Smartphone-based App to Assess Diabetic Peripheral Neuropathy
Authors' conclusion
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.
Study context
- Population
- Patients with pre-diabetes or diabetes
- Participants
- 71 patients
- Comparison
- Smartphone-based vibration perception threshold (SVPT) vs Rydel-Seiffer tuning fork (RSTF)
- Outcome
- Correlation of SVPT with RSTF scores
Performance
As reported in the abstract
SVPT moderately correlated with RSTF scores (Rs)
−0.43
p = 0.0019
Further findings
SVPT vs clinical markers (hemoglobin A1c (HbA1c), age, disease duration), multivariable linear regression, adults aged 50 to 69 years
- Model fit
- F(4, 29) = 4.76, p = 0.00447, Multiple R2 = 0.396, Adjusted R2 = 0.313, ϵ = 0.167
- Age × HbA1c interaction, positively associated with SVPT
- β = 0.118, p = 0.001
- Diabetes duration, negatively associated with SVPT
- β = −0.098, p = 0.003
Original publication
Smartphone-based App to Assess Diabetic Peripheral Neuropathy. J Diabetes Sci Technol. Published 1 April 2026. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →