TY - JOUR
T1 - Biosensor vital sign detects multiple sclerosis progression
AU - Krysko, Kristen M.
AU - Akhbardeh, Alireza
AU - Arjona, Jennifer
AU - Nourbakhsh, Bardia
AU - Waubant, Emmanuelle
AU - Antoine Gourraud, Pierre
AU - Graves, Jennifer S.
N1 - Funding Information:
To the dedicated patients who participated in this study. We thank Dr. Douglas Goodin, Thomas Capenito, and Adam Santaniello for their assistance with the patient‐reported EDSS questionnaire and digital adaptation. Study funding included the UCSF CTSI pilot grants program and an Investigator initiated grant from Genentech. Dr. Kristen Krysko is funded by a Sylvia Lawry Physician Fellowship through the National Multiple Sclerosis Society (FP‐1605‐08753 (Krysko)).
Funding Information:
Dr. Kristen Krysko is funded by a Sylvia Lawry Physician Fellowship through the National Multiple Sclerosis Society (FP‐1605‐08753 (Krysko)). She also has fellowship funding through Biogen. Dr. Alireza Akhbardeh has no disclosures. Ms. Jennifer Arjona has no disclosures. Dr. Bardia Nourbakhsh reports personal fees from Jazz Pharmaceutical and grants from Genentech, outside the submitted work. Dr. Emmanuelle Waubant reports personal fees from DBV, Jazz Pharmaceuticals, Emerald, outside the submitted work. Dr. Pierre Antoine Gourraud received consulting fees or sponsored research from major pharmaceuticals companies all dealt with through academic pipelines: Merieux, Biogen, Merck, Methodomics, WeData, Boston Scientific, AstraZeneca, Cook. He was also founder (2008) www.methodomics.com and co‐Founder (2018) www.wedata.science . Dr. Jennifer Graves received grants from Genentech during the conduct of the study. She received grants from Biogen, personal fees from Novartis, and grants from Octave outside the submitted work.
Publisher Copyright:
© 2020 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association
PY - 2021/1
Y1 - 2021/1
N2 - Objective: To determine whether a small, wearable multisensor device can discriminate between progressive versus relapsing multiple sclerosis (MS) and capture limb progression over a short interval, using finger and foot tap data. Methods: Patients with MS were followed prospectively during routine clinic visits approximately every 6 months. At each visit, participants performed finger and foot taps wearing the MYO-band, which includes accelerometer, gyroscope, and surface electromyogram sensors. Metrics of within-patient limb progression were created by combining the change in signal waveform features over time. The resulting upper (UE) and lower (LE) extremity metrics’ discrimination of progressive versus relapsing MS were evaluated with calculation of AUROC. Comparisons with Expanded Disability Status Scale (EDSS) scores were made with Pearson correlation. Results: Participants included 53 relapsing and 15 progressive MS (72% female, baseline mean age 48 years, median disease duration 11 years, median EDSS 2.5, median 10 months follow-up). The final summary metrics differentiated relapsing from secondary progressive MS with AUROC UE 0.93 and LE 0.96. The metrics were associated with baseline EDSS (UE P = 0.0003, LE P = 0.0007). While most had no change in EDSS during the short follow-up, several had evidence of progression by the multisensor metrics. Interpretation: Within a short follow-up interval, this novel multisensor algorithm distinguished progressive from relapsing MS and captured changes in limb function. Inexpensive, noninvasive and easy to use, this novel outcome is readily adaptable to clinical practice and trials as a MS vital sign. This approach also holds promise to monitor limb dysfunction in other neurological diseases.
AB - Objective: To determine whether a small, wearable multisensor device can discriminate between progressive versus relapsing multiple sclerosis (MS) and capture limb progression over a short interval, using finger and foot tap data. Methods: Patients with MS were followed prospectively during routine clinic visits approximately every 6 months. At each visit, participants performed finger and foot taps wearing the MYO-band, which includes accelerometer, gyroscope, and surface electromyogram sensors. Metrics of within-patient limb progression were created by combining the change in signal waveform features over time. The resulting upper (UE) and lower (LE) extremity metrics’ discrimination of progressive versus relapsing MS were evaluated with calculation of AUROC. Comparisons with Expanded Disability Status Scale (EDSS) scores were made with Pearson correlation. Results: Participants included 53 relapsing and 15 progressive MS (72% female, baseline mean age 48 years, median disease duration 11 years, median EDSS 2.5, median 10 months follow-up). The final summary metrics differentiated relapsing from secondary progressive MS with AUROC UE 0.93 and LE 0.96. The metrics were associated with baseline EDSS (UE P = 0.0003, LE P = 0.0007). While most had no change in EDSS during the short follow-up, several had evidence of progression by the multisensor metrics. Interpretation: Within a short follow-up interval, this novel multisensor algorithm distinguished progressive from relapsing MS and captured changes in limb function. Inexpensive, noninvasive and easy to use, this novel outcome is readily adaptable to clinical practice and trials as a MS vital sign. This approach also holds promise to monitor limb dysfunction in other neurological diseases.
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U2 - 10.1002/acn3.51187
DO - 10.1002/acn3.51187
M3 - Article
C2 - 33211403
AN - SCOPUS:85096715802
SN - 2328-9503
VL - 8
SP - 4
EP - 14
JO - Annals of Clinical and Translational Neurology
JF - Annals of Clinical and Translational Neurology
IS - 1
ER -