[Value of index of microcirculatory resistance for early prediction of periprocedural myocardial microcirculatory injury after percutaneous coronary intervention in patients with coronary heart disease].

Objective: To explore the value of index of microcirculatory resistance (IMR) for early prediction of periprocedural myocardial injury (PMI) in patients with stable angina pectoris (SAP) and acute coronary syndrome (ACS) after PCI. Methods: It was a prospective study. One hundred and sixty-four patients who had single coronary lesion were consecutively enrolled from May 2014 to December 2017 at Nanjing Hospital affiliated to Nanjing Medical University. According to clinical manifestation, patients were divided into SAP group ( n= 81) and ACS group ( n= 83). IMR was determined by thermal dilution with pressure guide wire. Basic clinical characteristics, coronary angiographic results, PCI procedural details, IMR after PCI, ΔIMR (IMR=post-PCI-IMR pre-PCI), levels of myocardial biomarkers before and after PCI were compared between the two groups. Multivariate logistic regression was used to analyze the relation of PMI with IMR and ΔIMR, and the predictive ability was evaluated by receiver operating characteristic (ROC). Results: The levels of total cholesterol and low density lipoprotein cholesterol were significantly higher in ACS group than in SAP group ( P< 0.05), other clinical data at baseline were similar between the two groups ( P> 0.05). Quantitative coronary angiography (QCA) results and PCI related data were also similar between the two groups before PCI ( P> 0.05). Values of mean transit time (Tmn) of intracoronary injection with room temperature saline, post-PCI IMR and ΔIMR were significantly higher in ACS group than in SAP group after PCI ( P< 0.05). Plasma creatine kinase isoenzyme-MB difference (ΔCK-MB) (ΔCK-MB=CK-MB post-PCI-CK-MB pre-PCI) and cardiac troponin-I (cTnI) difference (ΔcTnI=cTnI post-PCI-cTnI pre-PCI) were significantly larger in ACS group than in SAP group ( P< 0.05). Multivariate logistic regression analysis showed that coronary artery disease (CHD) type (SAP and ACS) ( OR= 1.301, 95 %CI 1.083-1.562), age ( OR= 1.007, 95 %CI 1.000-1.013), ΔIMR ( OR= 1.009, 95 %CI 1.000-1.017) and post-PCI IMR ( OR= 1.008, 95 %CI 1.001-1.014) were independent predictors of PMI ( P< 0.05). The area under the ROC curve (AUC) of ΔIMR was 0.763 to predict PMI ( P< 0.05), the optimum cut-off value of ΔIMR was 5.485 with 70.0% sensitivity and 77.4% specificity. ΔIMR was positively correlated with ΔcTnI ( r= 0.592, P< 0.05). Conclusions: ΔIMR serves as an early predictor of PMI in CHD patients after PCI. As compared with SAP patients, ACS patients are more likely to develop PMI.