered myocardial infarction,71.1%of whom suffered STEMI.STEMI,as clinical critical illness,is one of the main death causes in China;The pPCI can significantly reduce the mortality of patients.However,these patients are still unable to avoid the occurrence of major adverse cardiovascular events（MACE）during perioperative period.When MACE occurs,the mortality rate will increase significantly.The prognosis of patients with STEMI treated with pPCI depends on various factors.It is a problem to identify these high-risk patients as soon as possible for clinicians.In the past few decades,the academic community has put forward varieties of risk prediction models in patients with STEMI,such as TIMI risk score,TIMI risk index,Zwolle pPCI risk index,ACEF-STEMI score and so on.However,these models had different defects:the endpoints predicted were all almost long-term death events,and the models were complicated and non-uniform.It failed to predict the risk of STEMI patients in emergency at bedside.Therefore,it wasn’t be able to be used extendedly in clinical practice.Moreover,the risk in perioperative period in STEMI patients is under-emphasized.So,it has not been promoted for clinical use.ObjectiveThis study intends to explore a simple,practical,and rapid risk score model for perioperative risk assessment in STEMI patients treated with pPCI.In order to assess the occurrence of MACE during perioperative period while deciding to undergo pPCI for them.MethodsA continuous collection of 548 STEMI patients treated with pPCI in emergency department of Henan Provincial People’s Hospital from December 2015 to December 2018.The variables were selected based on the risk stratification model proposed and the characteristics of the study,including general information:symptoms-signature time,gender,age;past medical history:history of hypertension,history of diabetes,history of previous angina,history of smoking,history of drinking,the history of heart failure;admission examination:electrocardiograph（anterior myocardial infarction location）,systolic blood pressure（SBP）,heart rate（HR）,left ventricular ejection fraction（LVEF）,and saturation of pulse oxygen（SpO₂）.The study endpoint was defined as major adverse cardiovascular events（MACE）during perioperative period（admission to postoperative 24 hours）,a composite event of cardiac shock（CS）,sustained ventricular tachycardia（SVT）,myocardial reinfarction,ventricular fibrillation（VF）,stroke,and death.Patients included were divided into MACE group（n=214）and non-MACE group（n=334）according to occurrence of MACE in perioperative period.The measurement variables were converted to categorical variables.Which were expressed as a percentage（%）and analyzed by using SPSS 22.0 statistical software.At first,univariate analysis was performed for data of the two groups to screen out the possible impact of MACE（P<0.05）.Then,the statistically significant variables（P<0.05）were included in multivariate logistic regression analysis to determine the independent risk factors for MACE.The basis included in this model was P<0.05.The odds ratio（OR）of each variable minus 1 to the nearest whole number to the variable,which was primary score model in STEMI patients（PSTEMI model）.All patients were divided into low-risk and high-risk groups based on their scores in PSTEMI model.The model discrimination was detected by receiver operating characteristic curve（ROC）,and the fitting performance of the model was evaluated according to the Hosmer-Lemeshow（H-L）test.Results1.The average age of 548 patients included in the study was 57.58±11.65 years old.There are 440（80.3%）males and 108 females（19.7%）;2.Univariateanalysis showed:Comparedwith non-MACE group,symptoms-signature time,female,SBP,HR,the history of heart failure,age,SpO₂,non-previous angina,LVEF,history of hypertension,history of smoking,the difference was statistically significant（P<0.05）and there was no significant difference in the history of diabetes and drinking history（P>0.05）.3.Multivariate regression analysis showed:symptom-signature time,female,SBP,HR,history of heart failure,anterior myocardial infarction,age,SpO₂,non-previous angina and LVEF were independent risk factors of perioperative MACE for STEMI patients treated with pPCI.4.The exploration of primary score model in STEMI patients（PSTEMI model）and risk stratification:We explored a new risk stratification model-PSTEMI model,which may be used to assess the occurrence of perioperative MACE in STEMI patientstreatedwithpPCI.Thefollowingvariableswereincluded:symptom-signature time（151-450 min,2 points;>450 min,3 points）,female（1point）,SBP<100 mmHg（1 point）),HR（≥101 beats/min（bpm）,2 points;60-80bpm,1 point;≤59 bpm,2 points）,history of heart failure（1 point）,age（≥71years,3 points;60-70 years,2 points）,SpO₂（85%-89%,2 points;≤84%,3 points）,non-previous angina（1 point）,anterior myocardial infarction（1 point）,LVEF（40%-49%,1 point;≤39%,3 points）.The PSTEMI model had a total scores of 0-17.The ROC analysis showed 6points were the best cutoff value for predicting occurrence of MACE.All patients were divided into two risk groups,318 patients were low-risk group（0-6 points）and230 patients were in the high-risk group（7-17 points）;There were 59 cases（18.55%）and 155 cases（67.39%）having perioperative MACE,respectively.The difference was statistically significant（P=0.000）.5.Validation of PSTEMI score:ROC analysis showed that the PSTEMI score model identified a good discrimination for occurrence of perioperative MACE（C statistic:0.816±0.019,95%CI:0.779-0.853,P=0.000）.The H-L test evaluated good fitting performance of the model（correlation coefficient:1.027,P=0.405）.Conclusion1.We explored a new risk score model that may be used to evaluate the perioperative risk in STEMI patients treated with pPCI-PSTEMI model;2.The model is simple,practical,and fast to evaluate the risk while deciding to undergo pPCI in STEMI patients.