Integrating vascular access surveillance with clinical monitoring for stenosis prediction.

Abstract

Arteriovenous fistula and arteriovenous graft are the most common types of vascular access for dialysis; stenosis and thrombosis are major complications leading to access failure andto an incresed risk ofmortality.The aim of the present study wasto assess the results of integrating strictvascular access blood flow surveillance with routine clinical monitoring for predicting vascular access stenosis in chronic hemodialysis patients. In this retrospective study, chronic dialysis patients with arteriovenous fistula or arteriovenous graft were included from a settingin which all patients underwent quarterly blood flow surveillance in 2017. The results of blood flow surveillance were confirmed by thorough physical examination. Predictive performance of blood flow surveillance models in detecting stenosis in patients with arteriovenous fistula or arteriovenous graft was evaluated.The predictive performance of the quarterlyblood flow surveillance model was described by confusion matrix. Differences in accuracy, positive predictive value (PPV), and negative predictive value (NPV) between blood flow surveillance models with distinct blood flow thresholds were evaluated. Of 397 included patients, 336 had anarteriovenous fistula and 61 had anarteriovenous graft. In 2017, 106 percutaneous transluminal angioplasty procedures were performed in patients with anarteriovenous fistula, and 63 in patients with anarteriovenous graft. The results revealed similar predictive performance of surveillance models using an absolute blood flow threshold of < 500 or < 400mL/min in predicting stenosis inpatients with arteriovenous fistula. Blood flow surveillance models for patients with anarteriovenous fistula had significantly higher accuracy than those for patients with anarteriovenous graft. Furthermore, the use ofarelative threshold, defined as blood flow < 1000mL/min and a 25% decline in blood flow, did not affect thepredictive performance of blood flow surveillance models. Blood flow surveillance models using thresholds of < 400 and < 600mL/min, followed by thorough physical examination, showed an accuracy of 91.54% and 72.15% in predicting stenosis inpatients with arteriovenous fistula and arteriovenous graft, respectively. These two blood flow surveillance models may be integrated with routine clinical monitoring to improve early detection and treatment of stenosis in hemodialysis patients.