Assessment of Upper Extremity Function in Multiple Sclerosis: Feasibility of a Digital Pinching Test
Background:The development of touchscreen-based assessments of upper extremity function could benefit people with multiple sclerosis (MS) by allowing convenient, quantitative assessment of their condition. The Pinching Test forms a part of the Floodlight smartphone app (F. Hoffmann-La Roche Ltd, Bas...
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| Vydáno v: | JMIR formative research Ročník 7; s. e46521 |
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02.10.2023
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| Abstract | Background:The development of touchscreen-based assessments of upper extremity function could benefit people with multiple sclerosis (MS) by allowing convenient, quantitative assessment of their condition. The Pinching Test forms a part of the Floodlight smartphone app (F. Hoffmann-La Roche Ltd, Basel, Switzerland) for people with MS and was designed to capture upper extremity function.Objective:This study aimed to evaluate the Pinching Test as a tool for remotely assessing upper extremity function in people with MS.Methods:Using data from the 24-week, prospective feasibility study investigating the Floodlight Proof-of-Concept app for remotely assessing MS, we examined 13 pinching, 11 inertial measurement unit (IMU)–based, and 13 fatigability features of the Pinching Test. We assessed the test-retest reliability using intraclass correlation coefficients [second model, first type; ICC(2,1)], age- and sex-adjusted cross-sectional Spearman rank correlation, and known-groups validity (data aggregation: median [all features], SD [fatigability features]).Results:We evaluated data from 67 people with MS (mean Expanded Disability Status Scale [EDSS]: 2.4 [SD 1.4]) and 18 healthy controls. In this cohort of early MS, pinching features were reliable [ICC(2,1)=0.54-0.81]; correlated with standard clinical assessments, including the Nine-Hole Peg Test (9HPT) (|r|=0.26-0.54; 10/13 features), EDSS (|r|=0.25-0.36; 7/13 features), and the arm items of the 29-item Multiple Sclerosis Impact Scale (MSIS-29) (|r|=0.31-0.52; 7/13 features); and differentiated people with MS-Normal from people with MS-Abnormal (area under the curve: 0.68-0.78; 8/13 features). IMU-based features showed similar test-retest reliability [ICC(2,1)=0.47-0.84] but showed little correlations with standard clinical assessments. In contrast, fatigability features (SD aggregation) correlated with 9HPT time (|r|=0.26-0.61; 10/13 features), EDSS (|r|=0.26-0.41; 8/13 features), and MSIS-29 arm items (|r|=0.32-0.46; 7/13 features).Conclusions:The Pinching Test provides a remote, objective, and granular assessment of upper extremity function in people with MS that can potentially complement standard clinical evaluation. Future studies will validate it in more advanced MS.Trial Registration:ClinicalTrials.gov NCT02952911; https://clinicaltrials.gov/study/NCT02952911 |
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| AbstractList | The development of touchscreen-based assessments of upper extremity function could benefit people with multiple sclerosis (MS) by allowing convenient, quantitative assessment of their condition. The Pinching Test forms a part of the Floodlight smartphone app (F. Hoffmann-La Roche Ltd, Basel, Switzerland) for people with MS and was designed to capture upper extremity function.BACKGROUNDThe development of touchscreen-based assessments of upper extremity function could benefit people with multiple sclerosis (MS) by allowing convenient, quantitative assessment of their condition. The Pinching Test forms a part of the Floodlight smartphone app (F. Hoffmann-La Roche Ltd, Basel, Switzerland) for people with MS and was designed to capture upper extremity function.This study aimed to evaluate the Pinching Test as a tool for remotely assessing upper extremity function in people with MS.OBJECTIVEThis study aimed to evaluate the Pinching Test as a tool for remotely assessing upper extremity function in people with MS.Using data from the 24-week, prospective feasibility study investigating the Floodlight Proof-of-Concept app for remotely assessing MS, we examined 13 pinching, 11 inertial measurement unit (IMU)-based, and 13 fatigability features of the Pinching Test. We assessed the test-retest reliability using intraclass correlation coefficients [second model, first type; ICC(2,1)], age- and sex-adjusted cross-sectional