Salt Reduction Using a Smartphone Application Based on an Artificial Intelligence System for Dietary Assessment in Patients with Chronic Kidney Disease: A Single-Center Retrospective Cohort Study

Abstract

This study evaluated the clinical usefulness of an artificial intelligence-powered smartphone application in reducing the daily salt intake of patients with chronic kidney disease (CKD). This study included 35 patients with CKD who were classified into app users (i.e., 13 outpatients who used the app for 3 months and whose salt intake was evaluated before and after using the app) and app nonusers (i.e., 22 outpatients not using the application; their salt intake was similarly evaluated). The primary outcome was estimated as salt intake after 3 months of using the application and at a 6-month follow-up. Linear mixed model analysis revealed that app users had a significant decrease in estimated salt intake after 3 months (−2.12 g/day; 95% CI, −4.05 to −0.19; p = 0.03) compared with app nonusers but not after 6 months (−0.96 g/day; 95% CI, −3.13 to 1.20; p = 0.38). App users showed a significant decrease in body mass index at 3 months (−0.42 kg/m2 [95% CI, −0.78 to −0.049; p = 0.03]) and 6 months (−0.65 kg/m2 [95% CI, −1.06 to −0.24; p = 0.002]). The application promoted short-term reduction in salt intake. These results provide a strong rationale for future trials.

Keywords

• salt reduction
• chronic kidney disease
• artificial intelligence
• smartphone application
• urinary protein