Finger and foot tapping as alternative outcomes of upper and lower extremity function in multiple sclerosis

Exploring concordance between face-to-face and tele-assessment of upper limb functionality in people with multiple sclerosis

BACKGROUND

People with multiple sclerosis (PwMS) experience fatigue, pain, and sensory-motor disturbances that limit fundamental daily activities. The development of techniques for remotely assessing upper limb functionality is crucial for advancing telemedicine as an integral part of the continuum of care for PwMS.

OBJECTIVE

To assess the agreement between face-to-face assessment and tele-assessment of upper limb functionality in PwMS.

METHOD

A descriptive study was conducted to investigate the concordance. Participants were evaluated twice: once physically and once remotely. Upper limb functionality (Manual Ability Measure), upper limb extremity muscle strength and endurance (30-second Arm Curl Test), and range of motion (Range of Movement) were assessed.

RESULTS

A total of 42 PwMS were included in this study. The participants were included in a face-to-face assessment and tele-assessment of upper limb functionality. Concordance between both methods for upper limb extremity muscle strength and endurance, manual dexterity, motor speed, precision, and range of motion was assessed as high. Moreover, most confidence intervals were narrow and excluded 0.8.

CONCLUSION

Tele-assessment of upper limb functionality showed high concordance with face-to-face assessment in PwMS. Tele-assessment of upper limb functionality through a video call system could serve as a complementary or alternative method to meet the increasing demand for monitoring multiple sclerosis disease progression.

A Simple Field Tapping Test for Evaluating Frequency Qualities of the Lower Limb Neuromuscular System in Soccer Players: A Validity and Reliability Study

Over the years, the foot tapping test protocol has been proposed by scientists to identify the capabilities of the lower limb neuromuscular system in the medical context; however, to our knowledge, no studies have established its usefulness and relationship to athletic performance. The aim of the present study was to test the reliability, criterion validity and sensitivity of a new foot tapping (TAP) test, and to examine its relationship with proxies of athletic performance in soccer players. Forty voluntary soccer players of two different levels participated in this study (20 players from the national level: age: 22.6 ± 2.5 years and 20 players from regional level: 25.1 ± 3.6 years). They performed the TAP test on two separate occasions to test its relative and absolute reliability. To examine the criterion validity of the TAP test, all participants performed four types of jumps, sprint tests, agility tests, the Wingate test and the finger tapping test considered a gold standard tapping test. The sensitivity was assessed with national and regional player levels. The TAP test presented a high relative and absolute reliability with intra-class correlation coefficient ICC > 0.90, standard errors of measurement SEM < 5% and mean difference ±95% limits of agreement equal to 0.2 ± 0.8 tap·s−1. National level players showed a higher TAP score (p < 0.001; dz = 1.96, large) compared to regional players (9.68 ± 1.41 tap·s−1 vs. 7.28 ± 1.01 tap·s−1, respectively) and the value of area under curve measured by the receiver operating characteristic curve technique was 0.95 (95% CI: 0.827−0.990). The TAP test showed a significant association with the finger tapping test (r = 0.84, p < 0.001), whereas no correlation was seen between the TAP test and all the other physical tests measured. The TAP test could be considered a valid and reliable test to assess lower limb neuromuscular ability in soccer players.

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

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 NeurExTM 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.

