The Multiple Sclerosis Functional Composite and its iPad-based companion, the Multiple Sclerosis Performance Test (MSPT), as well as other traditional function tests must be performed during a clinic visit, which presents challenges for some people with multiple sclerosis (MS).

Smartphone tests were developed, including a remote Timed Up and Go (rTUG), remote 5 Times Sit-to-Stand (r5STS), finger tapping test (FTT), and processing speed test (PST), in addition to open- and closed-eye balance measures. People with MS and a control group (CG) without MS performed smartphone tests and the previously validated, iPad-based MSPT. Convergent validity, sensitivity to disease status, and test-retest reliability were assessed.

The CG (n = 23; mean age, 38.56 ± 18.5 years; 65% female; 74% White) and the MS group (n = 23; mean age, 58.5 ± 11.9 years; 48% female; 83% White; mean disease duration, 11.82 ± 6.72 years) completed tests at a single visit. Valid taps per second on FTT was moderately correlated with the manual dexterity test (Spearman correlation coefficients, ρ = –0.46 [right] and –0.41 [left]). Total number correct on smartphone-administered PST strongly correlated with iPad-administered PST (ρ = 0.78). rTUG had a strong correlation and r5STS had a moderate correlation with the Timed 25-Foot Walk test (ρ = 0.80 and 0.55, respectively). Ellipse volume and ellipse area, derived from open-eye balance tests, showed sensitivity to disease status (partial η2 = 0.08 and 0.07, respectively) and good test-retest reliability (intraclass correlation coefficient = 0.82 and 0.77, respectively).

The FTT, PST, rTUG, and r5STS performed via smartphone application demonstrate convergent validity with their analogous MSPT tests. Open-eye balance outcomes also show promise for use in people with MS. These smartphone-based tests may allow for remote measurement of function for people with MS.

From the Cleveland Clinic Lerner College of Medicine, Cleveland, OH (KB); Department of Quantitative Health Sciences (MD) and Department of Biomedical Engineering (MK, KO, JA), Cleveland Clinic Lerner Research Institute, Cleveland, OH; Mellen Center for Multiple Sclerosis Treatment and Research, Cleveland Clinic, Cleveland, OH (MPM). 

 Marisa P. McGinley, DO, Mellen Center U-10, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44195; 

Part of this work was previously presented in poster format at the American Academy of Neurology Annual Meeting on April 16, 2024, in Denver, Colorado.

 Jay Alberts, PhD, has received consulting fees from Peloton Interactive and research support from the National Institutes of Health (NIH). He has also received intellectual property interests from a discovery or technology relating to health care. Marissa P. McGinley, DO, has received consulting fees from EMD Serono, Genentech, and Octave; she has received research support from Biogen, Genentech, and Novartis. She also receives funding from the NIH. All other authors have declared no relevant disclosures.

 This project was funded by KL2 TR002547.

Katherine Beshears, BS

Mengke Du, MPH

Mandy Koop, PhD

Kelsey Owen, BS

Jay Alberts, PhD

Marisa P. McGinley, DO

A novel battery of self-administered, smartphone application–based neuroperformance tests would allow more frequent, remote assessments of motor and cognitive function in people with multiple sclerosis (MS).

Outcomes derived from the smartphone app correlate with walking speed, manual dexterity, and processing speed tests from the previously validated Multiple Sclerosis Performance Test.

Open-eye balance tests using the Cleveland Clinic Balance Assessment App demonstrate sensitivity to disease status and test-retest reliability in people with MS, meriting further investigation as a novel performance measure.

The development of valid, reliable outcome measures for multiple sclerosis (MS)–related disability is key to both the measurement of treatment effect in clinical trials and the management of chronic disease in individual patients. Standard outcome measures currently in use for MS, such as the Expanded Disability Status Scale, are not sensitive to changes in disability among groups with the most and least amount of disability and focus primarily on ambulation.

 To address some of these concerns, the MS Functional Composite (MSFC) was created; later, the Multiple Sclerosis Performance Test (MSPT) was developed as an iPad adaptation of the MSFC.

However, the MSPT, along with traditional outcome measures, must be performed during an in-office visit, which presents challenges for people with MS. First, they may have access barriers, including living a significant distance from the MS clinic, work and family obligations, financial strain, and physical limitations due to the disease.