Spearman rank correlation, and known-groups validity (data aggregation: median [all features], SD [fatigability features]).METHODSUsing data from the 24-week, prospective feasibility study investigating the Floodlight Proof-of-Concept app for remotely assessing MS, we examined 13 pinching, 11 inertial measurement unit (IMU)-based, and 13 fatigability features of the Pinching Test. We assessed the test-retest reliability using intraclass correlation coefficients [second model, first type; ICC(2,1)], age- and sex-adjusted cross-sectional Spearman rank correlation, and known-groups validity (data aggregation: median [all features], SD [fatigability features]).We evaluated data from 67 people with MS (mean Expanded Disability Status Scale [EDSS]: 2.4 [SD 1.4]) and 18 healthy controls. In this cohort of early MS, pinching features were reliable [ICC(2,1)=0.54-0.81]; correlated with standard clinical assessments, including the Nine-Hole Peg Test (9HPT) (|r|=0.26-0.54; 10/13 features), EDSS (|r|=0.25-0.36; 7/13 features), and the arm items of the 29-item Multiple Sclerosis Impact Scale (MSIS-29) (|r|=0.31-0.52; 7/13 features); and differentiated people with MS-Normal from people with MS-Abnormal (area under the curve: 0.68-0.78; 8/13 features). IMU-based features showed similar test-retest reliability [ICC(2,1)=0.47-0.84] but showed little correlations with standard clinical assessments. In contrast, fatigability features (SD aggregation) correlated with 9HPT time (|r|=0.26-0.61; 10/13 features), EDSS (|r|=0.26-0.41; 8/13 features), and MSIS-29 arm items (|r|=0.32-0.46; 7/13 features).RESULTSWe evaluated data from 67 people with MS (mean Expanded Disability Status Scale [EDSS]: 2.4 [SD 1.4]) and 18 healthy controls. In this cohort of early MS, pinching features were reliable [ICC(2,1)=0.54-0.81]; correlated with standard clinical assessments, including the Nine-Hole Peg Test (9HPT) (|r|=0.26-0.54; 10/13 features), EDSS (|r|=0.25-0.36; 7/13 features), and the arm items of the 29-item Multiple Sclerosis Impact Scale (MSIS-29) (|r|=0.31-0.52; 7/13 features); and differentiated people with MS-Normal from people with MS-Abnormal (area under the curve: 0.68-0.78; 8/13 features). IMU-based features showed similar test-retest reliability [ICC(2,1)=0.47-0.84] but showed little correlations with standard clinical assessments. In contrast, fatigability features (SD aggregation) correlated with 9HPT time (|r|=0.26-0.61; 10/13 features), EDSS (|r|=0.26-0.41; 8/13 features), and MSIS-29 arm items (|r|=0.32-0.46; 7/13 features).The Pinching Test provides a remote, objective, and granular assessment of upper extremity function in people with MS that can potentially complement standard clinical evaluation. Future studies will validate it in more advanced MS.CONCLUSIONSThe Pinching Test provides a remote, objective, and granular assessment of upper extremity function in people with MS that can potentially complement standard clinical evaluation. Future studies will validate it in more advanced MS.ClinicalTrials.gov NCT02952911; https://clinicaltrials.gov/study/NCT02952911.TRIAL REGISTRATIONClinicalTrials.gov NCT02952911; https://clinicaltrials.gov/study/NCT02952911. Background:The development of touchscreen-based assessments of upper extremity function could benefit people with multiple sclerosis (MS) by allowing convenient, quantitative assessment of their condition. The Pinching Test forms a part of the Floodlight smartphone app (F. Hoffmann-La Roche Ltd, Basel, Switzerland) for people with MS and was designed to capture upper extremity function.Objective:This study aimed to evaluate the Pinching Test as a tool for remotely assessing upper extremity function in people with MS.Methods:Using data from the 24-week, prospective feasibility study investigating the Floodlight Proof-of-Concept app for remotely assessing MS, we examined 13 pinching, 11 inertial measurement unit (IMU)–based, and 13 fatigability features of the Pinching Test. We assessed the test-retest reliability using intraclass correlation coefficients [second model, first type; ICC(2,1)], age- and sex-adjusted cross-sectional Spearman rank correlation, and known-groups validity (data aggregation: median [all features], SD [fatigability features]).Results:We evaluated data from 67 people with MS (mean Expanded Disability Status Scale [EDSS]: 2.4 [SD 1.4]) and 18 healthy controls. In this cohort of early MS, pinching features were reliable [ICC(2,1)=0.54-0.81]; correlated with