Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, Ohio.
Minneapolis Heart Institute, Minneapolis, Minnesota.
JACC Cardiovasc Interv. 2017 Jun 12;10(11):1089-1098. doi: 10.1016/j.jcin.2017.03.016.
The aim of this study was to develop a hybrid approach-specific model to predict chronic total coronary artery occlusion (CTO) percutaneous coronary intervention success, useful for experienced but not ultra-high-volume operators.
CTO percutaneous coronary intervention success rates vary widely and have improved with the "hybrid approach," but current predictive models for success have major limitations.
Data were obtained from consecutively attempted patients from 7 clinical sites (9 operators, mean annual CTO volume 61 ± 17 cases). Angiographic analysis of 21 lesion variables was performed centrally. Statistical modeling was performed on a randomly designated training group and tested in a separate validation cohort. The primary outcome of interest was technical success.
A total of 436 patients (456 lesions) met entry criteria. Twenty-five percent of lesions had prior failed percutaneous coronary interventions at the site. The right coronary artery was the most common location (56.4%), and mean occlusion length was 24 ± 20 mm. The initial approach was most often antegrade wire escalation (70%), followed by retrograde (22%). Success was achieved in 79.4%. Failure was most closely correlated with presence of an ambiguous proximal cap, and in the presence of an ambiguous proximal cap, specifically defined collateral score (combination of Werner and tortuosity scores) and retrograde tortuosity. Without an ambiguous proximal cap, poor distal target, occlusion length >10 mm, ostial location, and 1 operator variable contributed. Prior failure, and Werner and tortuosity scores alone, were only weakly correlated with outcomes. The basic 7-item model predicted success, with C statistics of 0.753 in the training cohort and 0.738 in the validation cohort, the later superior (p < 0.05) to that of the J-CTO (Multicenter CTO Registry of Japan) (0.55) and PROGRESS CTO (Prospective Global Registry for the Study of Chronic Total Occlusion Intervention) (0.61) scores.
Success can be reasonably well predicted, but that prediction requires modification and combination of angiographic variables. Differences in operator skill sets may make it challenging to create a powerful, generalizable, predictive tool.
本研究旨在开发一种针对特定杂交技术的模型，以预测慢性完全闭塞（CTO）经皮冠状动脉介入治疗（PCI）的成功率，该模型适用于经验丰富但非超高手术量的术者。
CTO-PCI 的成功率差异很大，并且随着“杂交技术”的应用有所提高，但目前成功预测模型存在主要局限性。
数据来自 7 个临床中心连续尝试的患者（9 名术者，平均每年 CTO 手术量 61±17 例）。对 21 项病变变量进行中心分析。统计模型在随机指定的训练组中进行，并在单独的验证队列中进行测试。主要观察终点为技术成功率。
共纳入 436 名患者（456 处病变）。25%的病变在此部位曾有过失败的经皮冠状动脉介入治疗史。最常见的病变部位是右冠状动脉（56.4%），闭塞长度平均为 24±20mm。初始方法多为正向导丝升级（70%），随后是逆行（22%）。成功率为 79.4%。失败与近端模糊帽的存在密切相关，在存在近端模糊帽的情况下，特定定义的侧支评分（Werner 评分和迂曲评分的组合）和逆行迂曲评分也与失败密切相关。在没有近端模糊帽的情况下，较差的远端靶病变、闭塞长度>10mm、开口部位和 1 个术者变量也会导致失败。先前的失败，以及 Werner 评分和迂曲评分本身，仅与结果呈弱相关。基本的 7 项模型可预测手术成功，在训练队列中的 C 统计量为 0.753，在验证队列中的 C 统计量为 0.738，后者优于 J-CTO（日本多中心 CTO 注册中心）（0.55）和 PROGRESS CTO（慢性完全闭塞介入治疗前瞻性全球登记处）（0.61）评分（p<0.05）。
可以合理地预测手术成功率，但需要对血管造影变量进行修改和组合。术者技能的差异可能使得难以创建强大、通用的预测工具。