 Second, changes in neurological function that occur between visits may go unmeasured, such that it is difficult to appreciate a true level of disability because of infrequent assessment. The availability of in-home, self-administered tests of neurological function, used in conjunction with teleneurology visits, would reduce the number of visits necessary as well as allow more clinical course data to be captured. Finally, although there have been attempts to better capture disability in MS, such as the MSFC, measures that are more sensitive to change across the disability spectrum are still needed. In this study, a smartphone application–based battery of tests for cognitive and motor function was created by adapting several component tests of the MSPT and developing additional novel assessments (

; all supplemental materials are available in a PDF at the end of the online article). Convergent validity with the analogous MSPT tests, effect size, and test-retest reliability were analyzed by performing a cross-sectional study of a group of people with MS and a control group without MS.

A convenience sample of 23 people with MS and 23 control participants completed both the MSPT and the newly developed smartphone batteries. All tests were performed during a single visit at the Cleveland Clinic Mellen Center for Multiple Sclerosis Treatment and Research. Both groups had the same study inclusion criteria: 18 to 75 years old, able to understand the purpose of the study and provide informed consent, and able to comprehend the written and/or audio instructions for the software tool, which were provided in English. Exclusion criteria included a serious eye or vision problem (eg, uncorrected low vision as visual acuity of less than 20/60 of the better eye, cataracts, glaucoma) that would affect their ability to use technology. An additional inclusion criterion for participants with MS was a clinician-confirmed diagnosis of MS. Additional inclusion criteria for the control group were no cognitive impairment as defined by a score of 26 or greater on the Montreal Cognitive Assessment (MoCA), a Patient Health Questionnaire-9 score of less than 15, and no diagnoses of neurological, developmental, or medical illnesses. We did not impose these same additional criteria upon the MS group, as doing so might select for healthy people with MS and limit generalizability.

Participants with MS were recruited from the Mellen Center, and participants without MS were recruited via an institutional review board–approved advertisement that was posted on the Mellen Center website and displayed in flyer form around the Cleveland Clinic campus.

For this pilot stage of smartphone app testing, the component tests were self-administered by participants in the clinic while in the presence of a research coordinator. Validation of tests in a controlled environment was desired so that test instructions could be modified, if necessary, before testing in a remote home environment. Each MSPT iPad test was performed once, and each smartphone-based test was performed twice. There was a 30-minute rest period between each of the 3 trials to ensure participants were not fatigued. The order of smartphone and MSPT administration was counterbalanced between groups to mitigate any learning effects. Auditory and written instructions for each of the component tests performed on the iPad and smartphone were delivered via the application.

The iPad-based MSPT battery development and tests have been described in prior validation publications.

 In brief, the battery includes a manual dexterity test (MDT), walking speed test (WST), and processing speed test (PST). The MDT is an adaptation of the 9-Hole Peg Test (9HPT), the WST is an adaptation of the Timed 25-Foot Walk, and the PST is an adaptation of the Symbol Digit Modalities Test (SDMT).

The components of the smartphone battery were developed as adaptations of the MSPT along with several novel tests. The same smartphone device (iPhone 8) was used by all participants in the study; a research coordinator was present to answer questions for any participants unfamiliar with the device.

In the finger tapping test (FTT), participants are instructed to use a single finger and tap back and forth between 2 dots on the screen for 30 seconds. The test is conducted twice with both hands. The number of valid taps per second is recorded.

A digital version of the Timed Up and Go test (TUG) was developed (ie, remote TUG [rTUG]). To set up, the coordinator marked a line on the floor 3 m from a chair. The same chair, with armrests, was used for all trials. The smartphone was carried for all trials, from beginning to end, either in a pants pocket or in the participant’s hand. Participants started in the seated position and pressed a timer on the smartphone. The participant then walked o the line, turned around, walked back to the chair, and immediately stopped the timer when they sat down. A modified version (rMTUG) was also conducted, in which the participant performed the same procedures as previously described, but instead of walking to the prespecified 3-meter line, they were instructed to walk 3 normal-sized steps and turn around. This was done to create a version of the TUG test with less required setup to facilitate the ease of remote assessments in the future. For the rTUG and rMTUG, participants were instructed to walk at a comfortable and safe pace. To further assess lower extremity function and balance, a digital version of the 5 Times Sit-to-Stand test (5STS) was developed (ie, remote 5STS [rSTS]). Participants began sitting in a chair and pressed a timer on the smartphone. The participant was then instructed to stand up as quickly as they could 5 times. Participants held the phone while performing the r5STS and stopped the timer upon reaching the standing position for a fifth time; a coordinator observed to ensure that exactly 5 repetitions of the sitting-to-standing movement were completed. For each of these 3 tests (rTUG, rMTUG, r5STS), time to complete the task, in seconds, was recorded.

