Literature DB >> 18418341

The term diplegia should be enhanced. Part III: inter-observer reliability of the new rehabilitation oriented classification.

R Pascale1, S Perazza, G Borelli, E Bianchini, S Alboresi, P B Paolicelli, A Ferrari, G Cioni.   

Abstract

AIM: The aim of this study was to validate a recent classification of gait in children with the spastic diplegic form of cerebral palsy (CP) by checking the reliability of different scorers in assigning subject walking performance to one of the four specific patterns described in the classification.
METHODS: The gait patterns of 50 children and adolescents with CP (23 males, 27 females; age range 3-17 years) were selected among patients whose videos were stored in the archives of the Pisa and Reggio Emilia Hospitals. Only video recordings of gait with homogeneous features (duration of at least 90 s, simultaneous recordings on sagittal and frontal views, and other criteria) were taken for examination. The videos were blindly scored using an observational gait scale, at first by two of the authors of the classification system (defined as ''maximum experts''), then by ten expert observers, and finally by 206 professionals of rehabilitation after a one-day training on the classification. Cohen's kappa statistics (k) and intra class correlations (ICC) were calculated.
RESULTS: Kappa and ICC indicate an almost perfect agreement both between the two maximum experts and among the ten expert observers. Good results were also obtained in the group of one-day trained scorers. Only a few cases were assigned to the ''unclassified'' category. The profession of the observer (doctor or therapist) and previous knowledge of the classification had no significant influence on reliability scores.
CONCLUSION: The results suggest that the proposed classification can be reliably applied, even utilizing short video recordings, to arrange diplegic children into different patterns. Further studies are needed to validate the use of this classification system for clinical and research aims.

Entities:  

Mesh:

Year:  2008        PMID: 18418341

Source DB:  PubMed          Journal:  Eur J Phys Rehabil Med        ISSN: 1973-9087            Impact factor:   2.874


  1 in total

1.  Gait-Based Diplegia Classification Using LSMT Networks.

Authors:  Alberto Ferrari; Luca Bergamini; Giorgio Guerzoni; Simone Calderara; Nicola Bicocchi; Giorgio Vitetta; Corrado Borghi; Rita Neviani; Adriano Ferrari
Journal:  J Healthc Eng       Date:  2019-01-17       Impact factor: 2.682

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.