Digital Biomarkers in Multiple Sclerosis

For incurable diseases, such as multiple sclerosis (MS), the prevention of progression and the preservation of quality of life play a crucial role over the entire therapy period. In MS, patients tend to become ill at a younger age and are so variable in terms of their disease course that there is no standard therapy. Therefore, it is necessary to enable a therapy that is as personalized as possible and to respond promptly to any changes, whether with noticeable symptoms or symptomless. Here, measurable parameters of biological processes can be used, which provide good information with regard to prognostic and diagnostic aspects, disease activity and response to therapy, so-called biomarkers Increasing digitalization and the availability of easy-to-use devices and technology also enable healthcare professionals to use a new class of digital biomarkers-digital health technologies-to explain, influence and/or predict health-related outcomes. The technology and devices from which these digital biomarkers stem are quite broad, and range from wearables that collect patients' activity during digitalized functional tests (e.g., the Multiple Sclerosis Performance Test, dual-tasking performance and speech) to digitalized diagnostic procedures (e.g., optical coherence tomography) and software-supported magnetic resonance imaging evaluation. These technologies offer a timesaving way to collect valuable data on a regular basis over a long period of time, not only once or twice a year during patients' routine visit at the clinic. Therefore, they lead to real-life data acquisition, closer patient monitoring and thus a patient dataset useful for precision medicine. Despite the great benefit of such increasing digitalization, for now, the path to implementing digital biomarkers is widely unknown or inconsistent. Challenges around validation, infrastructure, evidence generation, consistent data collection and analysis still persist. In this narrative review, we explore existing and future opportunities to capture clinical digital biomarkers in the care of people with MS, which may lead to a digital twin of the patient. To do this, we searched published papers for existing opportunities to capture clinical digital biomarkers for different functional systems in the context of MS, and also gathered perspectives on digital biomarkers under development or already existing as a research approach.

Smartphone-derived keystroke dynamics are sensitive to relevant changes in multiple sclerosis

Background

To investigate smartphone keystroke dynamics (KD), derived from regular typing, on sensitivity to relevant change in disease activity, fatigue, and clinical disability in multiple sclerosis (MS).

Methods

Preplanned interim analysis of a cohort study with 102 MS patients assessed at baseline and 3‐month follow‐up for gadolinium‐enhancing lesions on magnetic resonance imaging, relapses, fatigue and clinical disability outcomes. Keyboard interactions were unobtrusively collected during typing using the Neurokeys App. From these interactions 15 keystroke features were derived and aggregated using 16 summary and time series statistics. Responsiveness of KD to clinical anchor‐based change was assessed by calculating the area under the receiver operating characteristic curve (AUC). The optimal cut‐point was used to determine the minimal clinically important difference (MCID) and compared to the smallest real change (SRC). Commonly used clinical measures were analyzed for comparison.

Results

A total of 94 patients completed the follow‐up. The five best performing keystroke features had AUC‐values in the range 0.72–0.78 for change in gadolinium‐enhancing lesions, 0.67–0.70 for the Checklist Individual Strength Fatigue subscale, 0.66–0.79 for the Expanded Disability Status Scale, 0.69–0.73 for the Ambulation Functional System, and 0.72–0.75 for Arm function in MS Questionnaire. The MCID of these features exceeded the SRC on group level. KD had higher AUC‐values than comparative clinical measures for the study outcomes, aside from ambulatory function.

Conclusions

Keystroke dynamics demonstrated good responsiveness to changes in disease activity, fatigue, and clinical disability in MS, and detected important change beyond measurement error on group level. Responsiveness of KD was better than commonly used clinical measures.

State and trait of finger tapping performance in multiple sclerosis

Finger tapping tests have been shown feasible to assess motor performance in multiple sclerosis (MS) and were observed to be strongly associated with the estimated clinical severity of the disease. Therefore, tapping tests could be an adequate tool to assess disease status in MS. In this study we examined potential influencing factors on a maximum tapping task with the whole upper-limb for 10 s in 40 MS patients using linear mixed effects modelling. Patients were tested in three sessions with two trials per body-side per session over the course of 4–27 days of inpatient rehabilitation. Tested factors were the expanded disability scale (EDSS) score, laterality of MS, age, sex, hand dominance, time of day, session, trial (first or second), time between sessions, and the reported day form. A second model used these factors to examine the self-reported day form of patients. Linear mixed effects modelling indicated the tapping test to have a good inter-trial (proportional variance < 0.01) and inter-session reliability (non-significant; when controlling for time between sessions), an influence of hand-dominance (proportional variance 0.08), to be strongly associated with the EDSS (eta² = 0.22, interaction with laterality of MS eta² = 0.12) and to be not associated with the reported day form. The model explained 87% (p < 0.01) of variance in tapping performance. Lastly, we were able to observe a positive effect of neurologic inpatient rehabilitation on task performance obvious from a significant effect of the time between sessions (eta² = 0.007; longer time spans between sessions were associated with higher increments in performance). Day form was only impacted by EDSS and the time of the day (p < 0.01, R² = 0.57, eta²_TIME = 0.017, eta²_EDSS = 01.19). We conclude that the tapping test is a reliable and valid assessment tool for MS.