Finally, 2 balance tests were created using the Cleveland Clinic Balance Assessment App (CC-BApp), which has been previously validated for the assessment of postural stability in people with Parkinson disease.

 Trunk rotation as well as trunk movements in the medial-lateral and anterior-posterior directions were collected. The participant started a timer on the phone (either in their pocket or in their hand) and stood with their feet together and eyes open for 30 seconds. They were instructed to remain as still as possible while visually fixating on a marked target on the wall. The test was repeated for another 30 seconds with their eyes closed; a research coordinator stood close by to steady the participant if needed. Using the recorded movements of the center of mass, we calculated an ellipsoid volume that, with 95% probability, contained the center of the points of sway.

To assess cognitive function, a smartphone version of the tablet-based PST was created, which is an adaptation of the SDMT, as described previously. Number of items answered correctly was recorded for the PST.

To assess the usability of the smartphone application, all participants completed a standardized questionnaire of 9 items, with set responses ranging from 1 (strongly disagree) to 5 (strongly agree) (

Participants’ demographic characteristics were summarized as counts and percentages for categorical variables and median and IQR for continuous variables. Comparison of the characteristics between groups was determined using Fisher exact test or Pearson χ

 test for categorical variables and the Wilcoxon rank sum test for continuous variables. Test results of the first
smartphone trial were used for convergent/divergent validity and sensitivity analyses.

Spearman rank (ρ) correlation coefficients were calculated to evaluate relationships between pairs of analogous neuroperformance measures from smartphone and MSPT (iPad-based) data. Additionally, to assess divergent validity, Spearman coefficients were calculated for each of the component smartphone tests when paired with an MSPT test of a different functional domain (ie, lower extremity, fine motor, or cognitive function). Correlation magnitudes were interpreted as negligible (< 0.10), weak (0.10-0.39), moderate (0.40-0.69), strong (0.70-0.89), or very strong (≥ 0.90).

Analysis of covariance (ANCOVA), with age as a covariate, was used to compare smartphone measure performance between groups. Effect sizes were calculated using partial η

 and interpreted as small (0.01-0.059), medium (0.06-0.13), or large (≥ 0.14).

Participants who had a complete set of smartphone measurements (both trials) were included in these analyses. Test-retest reliability of the smartphone battery was examined separately for both groups through the intraclass correlation coefficient (ICC) using a single-measurement, 2-way mixed-effects model with absolute agreement (ICC (2,1)). ICC values were interpreted as indicative of poor (< 0.50), moderate (0.50-0.75), good (0.75-0.89), or excellent (≥ 0.90) reliability. SEM and smallest detectable change (SDC) at a 95% CI were calculated to quantify absolute reliability: SEM = SD × √((1 - ICC)); SDC = SEM × 1.96 × √2 .

All analyses were conducted using R version 4.3.1 (R Foundation for Statistical Computing). All procedures were performed in compliance with relevant laws and institutional guidelines and have been approved by the institutional review board of the Cleveland Clinic (#19-719). Written informed consent was obtained from all participants.

A total of 23 people with MS and 23 control participants completed the assessments. As shown in 

, the people with MS were older (median age, 58.48 [IQR, 42.33-62.99] years) compared with control participants (29.40 [IQR, 24.45-54.05] years) (

 = .003), but there were no significant differences for sex, ethnicity, or race. Participants with MS predominantly had a diagnosis of relapsing-remitting MS (61%), a median disease duration of 12.18 years, and a range of disability as measured by the Patient-Determined Disease Steps (PDDS),

 with 22% reporting no disability (PDDS score, 1) and 52% reporting some degree of gait impairment (PDDS score, 4-7).

 reports the correlation coefficients between the smartphone tests and corresponding MSPT tests, separated by group. For people with MS, correlations were significant for all comparisons except the balance tests vs WST and FTT (left) vs MDT (left). Strong correlations (ρ > 0.70) were observed when comparing rTUG vs rMTUG (ρ = 0.96), rTUG vs WST (ρ = 0.80), rMTUG vs WST (ρ = 0.80), and number correct on PST iPad vs number correct on PST smartphone (ρ = 0.78); this suggests a strong linear correlation and agreement between measures. Moderate correlations were observed for FTT (right) vs MDT (right) (ρ = –0.46) and r5STS vs WST (ρ = 0.55).

 Convergent Validity Between Smartphone and iPad (MSPT) Neuroperformance Tests

) showed negligible to moderate correlations (ρ ≤ 0.69) between smartphone mobility measures (rTUG, rMTUG, r5STS) and nonmobility iPad measures (PST, MDT).

Divergent Validity Between Smartphone and iPad (MSPT) Neuroperformance Tests

After accounting for age as a covariate, a large effect size was observed in FTT (η²p = 0.27 and 0.20 for right [FTT(R)] and left [FTT(L)], respectively) between people with MS and control participants (

). Medium effect sizes were observed for rTUG (η²p = 0.07), ellipse area with open eyes (EA[O]) (η²p = 0.07), and ellipse volume with open eyes (EV[O]) (η²p = 0.08). The balance measures with closed eyes, EA(C) and EV(C), had small effect sizes (η²p = 0.04 and 0.05, respectively), as did the rMTUG (η²p = 0.05) and r5STS (η²p = 0.02) durations. Finally, the total correct (TC) on PST demonstrated a negligible effect size (η²p = 0.00).

Effects Size Results Using η²p to Account for Age

In people with MS, excellent reliability was observed for rTUG (ICC = 0.99), rMTUG (ICC = 0.90), r5STS (ICC = 0.99), EV(C) (ICC = 0.90), FTT(L) (ICC = 0.99), and PST(TC) (ICC = 0.93) (

). Good reliability was observed for FTT(R) (ICC = 0.86), EA(C) (ICC = 0.89), EA(O) (ICC = 0.77), and EV(O) (ICC = 0.82).

ICC for Test-Retest Reliability Between the First and Second Smartphone Measures

The majority of both people with MS and control participants strongly agreed they had previous experience with a computer (82% and 91%, respectively). They also had similar responses upon completion of the smartphone battery, except fewer people with MS reported being “not tired” (median [IQR] of 5 [4-5] in people with MS vs 5 [5] in control participants; 

). Most people with MS agreed or strongly agreed that they had no problems seeing information displayed on the smartphone screen or concentrating on the tests (5 [5] and 5 [4-5], respectively). Likewise, most found that they were given adequate time to complete the tasks (5 [5]) and did not foresee any problems should they take the test again (5 [5]).

Results of Smartphone Application Usability Questionnaire (N = 44

Sample size was originally calculated for 28 per group to detect correlations of 

 equal to or greater than 0.50 with 80% power at α = 0.05. However, the COVID-19 pandemic limited recruitment. The achieved sample (n = 23 per group, 46 total) provided adequate power (> 80%) to detect correlations of 

equal to or greater than 0.60. For test-retest reliability, approximately 20 participants were required to estimate an ICC equal to or greater than 0.60 with 80% power at α = 0.05 and a 10% dropout rate.

We created and pilot-tested smartphone-based neuroperformance tests to assess the level of cognitive, fine motor, and lower extremity function disability in people with MS. The data show that PST, rTUG, and rMTUG tests had strong correlations with their respective MSPT tests, and FTT (right and left) had large effect sizes for distinguishing participants with MS from control participants. Our study also included the first smartphone-based 5STS test used in MS, showing moderate correlation with the WST from the MSPT. Further, we demonstrated that open-eye balance measures originally developed for people with Parkinson disease (ie, CC-BApp) could differentiate people with MS from control participants. These results suggest that FTT, rTUG/rMTUG, and r5STS may provide useful data for measuring function in people with MS; biometric balance tests, particularly open-eye tests, merit further testing as performance-based measures in MS.

The MSFC was developed to provide a multidimensional objective assessment of neurological function but is limited by the need for administration by trained personnel. The MSPT improved upon the MSFC, as it is an in-office, validated iPad adaptation that can be self-administered and automatically uploaded into the electronic medical record. We aimed to further advance characterization in function by creating tests that could be self-administered and performed more frequently outside the clinic setting. The neuroperformance testing administered via smartphone application was not merely a recreation of the MSPT component tests in a different format but a set of related but novel tests accessible via smartphone. The tests are not only self-administered but can also be performed at a range of disability levels with no equipment other than a personal phone. Current outcome measures sometimes have additional barriers to completion, such as the Timed 25-Foot Walk, which requires patients to measure a specific distance. In this study, rMTUG showed promise as a possible substitute for rTUG, increasing ease of home administration; rMTUG demonstrated convergence with rTUG (ρ = 0.96 [IQR, 0.89-0.98]), and excellent test-retest reliability (ICC = 0.90). This is in agreement with other studies that have validated the traditional nondigital version of TUG as a valid measure of lower extremity function in MS.

Prior research has shown that the 5STS test is valid in assessing function in MS.

