| Part 1 Constructing a risk prediction model for percutaneous coronary intervention related myocardial infarctionBackground and objective:With the development of interventional technology and the update of stent materials,percutaneous coronary intervention(PCI)has become an important method for treatment of coronary artery disease(CAD).Over the past decades,PCI has become a common therapeutic procedure for revascularization,with minimal procedural complications.However,PCI related myocardial infarction(PMI)cannot be completely avoided,which is significantly related to poor prognosis.Therefore,it is particularly important to explore the risk factors of PMI and to construct a risk prediction model of PMI.Numerous studies have investigated the risk factors of PMI,however,to our knowledge,there is a lack of predictive model of PMI that combines multiple risk factors.The present study aims to construct a simple and practical risk prediction model of PMI to assess the risk of PMI in CAD patients undergoing PCI.Methods:This study was a single-center retrospective study.Patients with CAD who underwent elective single-vessel PCI from December 2009 to April 2019 in our hospital were recruited in this study.Their general information,medical history data,medication,blood routine examinations,blood biochemical examinations,cardiac function examinations,lesion characteristics,periprocedural treatment,characteristics of implanted stents were collected.The main body of this study was mainly composed of the following three parts.In the first part,the overall patients were divided into PMI group and non-PMI group according to whether PMI occurred after PCI.Then the differences of baseline characteristics between the two groups were compared.In the second part,single-variable Logistic regression analysis was conducted to initially selected the variables that significantly related to PMI.Then the LASSO regression was employed to select to regularized variables that independently related to PMI.In the third part,the multi-variable Logistic regression was used to construct the risk prediction model of PMI.Additionally,a nomogram was plotted to provide a visual inspection of the model.Finally,the receiver operating characteristic(ROC)curve was used to evaluate the discrimination of the model,and the calibration curve was used to evaluate the calibration of the model.Results:In total,9370 patients were included in this study.There were 1293 patients in the PMI group,and 8077 patients in the non-PMI group.The incidence of PMI was about13.8%.A total of 32 variables were selected in the single-variable Logistic regression analysis,and a combination of 8 variables was selected in the LASSO regression analysis.These 8 variables were confirmed as independently predictive factors for PMI in the multi-variable Logistic regression analysis:age>65 years(OR=1.284,95%CI:1.128-1.461,P<0.001),high sensitivity C-reactive protein>5 mg/L(OR=1.327,95%CI:1.139-1.546,P<0.001),e GFR<60 m L/min/1.73m~2(OR=1.391,95%CI:1.175-1.646,P<0.001),NT-pro BNP>1800 pg/m L(OR=1.752,95%CI:1.391-2.208,P<0.001),left main lesions(OR=1.594,95%CI:1.280-1.985,P<0.001),calcified lesions(OR=1.487,95%CI:1.259-1.757,P<0.001),number of stents>1(OR=1.506,95%CI:1.291-1.759,P<0.001),total length of the stent>30 mm(OR=2.114,95%CI:1.790-2.498,P<0.001).The risk prediction model of PMI was:Y=0.250*(age>65 years old)+0.283*(hypersensitive C-reactive protein>5 mg/L)+0.330*(e GFR<60 m L/min/1.73m~2)+0.561*(NT-pro BNP>1800 pg/m L)+0.466*(left main lesion)+0.397*(calcified lesion)+0.410*(number of stents>1)+0.749*(total length of stent>30 mm)-2.824.Additionally,a nomogram of the model was drawn to increase clinical operability.The area under the ROC curve of this model was 0.684(95%CI:0.668-0.699,P<0.001),and the calibration curve showed that the predicted PMI risk was almost consistent with the actually observed PMI risk.Conclusions:The current study supported that the elderly,high level of hypersensitivity C-reactive protein,low level of e GFR,high level of NT-pro BNP,left main lesion,calcified lesion,number of stents and total length of stents were independent risk factors of PMI in patients with CAD who underwent elective single-vessel PCI.The risk predicting model of PMI constructed in this study based on these 8 factors can be used to evaluate the PMI risk of patients with CAD after elective single-vessel PCI.Part 2 Exploring the effects of β-blockers and ACEI/ARB on the prognosis of patients with percutaneous coronary intervention related myocardial infarctionBackground and objective: Percutaneous coronary intervention related myocardial infarction(PMI)is a common complication of percutaneous coronary intervention(PCI),which is associated with adverse prognosis.