Digital Monitoring of Patients with Generalized Myasthenia Gravis: A Prospective Pilot Study

Monitoring patients with myasthenia gravis (MG) can be challenging due to the fluctuating nature of the disease. We aimed to test the reliability of using the MG Activities of Daily Living (MG-ADL) scale in the form of a smartphone application as a means for optimal patient monitoring and early exacerbation detection.

We conducted an observational, prospective, single-center study including patients with generalized MG at risk of clinical worsening. Follow-up was based on routine outpatient visits, remote monitoring via weekly self-completion of the MG-ADL scale, and home visits by specialist nurses.

Thirty-one patients were included [41.9% female; mean (SD) age 59 (15) years], 87.1% seropositive for anti-AChR antibodies. MG-ADL scores reported by the patient via the application showed excellent agreement with healthcare provider scores (ICC = 0.92, P < 0.01), moderate correlation with the MG Composite scale (ρ = 0.595, P < 0.01), and weak correlation with the Quantitative MG scale (ρ = 0.328, P < 0.01). Over the 15-month follow-up period, compared to 23 exacerbations detected during routine outpatient visits, the application detected 38 exacerbations in 14 patients, 20 of which led to therapeutic modifications.

This study demonstrates the reliability of MG-ADL scale data obtained via a smartphone application in reflecting clinical status and in detecting deterioration episodes sometimes missed during routine outpatient visits.