Background: Older adults with multiple sclerosis (MS) experience mobility impairments, but conventional brain imaging is a poor predictor of walking abilities in this population.
Objective: To test whether brain metabolites measured with Magnetic Resonance Spectroscopy (MRS) are associated with walking performance in older adults with MS.
Methods: Fifteen older adults with MS (mean age: 60.9, SD: 5.1) and 22 age-matched healthy controls (mean age: 64.2, SD: 5.7) underwent whole-brain MRS and mobility testing. Levels of N-acetylaspartate (NAA), myo-inositol (MI), choline (CHO), and temperature in 47 brain regions were compared between groups and correlated with walking speed (Timed 25 Foot Walk) and walking endurance (Six-Minute Walk).
Results: Older adults with MS had higher MI in 23 areas, including the bilateral frontal (right: t (21.449) = -2.605, P = .016; left: t (35) = -2.434, P = .020), temporal (right: t (35) = -3.063, P = .004; left: t (35) = -3.026, P = .005), and parietal lobes (right: t (21.100) = -2.886, P = .009; left: t (35) = -2.507, P = .017), and right thalamus (t (35) = -2.840, P = .007). MI in eleven regions correlated with walking speed, and MI in twelve regions correlated with walking endurance. NAA was lower in MS in the bilateral thalami (right: t (35) = 3.449, P < .001; left: t (35) = 2.061, P = .047), caudate nuclei (right: t (33) = 2.828, P = .008; left: t (32) = 2.132, P = .041), and posterior cingulum (right: t (35) = 3.077, P = .004; left: t (35) = 2.972, P = .005). NAA in four regions correlated with walking speed and endurance. Brain temperature was higher in MS patients in four regions, but did not correlate with mobility measures. There were no group differences in CHO.
Conclusion: MI and NAA may be useful imaging end-points for walking ability as a clinical outcome in older adults with MS.
Background: The integration of oxygen cost into the accelerometer's algorithms improves accuracy of total energy expenditure (TEE) values as post-stroke individuals walk. Recent work has shown that oxygen cost can be estimated from specific prediction equations for stroke patients.
Objective: The objective is to the validity of the different oxygen cost estimation equations available in the literature for calculating TEE using ActigraphGT3x as individuals with stroke sequelae walk.
Method: Individuals with stroke sequelae who were able to walk without human assistance were included. The TEE was calculated by multiplying the walking distance provided by an ActigraphGT3x worn on the healthy ankle and the patient's oxygen cost estimated from the selected prediction equations. The TEE values from each equation were compared to the TEE values measured by indirect calorimetry. The validity of the prediction methods was evaluated by Bland-Altman analysis (mean bias (MB) and limits of agreement (LoA) values).
Results: We included 26 stroke patients (63.5 years). Among the selected equations, those of Compagnat and Polese obtained the best validity parameters for the ActigraphGT3x: MBCompagnat = 1.2 kcal, 95% LoACompagnat = [-12.0; 14.3] kcal and MBPolese = 3.5 kcal, 95% LoAPolese = [-9.2; 16.1] kcal. For comparison, the estimated TEE value according to the manufacturer's algorithm reported MBManufacturer = -15 kcal, 95% LoAManufacturer = [-52.9; 22.8] kcal.
Conclusion: The Polese and Compagnat equations offer the best validity parameters in comparison with the criterion method. Using oxygen cost prediction equations is a promising approach to improving assessment of TEE by accelerometers in post-stroke individuals.
Background: New therapeutic approaches in neurological disorders are progressing into clinical development. Past failures in translational research have underlined the critical importance of selecting appropriate inclusion criteria and primary outcomes. Narrow inclusion criteria provide sensitivity, but increase trial duration and cost to the point of infeasibility, while broader requirements amplify confounding, increasing the risk of trial failure. This dilemma is perhaps most pronounced in spinal cord injury (SCI), but applies to all neurological disorders with low frequency and/or heterogeneous clinical manifestations.
Objective: Stratification of homogeneous patient cohorts to enable the design of clinical trials with broad inclusion criteria.
Methods: Prospectively-gathered data from patients with acute cervical SCI were analysed using an unbiased recursive partitioning conditional inference tree (URP-CTREE) approach. Performance in the 6-minute walk test at 6 months after injury was classified based on standardized neurological assessments within the first 15 days of injury. Functional and neurological outcomes were tracked throughout rehabilitation up to 6 months after injury.
Results: URP-CTREE identified homogeneous outcome cohorts in a study group of 309 SCI patients. These cohorts were validated by an internal, yet independent, validation group of 172 patients. The study group cohorts identified demonstrated distinct recovery profiles throughout rehabilitation. The baseline characteristics of the analysed groups were compared to a reference group of 477 patients.
Conclusion: URP-CTREE enables inclusive trial design by revealing the distribution of outcome cohorts, discerning distinct recovery profiles and projecting potential patient enrolment by providing estimates of the relative frequencies of cohorts to improve the design of clinical trials in SCI and beyond.
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