β-blockers and angiotensin converting enzyme inhibitor(ACEI)/angiotensin II receptor blockers(ARB)have been recommended for the secondary prevention of spontaneous acute myocardial infarction.However,it remains unclear whether β-blockers and ACEI/ARB can benefit patients with PMI.The current study aimed to explore the effects of β-blockers and ACEI/ARB on the prognosis of patients with PMI.Methods: This study was a single-center retrospective study.Patients who underwent elective single-vessel PCI and with a diagnosis of PMI from December 2009 to April 2019 in our hospital were recruited in this study.All the individuals were followed up with drug treatment and related clinical events for up to 5 years.The primary endpoint of present study was the major adverse cardiovascular events(MACE),which was a composite endpoint of all-cause death,non-fatal myocardial infarction,stroke,and revascularization.The secondary endpoints were the respective adverse cardiovascular events: including all-cause death,non-fatal myocardial infarction or stroke,revascularization.The main body of this study was consisted of the following three parts.In the first part,the overall follow-up patients were divided into BB group and non-BB group according to whether they took β-blockers.Then the differences of baseline characteristics between these two groups were compared.Similarly,the overall follow-up patients were also divided into ACEI/ARB group and non-ACEI/ARB group according to whether they took ACEI/ARB,and the differences of baseline characteristics between the two groups were also compared.In the second part,Cox regression analysis and Kaplan-Meier analysis were conducted to appraising the effects of β-blockers and ACEI/ARB on MACE incident in patients with PMI.In addition,the overall individuals were divided into subgroups based on gender,age,hypertension,diabetes,renal insufficiency,cardiac insufficiency and the level of cardiac troponin I respectively,and then subgroups analysis was conducted.Moreover,landmark analysis was conducted and a 1-year follow-up was set as the cut-off time.In the last part,Cox regression analysis and Kaplan-Meier analysis were employed to investigate the effects of β-blockers and ACEI/ARB on the incident of secondary endpoints(including all-cause death,non-fatal myocardial infarction or stroke,revascularization)in patients with PMI.Additionally,subgroup analysis and landmark analysis were conducted for revascularization incident.Results: In total,1293 patients were included in this study.A total of 1001 individuals were followed up,and the median follow-up time was 1295 days.During the follow-up period,617 patients took the beta-blockers,662 patients took the ACEI/ARB,190 patients were observed with MACE incident,47 patients were observed with all-cause death incident,and 30 patients were observed with non-fatal myocardial infarction or stroke incident,125 patients were observed with revascularization incident.Multivariate Cox regression analysis showed that use of β-blockers(HR=0.891,95%CI: 0.661-1.201,P=0.448)or use of ACEI/ARB(HR=0.941,95%CI: 0.682-1.297,P=0.709)was not significantly associated with MACE incident in patients with PMI.Similar results were observed in Kaplan-Meier analysis.Robustly,subgroup analysis and landmark analysis suggested that the use of β-blockers or ACEI/ARB was not significantly associated with MACE incident in patients with PMI in any subgroup or in any time period.In addition,Cox regression analysis and Kaplan-Meier analysis showed that the use of β-blockers or ACEI/ARB were not significantly associated with secondary endpoints(including all-cause death,non-fatal myocardial infarction or stroke,revascularization)incident in patients with PMI.Similar results were observed in subgroup analysis and landmark analysis of revascularization incident.Conclusions: There is no effect of β-blockers or ACEI/ARB on the prognosis of patients with PMI. |
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