Methodological heterogeneity biases physical activity metrics derived from the Actigraph GT3X in multiple sclerosis: A rapid review and comparative study

From wearable sensor data to digital biomarker development: ten lessons learned and a framework proposal

Wearable sensor technologies are becoming increasingly relevant in health research, particularly in the context of chronic disease management. They generate real-time health data that can be translated into digital biomarkers, which can provide insights into our health and well-being. Scientific methods to collect, interpret, analyze, and translate health data from wearables to digital biomarkers vary, and systematic approaches to guide these processes are currently lacking. This paper is based on an observational, longitudinal cohort study, BarKA-MS, which collected wearable sensor data on the physical rehabilitation of people living with multiple sclerosis (MS). Based on our experience with BarKA-MS, we provide and discuss ten lessons we learned in relation to digital biomarker development across key study phases. We then summarize these lessons into a guiding framework (DACIA) that aims to informs the use of wearable sensor data for digital biomarker development and chronic disease management for future research and teaching.

Comparison of patient-reported outcomes of physical activity and accelerometry in people with multiple sclerosis and ambulatory impairment: A cross-sectional study

BACKGROUND

Accelerometers and patient-reported outcomes (PRO) are used to assess physical activity (PA) in people with multiple sclerosis (pwMS). So far it is unknown, however, whether these assessments represent mobility limitations in pwMS with mild and moderate to severe disability alike. The primary aim of the study was to assess the correlation between accelerometry and International Physical Activity Questionnaire (IPAQ) scores in pwMS with different degrees of ambulatory impairment. Taken its frequent use into account, the Godin Leisure Time Exercise Questionnaire (GLTEQ) was investigated as additional PRO.

METHODS

In a prospective cohort of pwMS, correlational analyses were performed between the number of daily steps, time spent in light, moderate to vigorous PA (MVPA) and time spent sitting as assessed using accelerometry (ActiGraph®-GT3X), and the respective IPAQ and GLTEQ scores. Additionally, associations of PA with disease-specific characteristics, aerobic capacity (VO2peak), walking assessments (Timed 25-Foot Walk, T25FW; 2-Minute Walk Test, 2MWT) and walking perception (Multiple Sclerosis Walking Scale-12; MSWS-12) were explored. Patient subgroups with mild (Expanded Disability Status Scale; EDSS score <4.0) and moderate to severe disability (EDSS ≥4.0) were analysed for the impact of ambulatory impairment on PA. Multiple linear regression was used to determine predictors of PA.

RESULTS

A total of 56 pwMS completed the study, with a mean (standard deviation, SD) age of 48.4 (10.3) years, disease duration of 14.8 (9.6) years and median (interquartile range) EDSS score of 3.5 (2.0 - 4.4). Moderate to weak correlations were found between daily step count and IPAQ total metabolic equivalent (MET) minutes/week (p < 0.001; r = 0.506), MVPA MET-minutes/week (p < 0.01; r = 0.479) and walking MET-minutes/week (p < 0.05; r = 0.372) in the total cohort. Time spent sitting was inversely correlated with total MET-minutes/week and MVPA MET-minutes/week (p < 0.05; r = -0.358 and r = -0.365). Subgroup analysis revealed, that daily step count was significantly correlated with total MET-minutes/week, MVPA MET-minutes/week and walking MET-minutes/week (p < 0.01, r = 0.569; p < 0.01, r = 0.531 and p < 0.05, r = 0.480, respectively) in the "mild disability" subgroup only, whereas time spent sitting was inversely correlated with total MET-minutes/week (p < 0.05; r = -0.582) in the "moderate to severe disability" subgroup. There was no association between objectively assessed PA and GLTEQ scores in any group. In the total cohort, moderate to weak correlations were found between daily step count and walking assessments (T25FW: p < 0.01, ρ = -0.508; 2MWT: p < 0.01, ρ=0.463) and MSWS-12 (p < 0.001; ρ = -0.609). Moderate to weak correlations were also observed between VO2peak and walking assessments (T25FW: p < 0.01; ρ = -0.516; 2MWT: p < 0.01, ρ=0.480). Multiple linear regression analysis identified disability and VO2peak as predictors of PA (p = 0.045; β=0.25 and p < 0.001; β=0.49).