 Our study results similarly found moderate r5STS correlation with WST (ρ = 0.55) and agreement between repeat tests (ICC = 0.99), but r5STS was not as sensitive to disease status (η²p = 0.02; 

 = .34). r5STS may only moderately correlate with WST due to the tests measuring different domains of lower extremity and physical function.

A novel aspect of the study was the application of biometric balance testing, previously validated as an outcome measure for individuals with Parkinson disease, to people with MS.

 In this study, EA and EV did not demonstrate convergent validity with the WST, which likely reflects that the WST is not a measure of balance. Additionally, the test-retest reliability was good for people with MS but only moderate or poor for control participants, indicating potential concerns with the current version of the smartphone test. Further, sensitivity to disease status (control participants or people with MS) was medium for the eyes-open tests but small for eyes-closed tests. Overall, balance is an important clinical concept, but the smartphone balance tests likely would need further refinement before implementation.

This study builds on other attempts to develop smartphone-based applications for assessing neurological function in MS. Several examples of other developed applications are Floodlight MS, elevateMS, Konectom, and dreaMS.

 Our application is similar to these other suites of tests in that it includes the 9HPT/FTT, PST, and a test of balance. However, the inclusion of 5STS and TUG/MTUG as measures of lower extremity function is unique. Another strength of the present study is the range of disability levels represented in our cohort; although our cohort was small compared with cohorts of other studies, ours included a greater proportion of people using canes or bilateral supports. Our study also highlights the utility of the FTT as an alternative manual dexterity test to the 9HPT. A test similar to the FTT has shown concordance with 9HPT and the ability to distinguish between individuals with MS and control participants.

 This is consistent with our findings that FTT moderately correlates with MDT (ρ = –0.46 and –0.41 for the right and left hands, respectively); moreover, we found good test-retest reliability of the FTT (ICC = 0.86 and 0.90 for the right and left, respectively). FTT also has the added benefit of requiring less equipment than the 9HPT.

This study is limited by its small sample size and the fact that it is a convenience sample, which resulted in a significant difference in age and a (nonstatistically significant) difference in sex distribution between groups. Although we adjusted for age through an ANCOVA, it is possible that age-related cognitive and physical changes could have contributed to the differences observed. Thus, future studies should ensure matching between people with MS and control participants based on age, sex, and MoCA score. Also of note, the MS group had an overrepresentation of men (48%) compared with the overall MS population (~25%). Another potential limitation is that we did not utilize traditional MSFC tests as a comparison with smartphone test outcomes. We chose to compare smartphone tests with the MSPT instead, because we use it daily in clinical practice and it was previously validated against the MSFC.

There are additional limitations to our administration of smartphone tests. Variability in location of the phone (ie, pocket vs hand) could have altered test outcomes. Further, although all the tests can be performed at home, this study was completed in a controlled clinic environment; further testing outside the clinic and longitudinal testing are needed. When administered at home, the tests should be performed in the presence of another person for the prevention of falls or injuries (ie, during the closed-eye balance test). In future studies, administration of rTUG/rMTUG and r5STS could be improved to minimize any lag time; efforts will be made to optimize voice command or sensor-based data to eliminate the need to manually start/stop trials. In addition, as with all previously developed smartphone applications, a significant limitation is the integration into clinical workflow. The application developed and tested in the study was built to integrate with the electronic medical record through a single sign-on process utilized for our current patient portals. This integration was not utilized in this study and would need to be formally tested in future studies to demonstrate usability and feasibility for patients. Finally, as with any new health technology, it will be important to ensure this application is distributed in an equitable manner. Consideration should be given to ways in which people with low computer literacy or no access to a smartphone can still benefit, and the test instructions should be translated into additional languages for wider generalization.

Our study data demonstrate that a self-administered, smartphone-based application can be a valid, reliable, and sensitive means of administering neuroperformance testing to people with MS. Future work is needed to validate these measures longitudinally and develop implementation strategies for routine clinical workflows.

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A novel battery of self-administered, smartphone application–based neuroperformance tests would allow more frequent, remote assessments of motor and cognitive function in people with multiple sclerosis.

Pilot Study of Smartphone-Based Neuroperformance Tests in Multiple Sclerosis

Multiple sclerosis (MS) is a chronic, immune-mediated, neurodegenerative disease of the central nervous system with prevalent vascular comorbidities and associated vascular dysfunction involving arterial stiffness. This study examined the difference in arterial stiffness between people with MS and controls and whether the difference was accounted for by anxiety, depression, and walking endurance, variables not usually included in other studies of arterial stiffness in MS.