standard clinical assessments, including the Nine-Hole Peg Test (9HPT) (|r|=0.26-0.54; 10/13 features), EDSS (|r|=0.25-0.36; 7/13 features), and the arm items of the 29-item Multiple Sclerosis Impact Scale (MSIS-29) (|r|=0.31-0.52; 7/13 features); and differentiated people with MS-Normal from people with MS-Abnormal (area under the curve: 0.68-0.78; 8/13 features). IMU-based features showed similar test-retest reliability [ICC(2,1)=0.47-0.84] but showed little correlations with standard clinical assessments. In contrast, fatigability features (SD aggregation) correlated with 9HPT time (|r|=0.26-0.61; 10/13 features), EDSS (|r|=0.26-0.41; 8/13 features), and MSIS-29 arm items (|r|=0.32-0.46; 7/13 features).Conclusions:The Pinching Test provides a remote, objective, and granular assessment of upper extremity function in people with MS that can potentially complement standard clinical evaluation. Future studies will validate it in more advanced MS.Trial Registration:ClinicalTrials.gov NCT02952911; https://clinicaltrials.gov/study/NCT02952911 BackgroundThe development of touchscreen-based assessments of upper extremity function could benefit people with multiple sclerosis (MS) by allowing convenient, quantitative assessment of their condition. The Pinching Test forms a part of the Floodlight smartphone app (F. Hoffmann-La Roche Ltd, Basel, Switzerland) for people with MS and was designed to capture upper extremity function. ObjectiveThis study aimed to evaluate the Pinching Test as a tool for remotely assessing upper extremity function in people with MS. MethodsUsing data from the 24-week, prospective feasibility study investigating the Floodlight Proof-of-Concept app for remotely assessing MS, we examined 13 pinching, 11 inertial measurement unit (IMU)–based, and 13 fatigability features of the Pinching Test. We assessed the test-retest reliability using intraclass correlation coefficients [second model, first type; ICC(2,1)], age- and sex-adjusted cross-sectional Spearman rank correlation, and known-groups validity (data aggregation: median [all features], SD [fatigability features]). ResultsWe evaluated data from 67 people with MS (mean Expanded Disability Status Scale [EDSS]: 2.4 [SD 1.4]) and 18 healthy controls. In this cohort of early MS, pinching features were reliable [ICC(2,1)=0.54-0.81]; correlated with standard clinical assessments, including the Nine-Hole Peg Test (9HPT) (|r|=0.26-0.54; 10/13 features), EDSS (|r|=0.25-0.36; 7/13 features), and the arm items of the 29-item Multiple Sclerosis Impact Scale (MSIS-29) (|r|=0.31-0.52; 7/13 features); and differentiated people with MS-Normal from people with MS-Abnormal (area under the curve: 0.68-0.78; 8/13 features). IMU-based features showed similar test-retest reliability [ICC(2,1)=0.47-0.84] but showed little correlations with standard clinical assessments. In contrast, fatigability features (SD aggregation) correlated with 9HPT time (|r|=0.26-0.61; 10/13 features), EDSS (|r|=0.26-0.41; 8/13 features), and MSIS-29 arm items (|r|=0.32-0.46; 7/13 features). ConclusionsThe Pinching Test provides a remote, objective, and granular assessment of upper extremity function in people with MS that can potentially complement standard clinical evaluation. Future studies will validate it in more advanced MS. Trial RegistrationClinicalTrials.gov NCT02952911; https://clinicaltrials.gov/study/NCT02952911 |
| Author | Dondelinger, Frank Lipsmeier, Florian Montalban, Xavier Midaglia, Luciana Lindemann, Michael Graves, Jennifer S Zhang, Yan-Ping Bernasconi, Corrado Elantkowski, Marcin |
| AuthorAffiliation | 1 Department of Neurosciences University of California San Diego, CA United States 3 Department of Neurology-Neuroimmunology Multiple Sclerosis Centre of Catalonia, Vall d’Hebron University Hospital Barcelona Spain 2 F. Hoffmann-La Roche Ltd Basel Switzerland 4 Department of Medicine Autonomous University of Barcelona Barcelona Spain |
| AuthorAffiliation_xml | – name: 3 Department of Neurology-Neuroimmunology Multiple Sclerosis Centre of Catalonia, Vall d’Hebron University Hospital Barcelona Spain – name: 2 F. Hoffmann-La Roche Ltd Basel Switzerland – name: 1 Department of Neurosciences University of California San Diego, CA United States – name: 4 Department of Medicine Autonomous University of Barcelona Barcelona Spain |
