Balamuthusamy Saravanan, Reddi Alagarsamy Lakku, Madhrira Machaiah H, Sankarapandian Balamurugan, Nguyen Peter, Vallurupalli Avinash, Gabbard William, Jalandhara Nishant, Yurvati Albert
Tarrant Vascular Access Center, Vascular and Interventional Nephrology, Fort Worth, Texas - USA.
Texas Research Institute, PPG Healthcare PA, Fort Worth, Texas - USA.
J Vasc Access. 2017 Jul 14;18(4):319-324. doi: 10.5301/jva.5000734. Epub 2017 Jun 23.
Cephalic arch stenosis is one of the most common reasons for repeated endovascular intervention and eventual abandonment of access in hemodialysis patients. There is no prediction model to identify risk factors for recurrent cephalic arch stenosis. We have developed a mathematical model to predict the need for reintervention in brachiocephalic (BC) fistulas with recurrent cephalic arch stenosis.
Single-center retrospective analysis of 143 patients with a BC fistula referred to the vascular clinic for access dysfunction who underwent cephalic arch angioplasty were included for the analysis. Twelve-month post-index angioplasty data were analyzed using parametric, non-parametric and multiple regression models using SPSS software.
The mean need for re-intervention in 1 year since first index visit was 2.46 ± 1.404. Statistically significant correlation (p≤0.001) for re-intervention was observed with the severity of stenosis at index visit, access flow, vessel wall diameter proximal to the stenosis, average venous pressure >50% of the delivered blood flow rate and prolonged bleeding for >30 minutes as a reason for referral. Three equations have been derived for calculating the need for re-intervention based on the diameter of the vessel wall proximal to the stenosis.
Risk stratification of BC fistulas utilizing the above parameters could enable clinicians to identify accesses that are at risk for multiple re-interventions. Early identification of accesses that are at high risk for re-interventions at the cephalic arch might prolong access survival and reduce the cost for intervention by utilizing alternate strategies.
头臂弓狭窄是血液透析患者反复进行血管内介入治疗并最终放弃通路的最常见原因之一。目前尚无预测模型可用于识别复发性头臂弓狭窄的危险因素。我们开发了一种数学模型，用于预测头臂弓复发性狭窄的肱动脉-头静脉内瘘再次干预的必要性。
对143名头臂动静脉内瘘患者进行单中心回顾性分析，这些患者因通路功能障碍转诊至血管门诊并接受了头臂弓血管成形术，纳入分析。使用SPSS软件，采用参数模型、非参数模型和多元回归模型对头臂弓血管成形术后12个月的数据进行分析。
自首次就诊后的1年内再次干预的平均需求为2.46±1.404次。再次干预与首次就诊时的狭窄严重程度、通路血流量、狭窄近端血管壁直径、平均静脉压>50%的供血血流量以及作为转诊原因的出血时间延长>30分钟之间存在统计学显著相关性（p≤0.001）。根据狭窄近端血管壁直径，已推导得出三个用于计算再次干预必要性的公式。
利用上述参数对头臂动静脉内瘘进行风险分层，可使临床医生识别出有多次再次干预风险的通路。通过采用替代策略，早期识别出头臂弓处有高再次干预风险的通路，可能会延长通路使用寿命并降低干预成本。