Biosensor vital sign detects multiple sclerosis progression

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.

Early-warning signals for disease activity in patients diagnosed with multiple sclerosis based on keystroke dynamics

Within data gathered through passive monitoring of patients with Multiple Sclerosis (MS), there is a clear necessity for improved methodological approaches to match the emergence of continuous, objective, measuring technologies. As most gold standards measure infrequently and require clinician presence, fluctuations in the daily progression are not accounted for. Due to the underlying conditions of homogeneity and stationarity (the main tenets of ergodicity) not being met for the majority of the statistical methods employed in the clinical setting, alternative approaches should be investigated. A solution is to use a non-linear time series analysis approach. Here, Early-Warning Signals (EWS) in the form of critical fluctuations in Keystroke Dynamics (KD), collected using participant's smartphones, are investigated as indicators for a clinical change in three groups. These are patients with MS and changes in Magnetic Resonance Imaging (MRI), patients with MS but without changes in MRI, and healthy controls (HCs). Here, we report examples of EWS and changes in KD coinciding with clinically relevant changes in outcome measures in both patients with and without differences in the amount of MRI enhancing lesions. We also report no clinically relevant changes in EWS in the HC population. This study is a first promising step toward using EWS to identify periods of instability as measured by a continuous objective measure as a proxy for outcome measures in the field of MS.

Sensorimotor function in progressive multiple sclerosis

BACKGROUND

A sensitive test reflecting subtle sensorimotor changes throughout disease progression independent of mobility impairment is currently lacking in progressive multiple sclerosis.

OBJECTIVES

We examined non-ambulatory measures of upper and lower extremity sensorimotor function that may reveal differences between relapsing-remitting and progressive forms of multiple sclerosis.

METHODS

Cutaneous sensitivity, proprioception, central motor function and mobility were assessed in 32 relapsing-remitting and 31 progressive multiple sclerosis patients and 30 non-multiple sclerosis controls.

RESULTS

Cutaneous sensation differed between relapsing-remitting and progressive multiple sclerosis at the foot and to a lesser extent the hand. Proprioception function in the upper but not the lower extremity differed between relapsing-remitting and progressive multiple sclerosis, but was different for both upper and lower extremities between multiple sclerosis patients and non-multiple sclerosis controls. Foot-tap but not hand-tap speed was slower in progressive compared to relapsing-remitting multiple sclerosis, suggestive of greater central motor function impairment in the lower extremity in progressive multiple sclerosis. In addition, the non-ambulatory sensorimotor measures were more sensitive in detecting differences between relapsing-remitting and progressive multiple sclerosis than mobility assessed with the 25-foot walk test.

CONCLUSION

This study provides novel information about changes in sensorimotor function in progressive compared with relapsing-remitting forms of multiple sclerosis, and in particular the importance of assessing both upper and lower extremity function. Importantly, our findings showed loss of proprioceptive function in multiple sclerosis but also in progressive compared to relapsing-remitting multiple sclerosis.

[The efficacy and safety of siponimod in the Russian population of patients with secondary progressive multiple sclerosis]

AIM

To study the efficacy and safety of siponimod in patients with secondary progressive multiple sclerosis (SPMS) in the Russian population of the EXPAND study.

MATERIAL AND METHODS

Ninety-four patients with SPMS from Russia were included in the analysis. Sixty-three patients received siponimod and 31 patients received placebo. The primary endpoint of the study was time to 3-month confirmed disability progression (3m-CDP) events, other clinical and radiological endpoints were also evaluated.

RESULTS

The siponimod group showed a 54% reduction in the risk of 3m-CDP compared with the placebo group (p=0.0334). Secondary endpoints also showed the advantage of the drug over placebo. In the siponimod group, mild adverse events associated with impaired liver function, as well as arterial hypertension, were more common. No patient left the study due to an adverse event.