CONCLUSION

Significant associations of objective PA measurements using accelerometry with IPAQ were found only in pwMS with "mild disability". In pwMS with "moderate to severe disability", IPAQ did not reflect the objectively assessed amount of PA. In our cohort, GLTEQ showed no association with objectively assessed PA. Thus, an MS-specific self-reported questionnaire for assessing PA is warranted.

A low-fat diet improves fatigue in multiple sclerosis: Results from a randomized controlled trial

BACKGROUND

Fatigue can be a disabling multiple sclerosis (MS) symptom with no effective treatment options.

OBJECTIVE

Determine whether a low-fat diet improves fatigue in people with MS (PwMS).

METHODS

We conducted a 16-week randomized controlled trial (RCT) and allocated PwMS to a low-fat diet (active, total daily fat calories not exceeding 20%) or wait-list (control) group. Subjects underwent 2 weeks of baseline diet data collection (24-hour diet recalls (24HDRs)), followed by randomization. The active group received 2 weeks of nutrition counseling and underwent a 12-week low-fat diet intervention. One set of three 24HDRs at baseline and week 16 were collected. We administered a food frequency questionnaire (FFQ) and Modified Fatigue Impact Scale (MFIS) every 4 weeks. The control group continued their pre-study diet and received diet training during the study completion.

RESULTS

We recruited 39 PwMS (20-active; 19-control). The active group decreased their daily caloric intake by 11% (95% confidence interval (CI): -18.5%, -3.0%) and the mean MFIS by 4.0 (95% CI: -12.0, 4.0) compared to the control (intent-to-treat). Sensitivity analysis strengthened the association with a mean MFIS difference of -13.9 (95% CI: -20.7, -7.2).

CONCLUSIONS

We demonstrated a significant reduction in fatigue with a low-fat dietary intervention in PwMS.

Feasibility and scalability of a fitness tracker study: Results from a longitudinal analysis of persons with multiple sclerosis

Background

Consumer-grade fitness trackers offer exciting opportunities to study persons with chronic diseases in greater detail and in their daily-life environment. However, attempts to bring fitness tracker measurement campaigns from tightly controlled clinical environments to home settings are often challenged by deteriorating study compliance or by organizational and resource limitations.

Objectives

By revisiting the study design and patient-reported experiences of a partly remote study with fitness trackers (BarKA-MS study), we aimed to qualitatively explore the relationship between overall study compliance and scalability. On that account, we aimed to derive lessons learned on strengths, weaknesses, and technical challenges for the conduct of future studies.

Methods

The two-phased BarKA-MS study employed Fitbit Inspire HR and electronic surveys to monitor physical activity in 45 people with multiple sclerosis in a rehabilitation setting and in their natural surroundings at home for up to 8 weeks. We examined and quantified the recruitment and compliance in terms of questionnaire completion and device wear time. Furthermore, we qualitatively evaluated experiences with devices according to participants' survey-collected reports. Finally, we reviewed the BarKA-MS study conduct characteristics for its scalability according to the Intervention Scalability Assessment Tool checklist.

Results

Weekly electronic surveys completion reached 96%. On average, the Fitbit data revealed 99% and 97% valid wear days at the rehabilitation clinic and in the home setting, respectively. Positive experiences with the device were predominant: only 17% of the feedbacks had a negative connotation, mostly pertaining to perceived measurement inaccuracies. Twenty-five major topics and study characteristics relating to compliance were identified. They broadly fell into the three categories: "effectiveness of support measures", "recruitment and compliance barriers", and "technical challenges". The scalability assessment revealed that the highly individualized support measures, which contributed greatly to the high study compliance, may face substantial scalability challenges due to the strong human involvement and limited potential for standardization.

Conclusion

The personal interactions and highly individualized participant support positively influenced study compliance and retention. But the major human involvement in these support actions will pose scalability challenges due to resource limitations. Study conductors should anticipate this potential compliance-scalability trade-off already in the design phase.