Minimal clinically important difference of modified dynamic gait index in people with neurological disorders

Corrini, Chiara; Torchio, Alessandro; Anastasi, Denise; Parelli, Riccardo; Meotti, Matteo; Spedicato, Albino; Groppo, Elisabetta; d’Arma, Alessia; Grosso, Cristina; Montesano, Angelo; Cattaneo, Davide; Gervasoni, Elisa

doi:10.1016/j.gaitpost.2021.08.024

Cited by 6 publications

(4 citation statements)

References 28 publications

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“…Thus, many dynamic balance assessment tools have been developed, including clinical scales 5 , quantitative gait markers 6 , posturography 7 , fall prevention protocols 8 and single- and dual-task tests 9 . Regarding clinical scales, the Berg balance scale 10 , the MiniBESTest 10 , the timed up and go (TUG) 11 , and the modified dynamic gait index (mDGI) 12 , 13 are among the most commonly used in clinical practice to measure balance in PwND. Compared to the Berg scale, which does not assess dynamic balance during locomotion, and the TUG and MiniBESTest, which evaluate this aspect in a few functional tasks (i.e., one task in TUG and five tasks in MiniBESTest), the mDGI is specifically devoted to measuring an individual’s capacity to maintain their balance and adapt their gait in the presence of various environmental demands, essential to perform daily-life locomotor activities without falling.…”

Section: Introductionmentioning

confidence: 99%

“…The highest possible score on the mDGI is 64 points. The mDGI has been extensively validated in subjects with mobility impairments 14 , 15 and in different pathological cohorts such as stroke (ST), vestibular dysfunction, multiple sclerosis (MS), traumatic brain injuries, and Parkinson’s disease (PD) 12 , 13 . Recently, Torchio et al provided cut-off values to identify PwND with no or minimal risk of falls (mDGI score ) and PwND with high risk of falls (mDGI score ) 16 .…”

Section: Introductionmentioning

confidence: 99%

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Machine learning based estimation of dynamic balance and gait adaptability in persons with neurological diseases using inertial sensors

Liuzzi

Carpinella

Anastasi

et al. 2023

Sci Rep

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Poor dynamic balance and impaired gait adaptation to different contexts are hallmarks of people with neurological disorders (PwND), leading to difficulties in daily life and increased fall risk. Frequent assessment of dynamic balance and gait adaptability is therefore essential for monitoring the evolution of these impairments and/or the long-term effects of rehabilitation. The modified dynamic gait index (mDGI) is a validated clinical test specifically devoted to evaluating gait facets in clinical settings under a physiotherapist’s supervision. The need of a clinical environment, consequently, limits the number of assessments. Wearable sensors are increasingly used to measure balance and locomotion in real-world contexts and may permit an increase in monitoring frequency. This study aims to provide a preliminary test of this opportunity by using nested cross-validated machine learning regressors to predict the mDGI scores of 95 PwND via inertial signals collected from short steady-state walking bouts derived from the 6-minute walk test. Four different models were compared, one for each pathology (multiple sclerosis, Parkinson’s disease, and stroke) and one for the pooled multipathological cohort. Model explanations were computed on the best-performing solution; the model trained on the multipathological cohort yielded a median (interquartile range) absolute test error of 3.58 (5.38) points. In total, 76% of the predictions were within the mDGI’s minimal detectable change of 5 points. These results confirm that steady-state walking measurements provide information about dynamic balance and gait adaptability and can help clinicians identify important features to improve upon during rehabilitation. Future developments will include training of the method using short steady-state walking bouts in real-world settings, analysing the feasibility of this solution to intensify performance monitoring, providing prompt detection of worsening/improvements, and complementing clinical assessments.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Machine learning based estimation of dynamic balance and gait adaptability in persons with neurological diseases using inertial sensors

Liuzzi

Carpinella

Anastasi

et al. 2023

Sci Rep

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“…It is important to highlight that the PT group nearly reached a medium effect size and showed a minimal clinically important difference for the ABC scores (10.5%) for patient perceptions about their functional balance ability. A minimal clinically important difference of 10% for the ABC scores has been suggested for outpatients with neurological conditions (e.g., Parkinson’s disease, multiple sclerosis, and stroke) [ 30 ]. Our results suggest that a larger sample size would be needed to reach statistical significance despite the minimal clinical improvement of 10.5% on the ABC scores after the PT program.…”