The sample included 129 people with MS (age, 48.5 [10.8] years; 70.5% female; Expanded Disability Status Scale score median, 4) and 51 controls without MS (age, 48.7 [11.3] years; 78.4% female) who completed arterial stiffness, anxiety, and depression assessments and the 6-Minute Walk Test (6MWT).

There were significant differences between groups in arterial stiffness (

 = –0.438) and depressive symptoms (

 = –0.927), and walking endurance (

 = 1.618). The bivariate correlations were significant between arterial stiffness and age, body mass index (BMI), mean arterial pressure (MAP), and 6MWT distance (all 

 < .05). The difference in arterial stiffness between groups remained when controlling for age, BMI, MAP, anxiety and depression symptoms, and 6MWT distance.

Our results indicate that people with MS have higher levels of arterial stiffness compared with controls, but this difference is not explained by age, BMI, MAP, anxiety, depression, or walking endurance.

From the Integrative Physiology Lab (SRD, NGD, BF, RWM) and the Department of Kinesiology and Nutrition (SRD, NGD, RWM), College of Applied Health Sciences, University of Illinois Chicago, Chicago, IL; Interdisciplinary School of Health Sciences, University of Ottawa, Ottawa, ON, Canada (LAP); Manning College of Nursing and Health Sciences, University of Massachusetts Boston, Boston, MA (BF). 

: Sydney R. DeJonge, MS, College of Applied Health Sciences, 1919 W Taylor St, Suite 545, Chicago, IL, 60612; 

We would like to thank and acknowledge those who collected data from the previously published studies and all the participants who made these data analyses possible. A special thanks to the committee of the Integrative Physiology of Exercise Conference for allowing these results to be presented as a poster abstract at their conference in November 2024.

We presented these results as a poster at theIntegrative Physiology of Exercise Conference from November 20 to 22, 2024, in University Park, Pennsylvania.

The authors have declared no relevant conflicts of interest.

This study includes data that were collected through research projects funded by the National Multiple Sclerosis Society (RG 4702A1/2) and the University of Illinois Urbana-Champaign Research Board. This research was supported by a predoctoral F31 Fellowship from the National Cancer Institute (1F31CA295016-01).

Sydney R. DeJonge, MS

Noah G. DuBose, MS

Lara A. Pilutti, PhD

Bo Fernhall, PhD

Robert W. Motl, PhD

Arterial stiffness was higher in 129 people with multiple sclerosis (MS) compared with 51 control participants.

Differences in arterial stiffness were not accounted for by age, body mass index, mean arterial pressure, anxiety and depression symptoms, or walking endurance.

Arterial stiffness is associated with aging, obesity, comorbidities, and cardiovascular disease in the general population and needs to be further studied in people with MS.

Multiple sclerosis (MS) is a chronic, immune-mediated neurodegenerative disease of the central nervous system (CNS) with a prevalence of nearly 1 million adults in the United States.

 A hallmark feature of MS includes CNS lesions that are the primary source of disability. Another noteworthy disease feature is comorbidity, defined as a coexisting supplementary disease that is not a direct outcome of MS itself.

 Over 50% of people with MS present with 1 or more comorbidities,

 and vascular comorbidity (eg, hypertension, hyperlipidemia, diabetes, ischemic heart disease)

 is exceedingly prevalent in MS and associated with worse disease outcomes.

The vascular system represents a focal point for understanding vascular comorbidity in MS, as impairment of vascular function may represent an initial marker for the development of vascular comorbidity.

 The functions of the vascular system include maintaining adequate blood flow, blood pressure, and exchange of metabolic byproducts and gases throughout the body.

 Arterial stiffness reflects the structural and mechanical properties of the arterial wall that influence changes in blood pressure and flow

 and can be measured as carotid-femoral pulse wave velocity (cfPWV) using noninvasive techniques.

There is emerging evidence that people with MS have impaired vascular function, particularly arterial stiffness, compared with controls,

 and the difference in arterial stiffness remains when controlling for covariates such as age, sex, body mass index (BMI), and aerobic fitness.

 Arterial stiffness has also been associated with cognitive processing speed,

 in MS. There is no explanation for increased levels of arterial stiffness in people with MS compared with control groups, and there are notable limitations within this research, including small samples of MS and control participants and a lack of consideration of other common outcomes, including anxiety, depression, and walking endurance, along with other covariates such as mean arterial pressure (MAP) when comparing MS and control samples.

 Prior evidence in controls has demonstrated that people with increased anxiety and depression have higher levels of arterial stiffness,

 and due to the prevalence of anxiety and depression in MS, we suggest this could account for the difference.

