The influencing factors of poor coronary collateral circulation formation in patients with acute coronary syndrome and its effect on prognosis

Zhang Yijun; Yu Xin; Huang Tao

doi:10.3760/j.issn.1673-4777.2025.11.006

Abstract：Objective To analyze the influencing factors of poor coronary collateral circulation(CCC)formation in patients with acute coronary syndrome(ACS)and its effect on prognosis.Methods A total of 260 ACS patients admitted to 3201 Hospital from January 2021 to December 2023 were selected and divided into poor formation group and good formation group according to CCC formation.The clinical data of ACS patients were collected,and the incidence of major adverse cardiovascular events(MACE)was calculated after 1 year of follow-up.Univariate analysis was used to analyze the factors of poor CCC in ACS patients,LASSO regression was used to screen the related variables affecting poor CCC in ACS patients,and multivariate Logistic regression analysis was used to determine the independent influencing factors.Based on this,a nomogram prediction model for poor CCC in ACS patients was constructed.By testing the fit of the H-L model,the receiver operating characteristic(ROC)curve was plotted to evaluate the predictive ability of the model,the C-index was used to evaluate the ability to discriminate,the calibration curve was used to evaluate consistency,and the decision curve was used to evaluate the clinical decision value.Results The rate of poor CCC formation in 260 ACS patients was 63.5％(165/260).Multivariate Logistic regression analysis showed that diabetes,high atherogenic index of plasma(AIP)and high neutrophil-to-lymphocyte ratio(NLR)were independent risk factors for poor CCC formation in ACS patients,while right coronary artery,multi-vessel disease and high Gensini score were independent protective factors(all P＜0.05).Based on the above influencing factors,a nomogram model was established as follows:Logit(P)=0.876+1.292 × diabetes-1.176 × culprit vessel-1.785 × number of diseased vessels-0.028 × Gensini Score+0.423 × AIP+0.424 × NLR,with a non-significant H-L test(P＞0.05).The ROC curve analysis results showed that the area under the curve of the nomogram model predicting poor CCC formation in ACS patients was 0.887(95％confidence interval:0.842-0.923),with sensitivity and specificity of 81.8％and 83.2％,respectively.After 1 000 bootstrap self sampling resampling for internal validation,the C-index was 0.888(95％confidence interval:0.883-0.893).The calibration curve showed that the predicted probability was well fitted to the ideal curve,and the decision curve showed that when the threshold probability was greater than 0.15,the net clinical benefit was greater than 0.After 1 year of follow-up,the incidence of MACE in the poor formation group was higher than that in the good formation group[33.9％(56/165)vs 21.1％(20/95)](P＜0.05).Conclusion Diabetes,culprit vessel,number of diseased vessels,Gensini score,AIP and NLR are independent influencing factors for poor CCC in ACS patients.The nomogram model based on this has good predictive value,and poor CCC can increase the incidence of MACE.