CONCLUSION

The use of siponimod in patients with SPMS in the Russian population reduced the risk of disability progression. Siponimod showed a favorable safety profile.

Smartphone Level Test Measures Disability in Several Neurological Domains for Patients With Multiple Sclerosis

Our long-term goal is to employ smartphone-embedded sensors to measure various neurological functions in a patient-autonomous manner. The interim goal is to develop simple smartphone tests (apps) and evaluate the clinical utility of these tests by selecting optimal outcomes that correlate well with clinician-measured disability in different neurological domains. In this paper, we used prospectively-acquired data from 112 multiple sclerosis (MS) patients and 15 healthy volunteers (HV) to assess the performance and optimize outcomes of a Level Test. The goal of the test is to tilt the smartphone so that a free-rolling ball travels to and remains in the center of the screen. An accelerometer detects tilting and records the coordinates of the ball at set time intervals. From this data, we derived five features: path length traveled, time spent in the center of the screen, average distance from the center, average speed while in the center, and number of direction changes underwent by the ball. Time in center proved to be the most sensitive feature to differentiate MS patients from HV and had the strongest correlations with clinician-derived scales. Its superiority was validated in an independent validation cohort of 29 MS patients. A linear combination of different Level features failed to outperform time in center in an independent validation cohort. Limited longitudinal data demonstrated that the Level features were relatively stable intra-individually within 4 months, without definitive evidence of learning. In contrast to previously developed smartphone tests that predominantly measure motoric functions, Level features correlated strongly with reaction time and moderately with cerebellar functions and proprioception, validating its complementary clinical value in the MS app suite. The Level Test measures neurological disability in several domains in two independent cross-sectional cohorts (original and validation). An ongoing longitudinal cohort further investigates whether patient-autonomous collection of granular functional data allows measurement of patient-specific trajectories of disability progression to better guide treatment decisions.

Upper Extremity Capability Tests in Multiple Sclerosis

Multiple sclerosis is a chronic demyelinating disease. Since attacks are accompanied by psychiatric and physical disabilities, additional symptoms such as withdrawal from the social environment and psychiatric disorders are also observed. It is very important to evaluate patients adequately and correctly, to determine the disability, and treat them with appropriate clinical approach. For this reason, Expanded Disability Status Scale score and upper extremity capacity measurement tests are used in many studies by investigators. These tests provide detailed examination on the patient's upper limbs, and indirectly provide information about their cognitive function. A multi-disciplinary approach for multiple sclerosis patients is the most crucial factor in clinical follow-up and treatment success.

Identifying and Quantifying Neurological Disability via Smartphone

Embedded sensors of the smartphones offer opportunities for granular, patient-autonomous measurements of neurological dysfunctions for disease identification, management, and for drug development. We hypothesized that aggregating data from two simple smartphone tests of fine finger movements with differing contribution of specific neurological domains (i.e., strength & cerebellar functions, vision, and reaction time) will allow establishment of secondary outcomes that reflect domain-specific deficit. This hypothesis was tested by assessing correlations of smartphone-derived outcomes with relevant parts of neurological examination in multiple sclerosis (MS) patients. We developed MS test suite on Android platform, consisting of several simple functional tests. This paper compares cross-sectional and longitudinal performance of Finger tapping and Balloon popping tests by 76 MS patients and 19 healthy volunteers (HV). The primary outcomes of smartphone tests, the average number of taps (per two 10-s intervals) and the average number of pops (per two 26-s intervals) differentiated MS from HV with similar power to traditional, investigator-administered test of fine finger movements, 9-hole peg test (9HPT). Additionally, the secondary outcomes identified patients with predominant cerebellar dysfunction, motor fatigue and poor eye-hand coordination and/or reaction time, as evidenced by significant correlations between these derived outcomes and relevant parts of neurological examination. The intra-individual variance in longitudinal sampling was low. In the time necessary for performing 9HPT, smartphone tests provide much richer and reliable measurements of several distinct neurological functions. These data suggest that combing more creatively-construed smartphone apps may one day recreate the entire neurological examination.