 Similarly, there are noticeable differences in walking endurance between people with MS and controls,

 and this has not previously been identified as a covariate.

The present study is a secondary analysis of data combined from 3 separate studies measuring arterial stiffness using cfPWV in people with MS and control participants (

, presented in a PDF at the bottom of the online article with other supplemental materials).

 The large combined data set permitted further examination of differences between participants with MS and control participants in arterial stiffness, namely cfPWV, and whether other variables might account for the differences in arterial stiffness between the groups. We hypothesized a priori that arterial stiffness would be higher in people with MS than in control participants, even after accounting for other variables, including anxiety, depression, and walking endurance, as they have been associated with measures of arterial stiffness in control participants.

We conducted a secondary analysis of data combined from 3 previously published studies that included participants with MS and control participants.

 The procedures were approved by the University of Illinois Urbana-Champaign and the University of Illinois Chicago institutional review boards, and all participants provided written informed consent. The secondary analysis included 129 participants with MS and 51 controls without MS.

Age and sex were self-reported, and BMI was based on height and weight recorded from a stadiometer and scale. Disability status was based on the Expanded Disability Status Scale (EDSS) score generated from an examination performed by a Neurostatus-certified examiner (n = 98) and EDSS scores converted from Patient-Determined Disease Steps scale scores (n = 31).

 We further captured the disease course and duration based on self-report.

Vascular function was assessed via applanation tonometry using a high-fidelity strain gauge pressure transducer (SphygmoCor; ATCOR Medical). All participants rested in the supine position for 10 minutes before the assessment. Aortic stiffness was assessed using the gold-standard procedure, cfPWV. Arterial stiffness was calculated from the time delay between pressure waves measured at the common carotid artery to the femoral artery and the distance between the carotid and femoral arteries. Radial artery pressure waveforms were collected through a noninvasive blood pressure measurement and applanation tonometry (SphygmoCor). A generalized transfer function was applied to calculate central pressure waveforms such as central systolic blood pressure (cSBP), central diastolic blood pressure (cDBP), and MAP.

 These variables, particularly MAP, are essential as pressure strongly influences arterial stiffness.

The 6-Minute Walk Test (6MWT) measured aerobic or walking endurance and was performed in an accessible hallway with 4 corridors that allowed participants to walk without any obstacles or restrictions. Participants walked as far and as fast as possible within the limits of safety and stability for 6 minutes,

 and we permitted the use of an assistive device if needed. The 6MWT distance was measured in feet (6MWD).

Anxiety and depression symptoms were measured by the Hospital Anxiety and Depression Scale (HADS).

 The HADS questionnaire has 14 items, 7 aligning with anxiety (HADS-A) and 7 with depression (HADS-D), and each item was rated on a scale of 0 (most of the time) to 3 (not at all). The negatively worded items were reverse-scored, and the scores from the 7 items were summed into a composite score of anxiety and depression subscales over the previous 4-week period. Scores range from 0 to 21, with higher scores suggesting a greater occurrence of anxiety and depression symptoms.

Data analyses were performed using IBM SPSS Statistics version 28.0. Descriptive statistics are provided as mean (SD), median (IQR), or frequency (%), based on the measurement properties per outcome. We compared samples on demographic variables using independent-samples 

 tests. We performed independent-samples 

 tests on measurements of vascular function, 6MWD, and summary scores of anxiety and depression; the magnitude of differences was expressed as Cohen 

, with guidelines of 0.2, 0.5, and greater than 0.8 as small, moderate, and large differences, respectively. We examined associations among vascular function and other variables using bivariate Pearson correlations for identifying possible covariates. We did a regression analysis examining whether vascular function differed between groups even after controlling for covariates using a stepwise entry of variables (ie, group in step 1 and covariates in subsequent steps). We selected variables that either differed between groups or had bivariate correlations with cfPWV. Significance for all analyses was set at 

Study participant demographic and clinical characteristics are provided in 

. There were no significant differences in age, sex, or BMI between groups. Participants with MS largely had a relapsing-remitting course with moderate disease duration and level of disability and had not experienced a relapse within the previous 30 days.

Demographic and Clinical Characteristics of the Sample

 tests for vascular parameters, HADS subscale scores, and 6MWD are presented in 

. There were statistically significant differences between MS and control participants in cfPWV (

 = 1.618). There were no significant differences between groups in cSBP, cDBP, or MAP.

 Between-Group Comparison of Vascular Function, Anxiety, Depression, and 6-Minute Walk Distance

There were statistically significant correlations between cfPWV with age (

), cfPWV was higher in those who were older and had a higher BMI and MAP but was lower in those with greater walking endurance in the overall sample of participants with MS and control participants.

