Machine Learning-Driven Digital Phenotyping of Accelerometer-Based Physical Activity Patterns and Mortality in Patients on Hemodialysis: The PROMOTE Study

Background: Sedentary behavior is prevalent in hemodialysis (HD) patients. While physical activity (PA) guidelines recommend 150–300 min/week of moderate-intensity PA (MPA) or 75–150 min/week of vigorous-intensity PA (VPA), we have previously identified low-intensity PA (LPA) as a more optimal form of PA for HD patients. However, such recommendations based on a single PA metric overlook the complexity of real-world PA patterns. Digital phenotyping of PA patterns unique to HD patients may offer more actionable recommendations. Methods: The PROMOTE study enrolled 1,030 HD patients who were prospectively followed for three years. PA was measured using triaxial accelerometers at baseline and one year later. The cohort was randomly split into derivation and validation groups in a 6:4 ratio. High-dimensional PA data were reduced to two dimensions using Uniform Manifold Approximation and Projection (UMAP), followed by k-means clustering. Cox models were used to examine associations between PA patterns and all-cause death. Results: Three clusters were identified from UMAP-assisted k-means clustering. A significant difference in the ratio of moderate-to-vigorous PA (MVPA) to total PA was found across clusters, with median [interquartile range] MVPA ratios of 3 [1–5] %, 4 [2–6] %, and 15 [10–15] %. The first two clusters were classified as the “LPA-dominant type”, and the third as the “MVPA-mixed type”. Clustering was replicated in the validation group. These phenotypes were consistent on both dialysis and non-dialysis days, and persisted after one year. The MVPA-mixed type exhibited better survival than the LPA-dominant type (HR 0.70, 95% CI, 0.49-0.99). The hazard of death declined steeply with increasing MVPA ratio, with the lowest hazard observed at 13-16%. Conclusion: The MVPA-mixed pattern, identified as a digital phenotype of HD patients, was associated with better survival than the LPA-dominant pattern.

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Journal
Journal of the American Society of Nephrology
Published
2025-10-01
DOI
https://doi.org/10.1681/asn.2025hy9dhgq8
Primary Topic
Dialysis and Renal Disease Management
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article
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article

Machine Learning-Driven Digital Phenotyping of Accelerometer-Based Physical Activity Patterns and Mortality in Patients on Hemodialysis: The PROMOTE Study

Ayaka Sugimachi, Isao Matsui, Yusuke Sakaguchi, Yoshitaka Isaka et al.
Journal of the American Society of Nephrology
Dialysis and Renal Disease Management
article

Machine Learning-Driven Digital Phenotyping of Accelerometer-Based Physical Activity Patterns and Mortality in Patients on Hemodialysis: The PROMOTE Study

Ayaka Sugimachi, Isao Matsui, Yusuke Sakaguchi, Yoshitaka Isaka, Jun‐Ya Kaimori, Shungo Fukuda, Yohei Doi, Hikaru Kadono, Ryuta Uwatoko, Tatsufumi Oka, Masayuki Mizui, Yuki Kawano
article en

Abstract

Background: Sedentary behavior is prevalent in hemodialysis (HD) patients. While physical activity (PA) guidelines recommend 150–300 min/week of moderate-intensity PA (MPA) or 75–150 min/week of vigorous-intensity PA (VPA), we have previously identified low-intensity PA (LPA) as a more optimal form of PA for HD patients. However, such recommendations based on a single PA metric overlook the complexity of real-world PA patterns. Digital phenotyping of PA patterns unique to HD patients may offer more actionable recommendations. Methods: The PROMOTE study enrolled 1,030 HD patients who were prospectively followed for three years. PA was measured using triaxial accelerometers at baseline and one year later. The cohort was randomly split into derivation and validation groups in a 6:4 ratio. High-dimensional PA data were reduced to two dimensions using Uniform Manifold Approximation and Projection (UMAP), followed by k-means clustering. Cox models were used to examine associations between PA patterns and all-cause death. Results: Three clusters were identified from UMAP-assisted k-means clustering. A significant difference in the ratio of moderate-to-vigorous PA (MVPA) to total PA was found across clusters, with median [interquartile range] MVPA ratios of 3 [1–5] %, 4 [2–6] %, and 15 [10–15] %. The first two clusters were classified as the “LPA-dominant type”, and the third as the “MVPA-mixed type”. Clustering was replicated in the validation group. These phenotypes were consistent on both dialysis and non-dialysis days, and persisted after one year. The MVPA-mixed type exhibited better survival than the LPA-dominant type (HR 0.70, 95% CI, 0.49-0.99). The hazard of death declined steeply with increasing MVPA ratio, with the lowest hazard observed at 13-16%. Conclusion: The MVPA-mixed pattern, identified as a digital phenotype of HD patients, was associated with better survival than the LPA-dominant pattern.

Journal of the American Society of NephrologyVol. 36(10S)
Osaka Prefecture University (JP)
Openalex Percentile: Top 53%
Dialysis and Renal Disease Management
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