Risk score for the prediction of arteriovenous fistula maturation.

Background: The poor maturation rate of arteriovenous fistulas (AVF) remains a challenge. We aim to develop a parsimonious risk score equations that incorporate patients' demographics, comorbidities, and vessel characteristics to assist the access surgeons in predicting the likelihood of AVF maturation before surgery.

Methods: Data of AVFs created from 2015 to 2020 in National University Hospital Singapore was retrospectively obtained and used as the training dataset. Two prediction models were developed to predict: (1) the commencement of cannulation and (2) functional maturation, by three months after creation. The models were internally validated using k-fold cross validation, and externally validated on patients who had AVF created in 2021 and 2022. The final models were converted to interpretable risk score equations for clinical usage.

Results: The training dataset included 474 AVF cases. Six and eight variables were selected for predicting (1) the commencement of cannulation and (2) functional maturation, respectively. The two models demonstrated satisfactory performance with a C-statistic of 0.72 and 0.74, respectively. The C-statistics in internal validation were 0.7 and 0.69 for the two models, respectively. External validation was performed using the data of 220 different patients, the C-statistics was 0.7 in both models.

Conclusions: The two risk scores developed demonstrated reasonable pre-operation predicative value for AVF maturation. They are potentially useful in aiding clinicians to make decision about AVF creation sites. Further evaluation of these prediction scores in large cohort is require to reveal their clinical value.