Significant Bivariate Correlations Among cfPWV and Age, BMI, MAP, and 6MWD

 presents the regression analysis examining whether group differences in cfPWV were accounted for by HADS-A, HADS-D, age, BMI, MAP, or 6MWD. The inclusion of group in step 1 explained 2.8% of the variance in cfPWV, and the effect of group was statistically significant (

 < .05). Group remained a statistically significant predictor of cfPWV even when age, BMI, MAP, and HADS-A entered the regression in steps 2 through 5.

Regression Analysis of Vascular Function Between Groups After Controlling for Covariates

Participants with MS had higher cfPWV and worse anxiety and depression symptoms and shorter 6MWD than control participants in this large, combined data set. We further demonstrated that the differences in cfPWV between groups were not influenced by age, BMI, MAP, 6MWD, and anxiety or depressive symptoms. These findings align with other research using smaller samples that demonstrated higher cfPWV in people with MS than in control participants but without substantial control for covariates.

 This overall difference in arterial stiffness aligns with vascular dysfunction and might be an early precursor of vascular comorbidities in MS. Arterial stiffness is a strong predictor of cardiovascular disease and overall mortality in the general population,

 and our results and prior research demonstrate increased arterial stiffness in MS, which could indicate an increased risk in cardiovascular disease and even death for people with MS.

Some researchers have examined possible covariates of the difference in arterial stiffness between participants with MS and control participants. For example, findings from one study reported that people with MS engaged in lower amounts of physical activity than controls, and those lower physical activity levels accounted for the difference in arterial stiffness between the 2 groups.

 Results from another study found that aerobic capacity is lower in people with MS than in control participants, but it did not account for the difference in cfPWV between the groups.

 Our study findings report that age, BMI, MAP, anxiety, depression, and 6MWD do not account for the difference in cfPWV between participants with MS and control participants. Collectively, these results underscore the established difference in arterial stiffness between participants with MS and control participants and imply that blood pressure does not contribute to the difference in cfPWV, despite the significant role that it has on stiffness. To date, we have not solidified the core reasons for the differences in vascular function; however, these results contribute to the current literature by identifying factors that do not account for the differences between participants with and without MS.

Our study does have limitations. The studies we combined were not all designed a priori to compare vascular function between people with MS and control participants. A major limitation of our analysis was that there were no comorbidities or related medications in these studies. Also, not including other measurements of vascular function, such as ankle-brachial index and pulse volume recording, is a limitation, as these measures could help aid in the understanding of increased cfPWV in people with MS. On average, participants in this secondary analysis did not meet the usually accepted cutoff subscale scores for elevated anxiety and depression on the HADS questionnaire. This indicates they were not experiencing clinically elevated anxiety or depressive symptoms; this is a limiting factor, as these symptoms are covariates in our analysis. In addition, we cannot conclude whether people were being treated for anxiety or depression with medication or other therapeutic mechanisms, as this information was not initially collected. The sample of people with MS recruited for the original studies primarily had a relapsing-remitting clinical course and a low average EDSS score, which may limit the generalizability of these results. Disease course and duration were self-reported, and this also represents a limitation based on possible inaccuracy in reporting.

Our results might highlight measuring markers of vascular function throughout the arterial tree, in addition to including measurements such as ankle-brachial index and flow-mediated dilation, as directions for future research in MS. Including measurements of potential mechanisms for vascular dysfunction, such as autonomic function and biomarkers (eg, cytokines, C-reactive protein), would be important as well, as these outcomes are generally consequences of MS. Levels of physical activity in combination with arterial stiffness could be considered, as there have been prior data to confirm this association in MS. Future studies should include subpopulations of people with MS who have other comorbid conditions (ie, those with hypertension, diabetes, and anxiety or depression disorders) when examining arterial stiffness. Finally, a medication history would be beneficial when considering data in these subpopulations. Such endeavors will further our understanding of vascular dysfunction in MS and perhaps its sources and influences for future intervention.

Findings from this study demonstrate that people with MS had higher arterial stiffness compared with control participants and that this difference was not explained by age, BMI, MAP, anxiety and depression symptoms, or walking endurance. These results further suggest that arterial stiffness may be associated with etiology and progression of MS and not factors such as anxiety, depression, MAP, or 6MWD.

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Volume 28, Issue 4

Pilot Study of Smartphone-Based Neuroperformance Tests in Multiple Sclerosis

Arterial Stiffness Is Higher in People With Multiple Sclerosis Than in Control Group