Risk Prediction Model and Scoring System Analysis in Patients With Side Branch Occlusion During Coronary Bifurcation Intervention
10.3969/j.issn.1000-3614.2015.09.02
- VernacularTitle:冠状动脉分叉病变介入治疗中分支闭塞风险模型及评分系统的研究
- Author:
Yuan HE
;
Dong ZHANG
;
Dong YIN
;
Bo XU
;
Kefei DOU
- Publication Type:Journal Article
- Keywords:
Coronary bifurcation lesion;
Intervention strategy;
Side branch occlusion;
Risk prediction;
Scoring system
- From:
Chinese Circulation Journal
2015;(9):827-832
- CountryChina
- Language:Chinese
-
Abstract:
Objective: To establish a risk prediction model and scoring system in patients with side branch (SB) occlusion during coronary bifurcation intervention. Methods: A total of 7007 consecutive patients who received percutanenous coronary intervention (PCI) in our hospital from 2012-02 to 2012-07 were recruited and 1545 patients (with 1601 bifurcation lesions) treated by single stent technique or main vessel stenting ifrst strategy were selected for our study. According to weather SB occlusion occurred during operation, the lesions were divided into 2 groups: Non-SB occlusion group,n=1431 and SB occlusion group,n=114. The data set of the ifrst 1200/1601 lesions by time sequence, was used for establishing the risk model and scoring system, the data set of rest 401 lesions was used for model validation. Results: The modeling data set presented that the relationship between pre-operative main vessel plaque and the position of branch vessel, the main blood vessel pre-stenting TIMI grade, the stenosis degree of pre-operative bifurcation nucleus, the angle of pre-operative bifurcation and the ratio of pre-senting stenosis degree of branch diameter and pre-operative main vessel to branch vessel diameter were the independent risk factors for branch occlusion. The risk model ROC=0.80, 95% CI 0.75-0.85, Hosmer-Lemeshow HLP=1.00; the scoring system ROC=0.76, 95% CI 0.71-0.82, HLP=0.12. The validation data set ROC=0.81, 95% CI 0.73-0.89, HLP=0.77; the scoring system ROC=0.77, 95% CI 0.69-0.86, HLP=0.58. The quartile integration of both data sets indicated that the patients with the integration score ≥ 10 had the higher risk for SB occlusion than those with integration score < 10 during the operation,P<0.001. Conclusion: Our research developed a simple and user-friendly system, it may distinguish the patients with high risk of SB occlusion during bifurcation intervention by quantitative stratiifcation of coronary angiographic imaging.
