Assessment of Smartphone-Based Spiral Tracing in Multiple Sclerosis Reveals Intra-Individual Reproducibility as a Major Determinant of the Clinical Utility of the Digital Test.

Journal: Frontiers in medical technology
Published Date:

Abstract

Technological advances, lack of medical professionals, high cost of face-to-face encounters, and disasters such as the COVID-19 pandemic fuel the telemedicine revolution. Numerous smartphone apps have been developed to measure neurological functions. However, their psychometric properties are seldom determined. It is unclear which designs underlie the eventual clinical utility of the smartphone tests. We have developed the smartphone Neurological Function Tests Suite (NeuFun-TS) and are systematically evaluating their psychometric properties against the gold standard of complete neurological examination digitalized into the NeurEx app. This article examines the fifth and the most complex NeuFun-TS test, the "Spiral tracing." We generated 40 features in the training cohort (22 healthy donors [HD] and 89 patients with multiple sclerosis [MS]) and compared their intraclass correlation coefficient, fold change between HD and MS, and correlations with relevant clinical and imaging outcomes. We assembled the best features into machine-learning models and examined their performance in the independent validation cohort (45 patients with MS). We show that by involving multiple neurological functions, complex tests such as spiral tracing are susceptible to intra-individual variations, decreasing their reproducibility and clinical utility. Simple tests, reproducibly measuring single function(s) that can be aggregated to increase sensitivity, are preferable in app design.

Authors

  • Komi S Messan
    National Institutes of Health, National Institute of Allergy and Infectious Diseases, Office of Data Science and Emerging Technologies, Rockville, MD, United States.
  • Linh Pham
    National Institutes of Health, National Institute of Allergy and Infectious Diseases, Laboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, Bethesda, MD, United States.
  • Thomas Harris
    National Institutes of Health, National Institute of Allergy and Infectious Diseases, Laboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, Bethesda, MD, United States.
  • Yujin Kim
    National Institutes of Health, National Institute of Allergy and Infectious Diseases, Laboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, Bethesda, MD, United States.
  • Vanessa Morgan
    National Institutes of Health, National Institute of Allergy and Infectious Diseases, Laboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, Bethesda, MD, United States.
  • Peter Kosa
    National Institutes of Health, National Institute of Allergy and Infectious Diseases, Laboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, Bethesda, MD, United States.
  • Bibiana Bielekova
    National Institutes of Health, National Institute of Allergy and Infectious Diseases, Laboratory of Clinical Immunology and Microbiology, Neuroimmunological Diseases Section, Bethesda, MD, United States.

Keywords

No keywords available for this article.