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Successful guidewire crossing via collateral channel at retrograde percutaneous coronary intervention for chronic total occlusion: the J-Channel score.

逆行经皮冠状动脉介入治疗慢性完全闭塞时成功的导丝通过侧支通道: J 通道评分。

  • 影响因子:2.41
  • DOI:10.4244/EIJ-D-18-00993
  • 作者列表:"Nagamatsu W","Tsuchikane E","Oikawa Y","Sumitsuji S","Igarashi Y","Yoshikawa R","Muto M","Okada H","Katoh O
  • 发表时间:2020-04-03
Abstract

AIMS:Guidewire (GW) tracking in a collateral channel (CC) is an important step during retrograde chronic total occlusion (CTO) percutaneous coronary intervention (PCI). The aim of this study was to create a prediction score model for CC GW crossing success. METHODS AND RESULTS:We analysed data on 886 CCs included in the Japanese CTO PCI Expert Registry during 2016. CCs were categorised as septal (n=610) and non-septal (n=276). CCs were randomly assigned to derivation and validation sets in a 2:1 ratio. The score was developed by multivariate analysis with angiographic findings. Small vessel, reverse bend, and continuous bends were independent predictors in the septal CC subset. Small vessel, reverse bend, and corkscrew were independent predictors in the non-septal CC subset. The extent of intervention was easy, intermediate, and difficult in 92.9%, 57.4%, and 16.7% in the septal CC subset and 91.7%, 54.3%, and 19.0% in the non-septal CC subset, respectively, in the validation set. The area under the receiver operating characteristic curve was >0.7 in the derivation and validation sets of both CC subsets. CONCLUSIONS:The prediction score model can suggest grading of the difficulty of CC GW crossing based on angiographic findings for each type of CC.

摘要

目的: 侧支通道 (CC) 的导丝 (GW) 追踪是逆行慢性完全闭塞 (CTO) 经皮冠状动脉介入治疗 (PCI) 的重要步骤。本研究的目的是创建 CC GW 穿越成功的预测评分模型。 方法和结果: 我们分析了 2016年日本 CTO PCI 专家登记处纳入的 886 个 CCs 的数据。CCs 分为间隔 (n = 610) 和非间隔 (n = 276)。CCs 以 2:1 的比例随机分配到推导和验证集。通过血管造影结果的多变量分析制定评分。小血管、反向弯曲和连续弯曲是间隔 CC 子集的独立预测因素。小血管、反向弯曲和螺旋体是非间隔 CC 子集的独立预测因素。干预范围在间隔 CC 子集的 92.9% 、 57.4% 和 16.7% 以及在非间隔 CC 子集的 91.7% 、 54.3% 和 19.0% 中分别为容易、中间和困难。在验证集中。在两个 CC 子集的推导和验证集中,受试者工作特征曲线下面积> 0.7。 结论: 预测评分模型可以根据每种类型 CC 的血管造影结果提示 CC GW 交叉的难度分级。

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DOI:10.1172/JCI124708
作者列表:["Jain M","Dhanesha N","Doddapattar P","Chorawala MR","Nayak MK","Cornelissen A","Guo L","Finn AV","Lentz SR","Chauhan AK"]

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影响因子:4.65
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DOI:10.1161/ATVBAHA.119.313602
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