Section: Discussionmentioning

confidence: 99%

Mobility Rehab visual feedback system for gait rehabilitation in older adults

Silva-Batista,

Harker,

Vitorio

et al. 2023

J NeuroEngineering Rehabil

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Background Gait and balance impairments are among the main causes of falls in older adults. The feasibility and effectiveness of adding sensor-based feedback to physical therapy (PT) in an outpatient PT setting is unknown. We evaluated the feasibility and effectiveness of PT intervention combined with a therapist-assisted visual feedback system, called Mobility Rehab, (PT + MR) in older adults. Methods Twenty-eight older adults with and without neurological diseases were assigned either PT + MR (n = 22) or PT alone (n = 6). Both groups performed 8 sessions (individualized) of 45 min long (30 min for gait training and 15 min for endurance, strength, and balance exercises) in an outpatient clinic. Mobility Rehab uses unobtrusive, inertial sensors on both wrists and feet, and at the sternum level with real-time algorithms to provide real-time feedback on five gait metrics (step duration, stride length, elevation at mid-swing, arm swing range-of-motion [ROM], and trunk coronal ROM), which are displayed on a tablet. The primary outcome was the Activities-specific Balance Confidence scale (ABC). The secondary outcome was gait speed measured with wearable inertial sensors during 2 min of walking. Results There were no between-group differences at baseline for any variable (P > 0.05). Neither PT + MR nor PT alone showed significant changes on the ABC scores. PT + MR, but not PT alone, showed significant improvements in gait speed and arm swing ROM. The system was evaluated as ‘easy to use’ by the PT. Conclusions Our preliminary results show that PT + MR improves gait speed in older adults with and without neurological diseases in an outpatient clinic. Clinical Trial Registration www.ClinicalTrials.gov, identifier: NCT03869879.

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“…Change in modified Dynamic Gait Index (mDGI): The modified Dynamic Gait Index is a clinical outcome measure to assess the ability to modify and adapt gait and balance during complex walking tasks. Higher scores indicate better performances [32].…”

Section: Upper-limb Functionmentioning

confidence: 99%

Classification and Quantification of Physical Therapy Interventions across Multiple Neurological Disorders: An Italian Multicenter Network

Bowman,

Mestanza Mattos,

Salvalaggio

et al. 2023

JCM

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Despite their relevance in neurorehabilitation, physical therapy (PT) goals and interventions are poorly described, compromising a proper understanding of PT effectiveness in everyday clinical practice. Thus, this paper aims to describe the prevalence of PT goals and interventions in people with neurological disorders, along with the participants’ clinical features, setting characteristics of the clinical units involved, and PT impact on outcome measures. A multicenter longitudinal observational study involving hospitals and rehabilitation centers across Italy has been conducted. We recruited people with stroke (n = 119), multiple sclerosis (n = 48), and Parkinson’s disease (n = 35) who underwent the PT sessions foreseen by the National Healthcare System. Clinical outcomes were administered before and after the intervention, and for each participant the physical therapists completed a semi-structured interview to report the goals and interventions of the PT sessions. Results showed that the most relevant PT goals were related to the ICF activities with “walking” showing the highest prevalence. The most used interventions aimed at improving walking performance, followed by those aimed at improving organ/body system functioning, while interventions targeting the cognitive–affective and educational aspects have been poorly considered. Considering PT effectiveness, 83 participants experienced a clinically significant improvement in the outcome measures assessing gait and balance functions.

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Minimal clinically important difference of modified dynamic gait index in people with neurological disorders

Cited by 6 publications

References 28 publications

Machine learning based estimation of dynamic balance and gait adaptability in persons with neurological diseases using inertial sensors

Machine learning based estimation of dynamic balance and gait adaptability in persons with neurological diseases using inertial sensors

Mobility Rehab visual feedback system for gait rehabilitation in older adults

Classification and Quantification of Physical Therapy Interventions across Multiple Neurological Disorders: An Italian Multicenter Network

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