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      Literature Review and Comparison of Two Statistical Methods to Evaluate the Effect of Botulinum Toxin Treatment on Gait in Children with Cerebral Palsy

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          Abstract

          Aim

          This study aimed at comparing two statistical approaches to analyze the effect of Botulinum Toxin A (BTX-A) treatment on gait in children with a diagnosis of spastic cerebral palsy (CP), based on three-dimensional gait analysis (3DGA) data. Through a literature review, the available expert knowledge on gait changes after BTX-A treatment in children with CP is summarized.

          Methods

          Part 1—Intervention studies on BTX-A treatment in children with CP between 4–18 years that used 3DGA data as an outcome measure and were written in English, were identified through a broad systematic literature search. Reported kinematic and kinetic gait features were extracted from the identified studies. Part 2—A retrospective sample of 53 children with CP (6.1 ± 2.3years, GMFCS I-III) received 3DGA before and after multilevel BTX-A injections. The effect of BTX-A on gait was interpreted by comparing the results of paired samples t-tests on the kinematic gait features that were identified from literature to the results of statistical parametric mapping analysis on the kinematic waveforms of the lower limb joints.

          Results

          Part 1–53 kinematic and 33 kinetic features were described in literature. Overall, there is no consensus on which features should be evaluated after BTX-A treatment as 49 features were reported only once or twice. Part 2—Post-BTX-A, both statistical approaches found increased ankle dorsiflexion throughout the gait cycle. Statistical parametric mapping analyses additionally found increased knee extension during terminal stance. In turn, feature analyses found increased outtoeing during stance after BTX-A.

          Conclusion

          This study confirms that BTX-A injections are a valuable treatment option to improve gait function in children with CP. However, different statistical approaches may lead to different interpretations of treatment outcome. We suggest that a clear, definite hypothesis should be stated a priori and a commensurate statistical approach should accompany this hypothesis.

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          Most cited references33

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          One-dimensional statistical parametric mapping in Python.

          Statistical parametric mapping (SPM) is a topological methodology for detecting field changes in smooth n-dimensional continua. Many classes of biomechanical data are smooth and contained within discrete bounds and as such are well suited to SPM analyses. The current paper accompanies release of 'SPM1D', a free and open-source Python package for conducting SPM analyses on a set of registered 1D curves. Three example applications are presented: (i) kinematics, (ii) ground reaction forces and (iii) contact pressure distribution in probabilistic finite element modelling. In addition to offering a high-level interface to a variety of common statistical tests like t tests, regression and ANOVA, SPM1D also emphasises fundamental concepts of SPM theory through stand-alone example scripts. Source code and documentation are available at: www.tpataky.net/spm1d/.
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            Generalized n-dimensional biomechanical field analysis using statistical parametric mapping.

            A variety of biomechanical data are sampled from smooth n-dimensional spatiotemporal fields. These data are usually analyzed discretely, by extracting summary metrics from particular points or regions in the continuum. It has been shown that, in certain situations, such schemes can compromise the spatiotemporal integrity of the original fields. An alternative methodology called statistical parametric mapping (SPM), designed specifically for continuous field analysis, constructs statistical images that lie in the original, biomechanically meaningful sampling space. The current paper demonstrates how SPM can be used to analyze both experimental and simulated biomechanical field data of arbitrary spatiotemporal dimensionality. Firstly, 0-, 1-, 2-, and 3-dimensional spatiotemporal datasets derived from a pedobarographic experiment were analyzed using a common linear model to emphasize that SPM procedures are (practically) identical irrespective of the data's physical dimensionality. Secondly two probabilistic finite element simulation studies were conducted, examining heel pad stress and femoral strain fields, respectively, to demonstrate how SPM can be used to probe the significance of field-wide simulation results in the presence of uncontrollable or induced modeling uncertainty. Results were biomechanically intuitive and suggest that SPM may be suitable for a wide variety of mechanical field applications. SPM's main theoretical advantage is that it avoids problems associated with a priori assumptions regarding the spatiotemporal foci of field signals. SPM's main practical advantage is that a unified framework, encapsulated by a single linear equation, affords comprehensive statistical analyses of smooth scalar fields in arbitrarily bounded n-dimensional spaces. 2010 Elsevier Ltd. All rights reserved.
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              The World Health Organization International Classification of Functioning, Disability, and Health: a model to guide clinical thinking, practice and research in the field of cerebral palsy.

              The way we think about health and disease determines to a considerable extent what we do and say in our clinical encounters with patients. The recent publication and promotion of the World Health Organization's International Classification of Function, Health, and Disability (known as the ICF) represents an exciting new way to consider health and disease. In the context of children and youth with cerebral palsy, this model offers many heretofore ignored "point of entry" for counselling and intervention with these conditions. This model also provides many possibilities to explore research questions with a fresh approach. This article outlines the ICF model and discusses these opportunities.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                31 March 2016
                2016
                : 11
                : 3
                : e0152697
                Affiliations
                [1 ]Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium
                [2 ]Clinical Motion Analysis Laboratory, University Hospitals Leuven, Leuven, Belgium
                [3 ]Department of Bioengineering, Shinshu University, Ueda, Japan
                [4 ]Faculty of Engineering Science, KU Leuven, Leuven, Belgium
                [5 ]Department of Development and Regeneration, KU Leuven, Leuven, Belgium
                [6 ]Department of Orthopedics, University Hospitals Leuven, Leuven, Belgium
                Institute Pasteur, FRANCE
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: AN TP TDL GM KD. Performed the experiments: AN EP GM. Analyzed the data: AN EP TP. Wrote the paper: AN EP TP TDL GM KD.

                Article
                PONE-D-15-56128
                10.1371/journal.pone.0152697
                4816309
                27030973
                fb913619-b11c-4f86-979f-4379c6fe5116
                © 2016 Nieuwenhuys et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 8 January 2016
                : 17 March 2016
                Page count
                Figures: 6, Tables: 2, Pages: 17
                Funding
                AN is supported by an 'Onderzoekstoelage' (OT) of KU Leuven university (OT/12/100). EP is supported by the MD Paedigree project, a Model-Driven Paediatric European Digital Repository, partially funded by the European Commission under FP7 - ICT Programme (grant agreement no: 600932, http://www.md-paedigree.eu). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Biomechanics
                Biological Locomotion
                Gait Analysis
                Biology and Life Sciences
                Physiology
                Biological Locomotion
                Gait Analysis
                Medicine and Health Sciences
                Physiology
                Biological Locomotion
                Gait Analysis
                Physical Sciences
                Physics
                Classical Mechanics
                Kinematics
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Limbs (Anatomy)
                Legs
                Knees
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Limbs (Anatomy)
                Legs
                Knees
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Pelvis
                Hip
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Pelvis
                Hip
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Limbs (Anatomy)
                Legs
                Ankles
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Limbs (Anatomy)
                Legs
                Ankles
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Joints (Anatomy)
                Knee Joints
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Joints (Anatomy)
                Knee Joints
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Limbs (Anatomy)
                Legs
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Limbs (Anatomy)
                Legs
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Joints (Anatomy)
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Joints (Anatomy)
                Custom metadata
                All relevant data are available via Figshare ( https://dx.doi.org/10.6084/m9.figshare.2055729.v1).

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                Uncategorized

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