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      Remote monitoring of amyotrophic lateral sclerosis using wearable sensors detects differences in disease progression and survival: a prospective cohort study

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          Summary

          Background

          There is an urgent need for objective and sensitive measures to quantify clinical disease progression and gauge the response to treatment in clinical trials for amyotrophic lateral sclerosis (ALS). Here, we evaluate the ability of an accelerometer-derived outcome to detect differential clinical disease progression and assess its longitudinal associations with overall survival in patients with ALS.

          Methods

          Patients with ALS wore an accelerometer on the hip for 3–7 days, every 2–3 months during a multi-year observation period. An accelerometer-derived outcome, the Vertical Movement Index (VMI), was calculated, together with predicted disease progression rates, and jointly analysed with overall survival. The clinical utility of VMI was evaluated using comparisons to patient-reported functionality, while the impact of various monitoring schemes on empirical power was explored through simulations.

          Findings

          In total, 97 patients (70.1% male) wore the accelerometer for 1995 days, for a total of 27,701 h. The VMI was highly discriminatory for predicted disease progression rates, revealing faster rates of decline in patients with a worse predicted prognosis compared to those with a better predicted prognosis ( p < 0.0001). The VMI was strongly associated with the hazard for death (HR 0.20, 95% CI: 0.09–0.44, p < 0.0001), where a decrease of 0.19–0.41 unit was associated with reduced ambulatory status. Recommendations for future studies using accelerometery are provided.

          Interpretation

          The results serve as motivation to incorporate accelerometer-derived outcomes in clinical trials, which is essential for further validation of these markers to meaningful endpoints.

          Funding

          doi 10.13039/501100014076, Stichting ALS Nederland; (TRICALS-Reactive-II).

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          Most cited references49

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          El Escorial revisited: Revised criteria for the diagnosis of amyotrophic lateral sclerosis

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            Amyotrophic lateral sclerosis

            Amyotrophic lateral sclerosis is characterised by the progressive loss of motor neurons in the brain and spinal cord. This neurodegenerative syndrome shares pathobiological features with frontotemporal dementia and, indeed, many patients show features of both diseases. Many different genes and pathophysiological processes contribute to the disease, and it will be necessary to understand this heterogeneity to find effective treatments. In this Seminar, we discuss clinical and diagnostic approaches as well as scientific advances in the research fields of genetics, disease modelling, biomarkers, and therapeutic strategies.
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              Validation of accelerometer wear and nonwear time classification algorithm.

              the use of movement monitors (accelerometers) for measuring physical activity (PA) in intervention and population-based studies is becoming a standard methodology for the objective measurement of sedentary and active behaviors and for the validation of subjective PA self-reports. A vital step in PA measurement is the classification of daily time into accelerometer wear and nonwear intervals using its recordings (counts) and an accelerometer-specific algorithm. the purpose of this study was to validate and improve a commonly used algorithm for classifying accelerometer wear and nonwear time intervals using objective movement data obtained in the whole-room indirect calorimeter. we conducted a validation study of a wear or nonwear automatic algorithm using data obtained from 49 adults and 76 youth wearing accelerometers during a strictly monitored 24-h stay in a room calorimeter. The accelerometer wear and nonwear time classified by the algorithm was compared with actual wearing time. Potential improvements to the algorithm were examined using the minimum classification error as an optimization target. the recommended elements in the new algorithm are as follows: 1) zero-count threshold during a nonwear time interval, 2) 90-min time window for consecutive zero or nonzero counts, and 3) allowance of 2-min interval of nonzero counts with the upstream or downstream 30-min consecutive zero-count window for detection of artifactual movements. Compared with the true wearing status, improvements to the algorithm decreased nonwear time misclassification during the waking and the 24-h periods (all P values < 0.001). the accelerometer wear or nonwear time algorithm improvements may lead to more accurate estimation of time spent in sedentary and active behaviors.
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                Author and article information

                Contributors
                Journal
                eBioMedicine
                EBioMedicine
                eBioMedicine
                Elsevier
                2352-3964
                06 April 2024
                May 2024
                06 April 2024
                : 103
                : 105104
                Affiliations
                [a ]Department of Neurology, UMC Utrecht Brain Centre, University Medical Centre Utrecht, Utrecht, the Netherlands
                [b ]Biostatistics & Research Support, Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, the Netherlands
                Author notes
                []Corresponding author. Department of Neurology, UMC Utrecht Brain Centre, University Medical Centre Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, the Netherlands. r.p.a.vaneijk-2@ 123456umcutrecht.nl
                Article
                S2352-3964(24)00139-7 105104
                10.1016/j.ebiom.2024.105104
                11004066
                38582030
                18a0cc40-493b-40a8-a52f-9ee9bc9cd161
                © 2024 The Author(s)

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 13 December 2023
                : 20 March 2024
                : 20 March 2024
                Categories
                Articles

                amyotrophic lateral sclerosis,biomarkers,clinical trials,wearable sensors,remote monitoring

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