The Dresden Protocol for Multidimensional Walking Assessment (DMWA) in Clinical Practice

Trentzsch, Katrin; Weidemann, Marie Luise; Torp, Charlotte; Inojosa, Hernán; Scholz, Maria Brígida dos Santos; Haase, Rocco; Schriefer, Dirk; Akgün, Katja; Ziemssen, Tjalf

doi:10.3389/fnins.2020.582046

Cited by 16 publications

(25 citation statements)

References 104 publications

(146 reference statements)

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“…Subjects were tested with GAITRite (CIR-Systems Inc., Franklin, NJ, USA) according to the Dresden Protocol for Multidimensional Gait Assessment (DMWA) [33]. The GAITRite was investigated in numerous studies and has demonstrated high reliability and validity [34][35][36].…”

Section: Methodsmentioning

confidence: 99%

“…Selected gait parameters for people with MS and healthy controls (N = 60). Key parameters used in clinical routine according our DMWA protocol[33]; MS = multiple sclerosis; HC = healthy controls; EMIQ = Early Mobility Impairment Questionnaire; MSWS = Multiple Sclerosis Walking Scale; GCT = Gait Cycle Time; L = left; R = right; standard deviation = SD; data in mean ± SD; ( )-dimensionless values; p-value via Mann-Whitney U-Test for differences between groups.…”

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confidence: 99%

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Using Machine Learning Algorithms for Identifying Gait Parameters Suitable to Evaluate Subtle Changes in Gait in People with Multiple Sclerosis

et al. 2021

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In multiple sclerosis (MS), gait impairment is one of the most prominent symptoms. For a sensitive assessment of pathological gait patterns, a comprehensive analysis and processing of several gait analysis systems is necessary. The objective of this work was to determine the best diagnostic gait system (DIERS pedogait, GAITRite system, and Mobility Lab) using six machine learning algorithms for the differentiation between people with multiple sclerosis (pwMS) and healthy controls, between pwMS with and without fatigue and between pwMS with mild and moderate impairment. The data of the three gait systems were assessed on 54 pwMS and 38 healthy controls. Gaussian Naive Bayes, Decision Tree, k-Nearest Neighbor, and Support Vector Machines (SVM) with linear, radial basis function (rbf) and polynomial kernel were applied for the detection of subtle walking changes. The best performance for a healthy-sick classification was achieved on the DIERS data with a SVM rbf kernel (k = 0.49 ± 0.11). For differentiating between pwMS with mild and moderate disability, the GAITRite data with the SVM linear kernel (k = 0.61 ± 0.06) showed the best performance. This study demonstrates that machine learning methods are suitable for identifying pathologic gait patterns in early MS.

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Section: Methodsmentioning

confidence: 99%

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confidence: 99%

Using Machine Learning Algorithms for Identifying Gait Parameters Suitable to Evaluate Subtle Changes in Gait in People with Multiple Sclerosis

et al. 2021

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“…In recent years, the Expanded Disease Disability Scale (EDSS) has been an essential, irreplaceable scale in MS which has been improved in the past years by different approaches (127)(128)(129). However, other additional clinical instruments have been introduced to quantitate the different multidimensional aspects of MS as fatigue, cognition or walking function (130,131). The Multiple Sclerosis Functional Composite (MSFC) provides a functional assessment of different key functions (upper and lower extremities, cognition) that is used more and more frequently in MS and has been proven to be highly sensitive in the evaluation of very important clinical trials.…”

Section: Patients Physiological Status Datamentioning

confidence: 99%

“…The Multiple Sclerosis Performance Test (MSPT) is a digital adaptation of the MSFC with additional elements added ( 160 , 161 ) and measures health status via iPad with questionnaire on health status, processing speed with Processing Speed Test (PST) ( 162 ), manual skills with 9-Hole-Peg-Test (9-HPT) and walking speed with Timed 25-Foot-Walk (T25-FW) ( 160 ). Multidimensional gait analysis can be performed with measurement of walking speed (T25-FW), measurement of endurance [2-Minute Walk Test, 2MWT ( 163 , 164 )] and measurement of balance and gait quality on a sensor-based walking mat (GAITRite ® -System, Mobility Lab-System) ( 131 ). For the digital measurement of data in patient-specific everyday life (at home) there are various patient apps such as Floodlight, diverse fitness tracker and health apps available ( 165 , 166 ).…”

Section: Concept Of Digital Twins In the Management Of Multiple Sclerosismentioning

confidence: 99%

“…Thanks to the visualized simulation of the DT, the HCP has time to address all patients’ questions and concerns in detail. Examples of existing dashboards for displaying individual patient data at a glance include the walking assessment dashboard as part of the multidimensional digital patient management system MSDS 3D ( 201 , 202 ), showing the results of clinical multidimensional walking assessment and daily smart monitoring longitudinally ( 131 ), and the MS BioScreen, that integrates multiple dimensions of disease information: clinical evolution, therapeutic interventions, brain, eye, and spinal cord imaging, environmental exposures, genomics, and biomarker data ( 56 , 203 ).…”

