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Gait Profile Score (GPS)
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Supplemental: Cerebral Palsy (CP)
Short Description of Instrument
The Gait Profile Score (GPS) (Baker et al., 2009) is an index of overall gait pathology that may be used when examining the efficacy of interventions (i.e., therapy, bracing, surgery). The GPS is reported in the same units (degrees) as the kinematic variables and is the root mean square (RMS) difference between a specific gait trial and the averaged data from people with no gait pathology (Baker, 2012). The GPS can be decomposed to provide Gait Variable Scores (GVS) for nine key component kinematic variables: pelvic tilt, obliquity, and rotation, and hip flexion, abduction and rotation, knee flexion, ankle dorsiflexion and foot progression which are presented as a Movement Analysis Profile (MAP). The GPS is easier to calculate for new models where a large reference dataset is not available and in association with applications using the Movement Analysis Profile (MAP) (Baker et al., 2009).
Along with the Gillette Gait Index (GGI) and GDI, the GPS is one of 3 single indices of the three-dimensional gait analysis (3DGA) that summarize 3DGA kinematics (Cimolin & Galli, 2014).
Comments/Special Instructions
The GPS was developed to include the same kinematic features as the GDI (Schwartz et al., 2008). However, the GPS differs mathematically from the GDI and represents a raw score rather than a logarithmic scaled value (Baker et al., 2009; Schwartz et al., 2008).
A patient with data or a value that is twice as different from that of another person shows twice the GPS (Baker et al., 2009). The GDI and the GPS were developed for gait assessment of patients in general and not exclusively for CP patients (Tsitlakidis et al, 2020).
Scoring and Psychometric Properties
Scoring: The GPS is based on the GVS which is the RMS difference between a specific time normalized gait variable and the mean data from a reference population calculated across the gait cycle (Baker, 2012). The GVS for 15 clinically relevant kinematic variables (pelvic tilt, obliquity, and rotation of the left side and hip flexion, abduction, internal rotation, knee flexion, ankle dorsiflexion and foot progression, for the left and right sides) are combined to form the MAP.
Psychometric Properties: The GPS is highly correlated with the Gait Deviation Index (GDI) (Schwartz et al., 2008). The GPS has been validated against the established index measure of gait abnormality and general measures of mobility in children with gait pathology (Baker, 2009). The GPS and the MAP component scores have been shown to be significantly positively correlated with clinician ratings of kinematic gait deviation (Beynon, 2010).
Strengths: The GPS has the advantage over the GDI in that one can split the GPS up to the single joint levels for further analysis (Schweizer et al., 2013). The GPS is the only measure of gait pathology that has an established Minimally Clinically Important Difference (MCID) for both the GPS and for each GVS (Baker, 2012). Both the GDI and the GPS have been shown to have excellent inter-rater reliability (Rasmussen, 2015). Another strong point of the GPS is that it can give a statistical overview over a large cohort (Schweizer et al., 2013).
Weaknesses: The GPS is only a measure of gait quality during straight line walking on a clear level surface within a gait analysis laboratory. Other outcome measures would be required to establish whether gait function, particularly in more real-world environments, has improved as the result of a particular interventions (Baker, 2012). Gait speed is not correlated with GPS (Baker et al., 2009), and it is recommended that self-selected walking speed be reported in addition to GPS for clinical studies (Baker et al., 2012). The GPS does not provide the direction of gait deviation (e.g., below or above the norm) nor the factors contributing to the change of function. Additionally, the GPS does not show whether the deviation is due to time-shifts, or if the joint curves deviate in magnitude only (Schweizer et al., 2013).
Key References:
Baker R, McGinley JL, Schwartz MH, Beynon S, Rozumalski A, Graham HK, Tirosh O. The gait profile score and movement analysis profile. Gait Posture. 2009 Oct;30(3):265-9.
Baker R, McGinley JL, Schwartz M, Thomason P, Rodda J, Graham HK. The minimal clinically important difference for the Gait Profile Score. Gait Posture. 2012 Apr;35(4):612-5.
Beynon S, McGinley JL, Dobson F, Baker R. Correlations of the Gait Profile Score and the Movement Analysis Profile relative to clinical judgments. Gait Posture. 2010 May;32(1):129-32.
Rasmussen HM, Nielsen DB, Pedersen NW, Overgaard S, Holsgaard-Larsen A. Gait Deviation Index, Gait Profile Score and Gait Variable Score in children with spastic cerebral palsy: Intra-rater reliability and agreement across two repeated sessions. Gait Posture. 2015 Jul;42(2):133-7.
Schwartz MH, Rozumalski A. The Gait Deviation Index: a new comprehensive index of gait pathology. Gait Posture. 2008 Oct;28(3):351-7.
Schweizer K, Romkes J, Coslovsky M, Brunner R. The influence of muscle strength on the gait profile score (GPS) across different patients. Gait Posture. 2014 Jan;39(1):80-5.
Additional References:
Cimolin V, Galli M, Vimercati SL, Albertini G. Use of the Gait Deviation Index for the assessment of gastrocnemius fascia lengthening in children with Cerebral Palsy. Res Dev Disabil. 2011 Jan-Feb;32(1):377-81.
Cimolin V, Galli M. Summary measures for clinical gait analysis: a literature review. Gait Posture. 2014 Apr;39(4):1005-10.
Danino B, Erel S, Kfir M, Khamis S, Batt R, Hemo Y, Wientroub S, Hayek S. Are Gait Indices Sensitive Enough to Reflect the Effect of Ankle Foot Orthosis on Gait Impairment in Cerebral Palsy Diplegic Patients? J Pediatr Orthop. 2016 Apr-May;36(3):294-8.
Guzik A, Druzbicki M. Application of the Gait Deviation Index in the analysis of post-stroke hemiparetic gait. J Biomech. 2020 Jan 23;99:109575.
Malt MA, Aarli Å, Bogen B, Fevang JM. Correlation between the Gait Deviation Index and gross motor function (GMFCS level) in children with cerebral palsy. J Child Orthop. 2016 Jun;10(3):261-6.Molloy M, McDowell BC, Kerr C, Cosgrove AP. Further evidence of validity of the Gait Deviation Index. Gait Posture. 2010 Apr;31(4):479-82.
Speciali DS, Corr?a JC, Luna NM, Brant R, Greve JM, de Godoy W, Baker R, Lucareli PR. Validation of GDI, GPS and GVS for use in Parkinson's disease through evaluation of effects of subthalamic deep brain stimulation and levodopa. Gait Posture. 2014 Apr;39(4):1142-5.
Cerebral Palsy-specific:
Holmes SJ, Mudge AJ, Wojciechowski EA, Axt MW, Burns J. Impact of multilevel joint contractures of the hips, knees and ankles on the Gait Profile score in children with cerebral palsy. Clin Biomech (Bristol, Avon). 2018 Nov;59:8-14.
Tsitlakidis S, Schwarze M, Westhauser F, Heubisch K, Horsch A, Hagmann S, Wolf SI, GÖtze M. Gait Indices for Characterization of Patients with Unilateral Cerebral Palsy. J Clin Med. 2020 Nov 30;9(12):3888.
Document last updated June 2023