Prediction Tool to Estimate Potassium Diet in Chronic Kidney Disease Patients Developed Using a Machine Learning Tool: The UniverSel Study

Abstract

There is a need for a reliable and validated method to estimate dietary potassium intake in chronic kidney disease (CKD) patients to improve prevention of cardiovascular complications. This study aimed to develop a clinical tool to estimate potassium intake using 24-h urinary potassium excretion as a surrogate of dietary potassium intake in this high-risk population. Data of 375 adult CKD-patients routinely collecting their 24-h urine were included to develop a prediction tool to estimate potassium diet. The prediction tool was built from a random sample of 80% of patients and validated on the remaining 20%. The accuracy of the prediction tool to classify potassium diet in the three classes of potassium excretion was 74%. Surprisingly, the variables related to potassium consumption were more related to clinical characteristics and renal pathology than to the potassium content of the ingested food. Artificial intelligence allowed to develop an easy-to-use tool for estimating patients’ diets in clinical practice. After external validation, this tool could be extended to all CKD-patients for a better clinical and therapeutic management for the prevention of cardiovascular complications.

A Hybrid Risk Factor Evaluation Scheme for Metabolic Syndrome and Stage 3 Chronic Kidney Disease Based on Multiple Machine Learning Techniques

“…Existing studies that utilize ML methods to perform CKD data analysis mostly analyze the patients directly [ 16 , 17 , 20 , 31 , 32 , 33 , 34 ], and few studies have discussed the predictive models and important risk factors for CKD patients with MetS. Several studies have constructed predictive models for MetS patients, as well as their risk factors.…”

Potassium Intake and Human Health

“…Notably, guidelines on CKD management [ 19 ] highlight the role of dietary potassium intake in CKD, recommending the assessment of dietary potassium intake in CKD patients, particularly those with potential hyperkalaemia [ 20 ]. In this context, two other studies included in this Special Issue explored different aspects of the assessment of dietary potassium intake in patients with CKD [ 21 , 22 ]. Moreover, since the mechanisms of potassium homeostasis and excretion are impaired in these individuals, 24 h urine collection (the recognised gold standard for monitoring potassium intake [ 23 ]) may not be reliable to evaluate potassium intake in this setting.…”

“…Another study included in this Special Issue also explored the assessment of dietary potassium intake in CKD patients using Bayesian networks derived from AI [ 22 ]. A total of 375 adults with CKD were included in an analysis aimed to develop a clinical tool to estimate potassium intake using 24 h urinary potassium excretion.…”