| Author_xml | – sequence: 1 givenname: Jennifer S orcidid: 0000-0003-1539-1940 surname: Graves fullname: Graves, Jennifer S – sequence: 2 givenname: Marcin orcidid: 0000-0001-5841-153X surname: Elantkowski fullname: Elantkowski, Marcin – sequence: 3 givenname: Yan-Ping orcidid: 0000-0001-7602-4453 surname: Zhang fullname: Zhang, Yan-Ping – sequence: 4 givenname: Frank orcidid: 0000-0003-1816-6300 surname: Dondelinger fullname: Dondelinger, Frank – sequence: 5 givenname: Florian orcidid: 0000-0002-8663-819X surname: Lipsmeier fullname: Lipsmeier, Florian – sequence: 6 givenname: Corrado orcidid: 0000-0002-1019-5468 surname: Bernasconi fullname: Bernasconi, Corrado – sequence: 7 givenname: Xavier orcidid: 0000-0002-0098-9918 surname: Montalban fullname: Montalban, Xavier – sequence: 8 givenname: Luciana orcidid: 0000-0001-7981-2228 surname: Midaglia fullname: Midaglia, Luciana – sequence: 9 givenname: Michael orcidid: 0000-0003-1010-3890 surname: Lindemann fullname: Lindemann, Michael |
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| CitedBy_id | crossref_primary_10_2196_57033 crossref_primary_10_2196_60673 crossref_primary_10_2196_63090 crossref_primary_10_2196_70871 crossref_primary_10_1177_13524585241301854 crossref_primary_10_1177_20552076251314550 |
| Cites_doi | 10.2196/30394 10.7224/1537-2073.2012-053 10.1016/s0165-0270(01)00373-9 10.3390/brainsci11091247 10.1080/15427609.2017.1340052 10.3389/fmedt.2021.714682 10.1002/mds.27376 10.1038/s41586-020-2649-2 10.3389/fpsyg.2017.00456 10.1371/journal.pone.0058643 10.1212/WNL.0000000000008519 10.1016/j.msard.2017.02.013 10.1002/ana.22366 10.2196/14863 10.1016/j.jns.2006.02.018 10.1177/1352458514567553 10.1056/NEJMra1401483 10.1007/s00415-006-0431-5 10.1007/s10865-017-9840-4 10.1016/s0894-1130(03)80019-4 10.1038/s41746-023-00767-1 10.1177/13524585211028561 10.1177/1352458517690824 10.1016/j.jht.2011.05.001 10.1016/j.ensci.2020.100237 10.1212/wnl.33.11.1444 10.1038/s41592-020-0772-5 10.2196/26608 10.1016/s0021-9290(02)00340-8 10.1016/j.jht.2016.08.002 10.1093/brain/122.5.871 10.1016/j.jcm.2016.02.012 10.1016/j.imu.2017.05.005 10.1002/acn3.51187 10.1097/MRR.0000000000000145 10.1007/s00221-017-5075-4 10.1093/brain/124.5.962 |
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| Copyright | 2023. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. Jennifer S Graves, Marcin Elantkowski, Yan-Ping Zhang, Frank Dondelinger, Florian Lipsmeier, Corrado Bernasconi, Xavier Montalban, Luciana Midaglia, Michael Lindemann. Originally published in JMIR Formative Research (https://formative.jmir.org), 02.10.2023. Jennifer S Graves, Marcin Elantkowski, Yan-Ping Zhang, Frank Dondelinger, Florian Lipsmeier, Corrado Bernasconi, Xavier Montalban, Luciana Midaglia, Michael Lindemann. Originally published in JMIR Formative Research (https://formative.jmir.org), 02.10.2023. 2023 |
| Copyright_xml | – notice: 2023. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: Jennifer S Graves, Marcin Elantkowski, Yan-Ping Zhang, Frank Dondelinger, Florian Lipsmeier, Corrado Bernasconi, Xavier Montalban, Luciana Midaglia, Michael Lindemann. Originally published in JMIR Formative Research (https://formative.jmir.org), 02.10.2023. – notice: Jennifer S Graves, Marcin Elantkowski, Yan-Ping Zhang, Frank Dondelinger, Florian Lipsmeier, Corrado Bernasconi, Xavier Montalban, Luciana Midaglia, Michael Lindemann. Originally published in JMIR Formative Research (https://formative.jmir.org), 02.10.2023. 2023 |
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| Snippet | Background:The development of touchscreen-based assessments of upper extremity function could benefit people with multiple sclerosis (MS) by allowing... The development of touchscreen-based assessments of upper extremity function could benefit people with multiple sclerosis (MS) by allowing convenient,... BackgroundThe development of touchscreen-based assessments of upper extremity function could benefit people with multiple sclerosis (MS) by allowing... |
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| StartPage | e46521 |
| SubjectTerms | Hands Motor ability Multiple sclerosis Original Paper Range of motion Sensors Smartphones Spasticity Tremor (Muscular contraction) |
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| Title | Assessment of Upper Extremity Function in Multiple Sclerosis: Feasibility of a Digital Pinching Test |
| URI | https://www.proquest.com/docview/2918547554 https://www.proquest.com/docview/2871658639 https://pubmed.ncbi.nlm.nih.gov/PMC10580133 https://doaj.org/article/128fc2e6b1654d6c8f07e2a05c69ac41 |
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