Description

Scientific research focuses on limited parameters, aims to confirm hypotheses, and has minor uncertainties. In contrast, medical decisions involve many unknowns. Physicians must use all available knowledge to make the best decisions. However, decision-making can become unpredictable when limited evidence exists, leading to non-reproducible outcomes.

According to clinical guidelines, patients who need pre-kidney replacement therapy (pre-KRT) and opt for hemodialysis (HD) with a reasonable life expectancy should have arteriovenous (AV) access created. Nevertheless, constructing an AVF has limitations. [Additionally, the maturation rate of AVF is suboptimal. Therefore, after careful consideration of the patient's end-stage kidney disease (ESKD) life plan, the suggested order of AV access types and locations starts a native distal forearm radiocephalic AVF, followed by a native proximal forearm AVF, a forearm arteriovenous graft (AVG), then an upper arm AVG creation.[Lok et al., 2020] However, the decision-making process for selecting hemodialysis access is shared between patients, physicians, and the surgeon's discretion.

Therefore, clinical kidney practice requires effective decision-making to address ESKD life plan and AV access concerns while minimizing harm. Decision analysis models can bridge the gap between research and decision-making. Our study aim was to utilize a decision tree analysis (DTA) model to gain insight into the decision-making process within a multiple-center cohort.