PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 3, 2026Journal of Diabetes Science and Technology0 citations

Smartphone-based App to Assess Diabetic Peripheral Neuropathy

View Full Paper
RARachel A. G. AdenekanAAAdeyinka E. AdenekanKLKenneth K Leung

Key Points

  • To assess the clinical relevance and accuracy of smartphone-based vibration perception thresholds for monitoring diabetic peripheral neuropathy.
  • Measured vibration perception thresholds in 71 patients with pre-diabetes or diabetes.
  • Compared efficacy with tuning fork exams.
  • Analyzed correlations between SVPT and Rydel-Seiffer tuning fork scores.
  • Investigated the relationship of SVPT with clinical markers like HbA1c, age, and disease duration using multivariable linear regression.
  • Moderate correlation observed between SVPT and RSTF scores (R s = −0.43, p = 0.0019).
  • SVPTs showed significant correlation with clinical markers, especially in adults aged 50 to 69 years.
  • Positive association found between age and HbA1c with SVPTs (β = 0.118, p = 0.001).
  • Negative association observed between diabetes duration and SVPTs (β = −0.098, p = 0.003).

Abstract

Background: Diabetic peripheral neuropathy (DPN) affects approximately 50% of individuals with diabetes and is a risk factor for amputations. Unfortunately, foot exams and screening tools are inconsistent and miss early-stage nerve damage. A smartphone-based application that delivers controlled vibrations, records patient responses, and computes a vibration perception threshold (SVPT) may present an accessible, precise monitoring avenue. This study assesses the clinical relevance and precision of SVPTs for measuring large-fiber sensory deficits in patients with diabetes. Methods: We measured SVPTs in 71 patients with pre-diabetes or diabetes and compared their efficacy with tuning fork exams. We analyzed the correlation between SVPT and Rydel-Seiffer tuning fork (RSTF) scores, along with their relationship with clinical DPN markers such as hemoglobin A1c (HbA1c), age, and disease duration using multivariable linear regression. Results: The SVPTs moderately correlated with RSTF scores ( R s = −0.43, p = 0.0019). Among adults aged 50 to 69 years, SVPTs correlated significantly with clinical markers F (4, 29) = 4.76, p = 0.00447, Multiple R 2 = 0.396, Adjusted R 2 = 0.313, ϵ = 0.167. The interaction between age and HbA1c was positively associated with SVPTs (β = 0.118, p = 0.001), while SVPTs were negatively associated with diabetes duration (β = −0.098, p = 0.003). Conclusions: We present a clinically relevant, patient-operated smartphone application for large-fiber sensory monitoring, tested on patients with varying DPN risk. This novel platform has the potential to provide a precise, reliable, and accessible avenue for identifying individuals at risk of developing DPN complications, prior to overt clinical manifestation.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Adenekan et al. (2026) studied this question.

synapsesocial.com/papers/69cf5dd55a333a821460bd0dhttps://doi.org/10.1177/19322968261426385
Ask AI
Helpful
Bookmark
Share
View Full Paper