Sidney T. Baudendistel , Kerri S. Rawson , Christina N. Lessov-Schlaggar , Baijayanta Maiti , Paul T. Kotzbauer , Joel S. Perlmutter , Gammon M. Earhart , Meghan C. Campbell
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Multivariate analysis of variance identified differences in gait domains across clinical subtypes.</div></div><div><h3>Findings</h3><div>The “Motor Only” subtype exhibited the fastest velocity, longest step length, and least timing variability (swing, step, stance), compared to “Psychiatric & Motor” and “Cognitive & Motor” subtypes. Stance time differed across subtypes; “Psychiatric & Motor” subtype had the longest stance time, followed by “Cognitive & Motor”, then “Motor only”. The “Psychiatric & Motor” group had different asymmetry from the “Cognitive & Motor” subtype, as “Psychiatric & Motor” walked with longer steps on their less-affected side while the “Cognitive & Motor” subtype displayed the opposite pattern. No differences were observed for swing time, step velocity variability, step length variability, width measures, or other asymmetry measures.</div></div><div><h3>Interpretation</h3><div>Cognitive and Psychiatric subtypes displayed worse gait performance than the “Motor only” group. Stance time and step length asymmetry were different between Psychiatric and Cognitive subtypes, indicating gait deficits may be related to distinct aspects of non-motor manifestations. Gait signatures may help clinicians distinguish between non-motor subtypes, guiding personalized treatment.</div></div>","PeriodicalId":50992,"journal":{"name":"Clinical Biomechanics","volume":"122 ","pages":"Article 106445"},"PeriodicalIF":1.4000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Differential gait features across Parkinson's disease clinical subtypes\",\"authors\":\"Sidney T. Baudendistel , Kerri S. Rawson , Christina N. Lessov-Schlaggar , Baijayanta Maiti , Paul T. Kotzbauer , Joel S. Perlmutter , Gammon M. Earhart , Meghan C. Campbell\",\"doi\":\"10.1016/j.clinbiomech.2025.106445\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>Clinical subtypes in Parkinson's disease including non-motor manifestations may be more beneficial than subtypes based upon motor manifestations alone. Inclusion of gait metrics may help identity targets for rehabilitation and potentially predict development of non-motor symptoms for individuals with Parkinson's disease. This study aims to characterize gait differences across established multi-domain subtypes.</div></div><div><h3>Methods</h3><div>“Motor Only”, “Psychiatric & Motor” and “Cognitive & Motor” clinical subtypes were established through motor, cognitive, and psychiatric assessment. Walking was assessed in the “OFF” medication state. Multivariate analysis of variance identified differences in gait domains across clinical subtypes.</div></div><div><h3>Findings</h3><div>The “Motor Only” subtype exhibited the fastest velocity, longest step length, and least timing variability (swing, step, stance), compared to “Psychiatric & Motor” and “Cognitive & Motor” subtypes. Stance time differed across subtypes; “Psychiatric & Motor” subtype had the longest stance time, followed by “Cognitive & Motor”, then “Motor only”. The “Psychiatric & Motor” group had different asymmetry from the “Cognitive & Motor” subtype, as “Psychiatric & Motor” walked with longer steps on their less-affected side while the “Cognitive & Motor” subtype displayed the opposite pattern. No differences were observed for swing time, step velocity variability, step length variability, width measures, or other asymmetry measures.</div></div><div><h3>Interpretation</h3><div>Cognitive and Psychiatric subtypes displayed worse gait performance than the “Motor only” group. Stance time and step length asymmetry were different between Psychiatric and Cognitive subtypes, indicating gait deficits may be related to distinct aspects of non-motor manifestations. 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Differential gait features across Parkinson's disease clinical subtypes
Background
Clinical subtypes in Parkinson's disease including non-motor manifestations may be more beneficial than subtypes based upon motor manifestations alone. Inclusion of gait metrics may help identity targets for rehabilitation and potentially predict development of non-motor symptoms for individuals with Parkinson's disease. This study aims to characterize gait differences across established multi-domain subtypes.
Methods
“Motor Only”, “Psychiatric & Motor” and “Cognitive & Motor” clinical subtypes were established through motor, cognitive, and psychiatric assessment. Walking was assessed in the “OFF” medication state. Multivariate analysis of variance identified differences in gait domains across clinical subtypes.
Findings
The “Motor Only” subtype exhibited the fastest velocity, longest step length, and least timing variability (swing, step, stance), compared to “Psychiatric & Motor” and “Cognitive & Motor” subtypes. Stance time differed across subtypes; “Psychiatric & Motor” subtype had the longest stance time, followed by “Cognitive & Motor”, then “Motor only”. The “Psychiatric & Motor” group had different asymmetry from the “Cognitive & Motor” subtype, as “Psychiatric & Motor” walked with longer steps on their less-affected side while the “Cognitive & Motor” subtype displayed the opposite pattern. No differences were observed for swing time, step velocity variability, step length variability, width measures, or other asymmetry measures.
Interpretation
Cognitive and Psychiatric subtypes displayed worse gait performance than the “Motor only” group. Stance time and step length asymmetry were different between Psychiatric and Cognitive subtypes, indicating gait deficits may be related to distinct aspects of non-motor manifestations. Gait signatures may help clinicians distinguish between non-motor subtypes, guiding personalized treatment.
期刊介绍:
Clinical Biomechanics is an international multidisciplinary journal of biomechanics with a focus on medical and clinical applications of new knowledge in the field.
The science of biomechanics helps explain the causes of cell, tissue, organ and body system disorders, and supports clinicians in the diagnosis, prognosis and evaluation of treatment methods and technologies. Clinical Biomechanics aims to strengthen the links between laboratory and clinic by publishing cutting-edge biomechanics research which helps to explain the causes of injury and disease, and which provides evidence contributing to improved clinical management.
A rigorous peer review system is employed and every attempt is made to process and publish top-quality papers promptly.
Clinical Biomechanics explores all facets of body system, organ, tissue and cell biomechanics, with an emphasis on medical and clinical applications of the basic science aspects. The role of basic science is therefore recognized in a medical or clinical context. The readership of the journal closely reflects its multi-disciplinary contents, being a balance of scientists, engineers and clinicians.
The contents are in the form of research papers, brief reports, review papers and correspondence, whilst special interest issues and supplements are published from time to time.
Disciplines covered include biomechanics and mechanobiology at all scales, bioengineering and use of tissue engineering and biomaterials for clinical applications, biophysics, as well as biomechanical aspects of medical robotics, ergonomics, physical and occupational therapeutics and rehabilitation.