# The Gait Pattern Classification System for Children with Spastic Cerebral Palsy (GaP-CP)—A Validity Study

## TL;DR

This study validates a new system for classifying gait patterns in children with spastic cerebral palsy, showing it can effectively distinguish different gait deviations and support clinical decisions.

## Contribution

The study confirms the validity of the GaP-CP system and identifies pattern-specific clinical phenotypes for children with spastic cerebral palsy.

## Key findings

- The GaP-CP system shows good content and construct validity for classifying gait patterns in children with spastic cerebral palsy.
- Pattern-specific clinical phenotypes were identified based on patient-specific characteristics, but not based on impairment-specific comparisons.
- Refined classification rules are recommended for clinical implementation of the GaP-CP system.

## Abstract

Background: In order to classify the gait of children with spastic cerebral palsy (sCP), the “gait pattern classification system for children with sCP” (GaP-CP) has been developed, based on a systematic review and complemented by an additional class of “mild deviations”. The objective of the current study was to examine the content and construct validity of the GaP-CP. Methods: Statistical non-parametric comparisons identified the differences between the kinematics (N = 270) and kinetics (N = 208) of children with sCP and children with typically developing gait (N = 56) (content validity—aim 1), and between neighboring patterns (construct validity—aim 2a). Pattern-specific clinical phenotypes were explored based on the differences between all gait patterns (Kruskal–Wallis comparisons with post hoc Mann–Whitney U tests) in patient- and impairment-specific characteristics (construct validity—aim 2b). Results: The apparent and true equinus were the most and least prevalent patterns, respectively. The majority of the original classification rules were confirmed by the patient data, indicating good content validity of the GaP-CP. Its construct validity was strengthened by distinguishing between gait deviations of neighboring patterns and differentiating between gait patterns based on patient-specific characteristics, leading to pattern-specific phenotypes. Yet, pattern-specific phenotypes could not be clearly defined based on the impairment-specific comparisons. Conclusions: The current results support the validity of the GaP-CP. Refined classification rules, using more precise terminology, establish a roadmap for its clinical implementation. The pattern-specific clinical phenotypes enable its use in a clinical context and may aid clinical decision-making.