Classification of equinus in ambulatory children with cerebral palsy-discrimination between dynamic tightness and fixed contracture.
In this study a generalised dynamic neural network (GDNN) was designed to process gait analysis parameters to evaluate equinus deformity in ambulatory children with cerebral palsy. The aim was to differentiate dynamic calf muscle tightness from fixed muscle contracture. Patients underwent clinical examination and had instrumented gait analysis before evaluating their equinus under anaesthesia and muscle relaxation at the time of surgery to improve gait. The performance of the clinical examination, the subjective interpretation of gait analysis results, and the application of the neural network to assess ankle function were compared to the examination under anaesthesia. Evaluation of equinus by a Neural Network showed high sensitivity and specificity values with a likelihood ratio of +14.63. The results indicate that dynamic calf muscle tightness can be differentiated from fixed calf muscle contracture with considerable precision that might facilitate clinical decision-making.
Zwick
Ernst B
EB
Department of Paediatric Surgery, Paediatric Orthopaedic Unit, Karl Franzens University, Auenbruggerplatz 34, A-8036 Graz, Austria. ernst.zwick@kfunigraz.ac.at
Leistritz
Lutz
L
Milleit
Berko
B
Saraph
Vinay
V
Zwick
Gertrude
G
Galicki
Miroslaw
M
Witte
Herbert
H
Steinwender
Gerhardt
G
D000465:Algorithms; D000758:Anesthesia; D000842:Ankle / Q000503:physiopathology; D001696:Biomechanical Phenomena; D002547:Cerebral Palsy / Q000503:physiopathology*; D002648:Child; D004863:Equinus Deformity / Q000145:classification / Q000503:physiopathology*; D005684:Gait / Q000502:physiology; D006801:Humans; D007717:Knee / Q000503:physiopathology; D009132:Muscles / Q000503:physiopathology; D016571:Neural Networks, Computer; D010388:Pelvis / Q000503:physiopathology; D012189:Retrospective Studies; D016138:Walking / Q000502:physiology