# Effects of a Hypertension Management Mobile App on Urinary Sodium Excretion in Patients With Chronic Kidney Disease: Randomized Controlled Trial

**Authors:** Takayuki Kawaoka, Yusuke Sakaguchi, Tatsufumi Oka, Yohei Doi, Ryohei Yamamoto, Isao Matsui, Masayuki Mizui, Jun-Ya Kaimori, Yoshitaka Isaka

PMC · DOI: 10.2196/68447 · JMIR mHealth and uHealth · 2026-03-16

## TL;DR

A hypertension management app was tested to reduce salt intake in CKD patients, but it did not significantly lower urinary sodium excretion despite improved self-reported behavior.

## Contribution

This is one of the first randomized trials to evaluate a smartphone app's effect on salt reduction in CKD patients.

## Key findings

- The app did not significantly reduce estimated 24-hour urinary sodium excretion compared to counseling alone.
- Self-reported salt intake behaviors improved in the app group, but this did not translate to measurable changes in urinary sodium.
- Secondary outcomes like blood pressure and proteinuria also showed no significant differences between groups.

## Abstract

Excessive salt intake is detrimental to the kidneys. Nevertheless, salt restriction is often suboptimal in patients with chronic kidney disease (CKD). Smartphone app–based interventions might help reduce salt intake by supporting self-monitoring and behavior change at scale. However, clinical trials evaluating these interventions for salt reduction are limited, particularly in CKD populations.

This study investigated whether a hypertension management app could reduce urinary sodium excretion in patients with CKD.

This open-label, single-center, randomized clinical trial included 101 patients with CKD who had a history of hypertension and estimated 24-hour urinary sodium excretion of 100 mmol or greater. Patients in the intervention group used CureApp HT, a smartphone app designed to manage hypertension through lifestyle modifications and self-monitoring, particularly for salt restriction. The app delivered daily, individualized guidance tailored to each patient’s lifestyle. Patients also received lifestyle counseling by nephrologists during outpatient visits. The control group received lifestyle counseling alone. The intervention period was 12 weeks. The primary outcome was the change in estimated 24-hour urinary sodium excretion from baseline to week 12, calculated from spot urine samples using the Tanaka method. Key secondary outcomes included office blood pressure, brachial-ankle pulse wave velocity, urinary protein-to-creatinine ratio, and plasma brain natriuretic peptide. The analysis was conducted in the intention-to-treat population, using a mixed-effects model for repeated measures.

A total of 101 patients were randomly assigned to the intervention group (n=51) or the control group (n=50). The median (IQR) app engagement rate, calculated by dividing the number of days patients recorded blood pressure in the app by the total intervention period, was 96% (73%-99%). The mean (SD) baseline estimated glomerular filtration rate and 24-hour urinary sodium excretion were 38 (18) mL/min/1.73 m2 and 145 (33) mmol, respectively. A higher proportion of patients in the intervention group reported that their salt intake behaviors had “significantly improved” or “somewhat improved” by the intervention than those in the control group (35/46, 76% vs 18/47, 38%; P<.001). However, the mean change in estimated 24-hour urinary sodium excretion during the intervention period did not differ significantly between groups (1.4, 95% CI −12.0 to 14.7 mmol in the intervention group vs 2.5, 95% CI −10.7 to 15.6 mmol in the control group; between-group difference −1.1, 95% CI −19.8 to 17.7 mmol; P=.92). Secondary outcomes were not significantly different between groups. These outcomes were not altered even in a subgroup of patients reporting improved self-reported salt intake behaviors.

The smartphone app did not reduce salt intake in patients with CKD, despite a substantial improvement in self-reported salt intake behaviors. Enhancing the intervention intensity may be necessary to effectively bridge the intention-behavior gap.

## Linked entities

- **Diseases:** chronic kidney disease (MONDO:0005300)

## Full-text entities

- **Genes:** YBX1 (Y-box binding protein 1) [NCBI Gene 4904] {aka BP-8, CBF-A, CSDA2, CSDB, DBPB, EFI-A}, NR3C2 (nuclear receptor subfamily 3 group C member 2) [NCBI Gene 4306] {aka MCR, MLR, MR, NR3C2VIT}, REN (renin) [NCBI Gene 5972] {aka ADTKD4, HNFJ2, RTD}, NPPB (natriuretic peptide B) [NCBI Gene 4879] {aka BNP, Iso-ANP}, CRP (C-reactive protein) [NCBI Gene 1401] {aka PTX1}, RAC1 (Rac family small GTPase 1) [NCBI Gene 5879] {aka MIG5, MRD48, Rac-1, TC-25, p21-Rac1}
- **Diseases:** HT (MESH:D006973), albuminuria (MESH:D000419), CKD (MESH:D051436), inflammation (MESH:D007249), proteinuria (MESH:D011507), noncommunicable diseases (MESH:D000073296), salt restriction (MESH:D002313), fibrosis (MESH:D005355), weight loss (MESH:D015431), cardiovascular diseases (MESH:D002318), cognitive impairment (MESH:D003072), impaired finger dexterity (MESH:C000721267), MMRM (MESH:D004195), salt toxicity (MESH:D013651), Kidney Disease (MESH:D007674)
- **Chemicals:** YS (MESH:D015019), Na (MESH:D012964), creatinine (MESH:D003404), Salt (MESH:D012492), alcohol (MESH:D000438), potassium (MESH:D011188), CureApp (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

47 references — full list in the complete paper: https://tomesphere.com/paper/PMC12991191/full.md

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Source: https://tomesphere.com/paper/PMC12991191