Section: Use Cases In Care Of Multiple Sclerosismentioning

confidence: 99%

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Digital Twins for Multiple Sclerosis

et al. 2021

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An individualized innovative disease management is of great importance for people with multiple sclerosis (pwMS) to cope with the complexity of this chronic, multidimensional disease. However, an individual state of the art strategy, with precise adjustment to the patient’s characteristics, is still far from being part of the everyday care of pwMS. The development of digital twins could decisively advance the necessary implementation of an individualized innovative management of MS. Through artificial intelligence-based analysis of several disease parameters – including clinical and para-clinical outcomes, multi-omics, biomarkers, patient-related data, information about the patient’s life circumstances and plans, and medical procedures – a digital twin paired to the patient’s characteristic can be created, enabling healthcare professionals to handle large amounts of patient data. This can contribute to a more personalized and effective care by integrating data from multiple sources in a standardized manner, implementing individualized clinical pathways, supporting physician-patient communication and facilitating a shared decision-making. With a clear display of pre-analyzed patient data on a dashboard, patient participation and individualized clinical decisions as well as the prediction of disease progression and treatment simulation could become possible. In this review, we focus on the advantages, challenges and practical aspects of digital twins in the management of MS. We discuss the use of digital twins for MS as a revolutionary tool to improve diagnosis, monitoring and therapy refining patients’ well-being, saving economic costs, and enabling prevention of disease progression. Digital twins will help make precision medicine and patient-centered care a reality in everyday life.

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Neurological complications in oncology and their monitoring and management in clinical practice: a narrative review

Fischer,

von Bonin,

Bornhäuser

et al. 2024

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Importance New anti-tumor treatments, such as immune checkpoint inhibitors and CAR T-cell therapy, are associated with an increasing number of neurological issues linked to tumors not arising from nervous system such as neurological and neuropsychological side effects that can significantly impair quality of life in the short or long term. The science of pathomechanisms, therapeutic approaches, and preventive measures is still in its early stages, and the progress is hampered by the lack of studied connection between neurological and oncological disciplines. Objectives This work aimed to provide an overview of the questions raised in the field of clinical neuroscience that concern the outcomes of oncological diseases and their treatment. Furthermore, we give an outline of how a collaborative approach between neurology and oncology, with the implementation of neuroscience techniques including up-to-date diagnostics and therapy, can help to improve the quality of oncological patients’ lives. Evidence review The covered areas of investigation in the evaluated articles primarily encompassed the review of known neurological complications of oncological diseases caused by neurotoxic mechanisms of performed therapies or those linked to concurrent pathological conditions. Similarly, the methods of their diagnostics were assessed. Findings Our literature review of 65 articles, including clinical trials, cohort studies, reviews, and theoretically based in vitro studies published between 1998 and 2023, outlines the broad spectrum of neurological complications primarily associated with malignant diseases and the anti-tumor therapies employed. Notably, immune-mediated complications, whose incidence is increasing due to the expanding use of new immunotherapies, require early detection and targeted treatment to prevent severe progression. In this context, neurological complications mediated by immune checkpoint inhibitors are often associated with significant impairments and high mortality, necessitating specialist consultation for early detection and differentiation from other phenotypically similar syndromes. Current data on the pathophysiology of these neurological complications are not reliable due to the limited number of studies. Moreover, there is a lack of evidence regarding the appropriate oncological approach in the event of therapy-related complications. Initial study results suggest that the establishment of interdisciplinary treatment interfaces for the management of oncology patients could improve the safety of these therapies and enhance the patients’ quality of life. Conclusions and relevance The accumulated knowledge on neurotoxicity caused by oncological diseases shows that the challenges in diagnosing and managing this condition are expanding in tandem with the growing array of therapies being employed. Therefore, it requires interdisciplinary approach with the introduction of new facilities enabling more personalized patient care.

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The Dresden Protocol for Multidimensional Walking Assessment (DMWA) in Clinical Practice

Cited by 16 publications

References 104 publications

Using Machine Learning Algorithms for Identifying Gait Parameters Suitable to Evaluate Subtle Changes in Gait in People with Multiple Sclerosis

Using Machine Learning Algorithms for Identifying Gait Parameters Suitable to Evaluate Subtle Changes in Gait in People with Multiple Sclerosis

Digital Twins for Multiple Sclerosis

Neurological complications in oncology and their monitoring and management in clinical practice: a narrative review

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