Abstract
In a recent article in Pediatric Nephrology, Olivier Niel and colleagues applied an artificial intelligence algorithm to a clinical problem that continues to challenge experienced pediatric nephrologists: optimizing the target weight of children on dialysis. They compared blood pressure, antihypertensive medication and intradialytic symptoms in children whose target weight was prescribed firstly by a nephrologist, then subsequently using a machine learning algorithm. Improvements in all outcome measures are reported. Their innovative approach to tackling this important clinical problem appears promising. In this editorial, we discuss the strengths and weaknesses of their study and consider to what extent machine learning strategies are suited to optimizing pediatric dialysis outcomes.
Highlights
The capabilities of artificial intelligence (AI) and machine learning have advanced considerably in recent years
A pilot study suggested AI may be beneficial for clinical decision support in anemia management [2], and a further clinical trial is underway [3]
In order to understand if this study provides a generalizable solution to optimizing target weight, we will consider its limitations
Summary
The capabilities of artificial intelligence (AI) and machine learning have advanced considerably in recent years. Improvements in all outcome measures are reported including reduction in median post-dialysis blood pressure from 77th to 60th centile, reduction in antihypertensive medication in 4 of 14 cases and reduction in intradialytic symptoms in three patients Their innovative approach to tackling an important clinical problem which continues to challenge experienced pediatric nephrologists is commendable. Given the limitations of this first pilot study applying machine learning to optimize target weight, the results are not sufficiently robust to recommend use of this strategy in clinical practice at this point in time This is an important study which illustrates the potential of neural networks to improve pediatric dialysis outcomes and should trigger further work to progress this approach
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