Author:

Keywords:

low back pain, subclassification, electromyography, motion analysis, posture, motor control impairment, Science & Technology, Life Sciences & Biomedicine, Clinical Neurology, Orthopedics, Neurosciences & Neurology, low back pain, subclassification, electromyography, motion analysis, posture, motor control impairment, LUMBAR SPINE, SURFACE ELECTROMYOGRAPHY, STABILIZING EXERCISE, RELIABILITY, INSTABILITY, DYSFUNCTION, DISORDERS, STIFFNESS, TISSUE, CARE, Adult, Biomechanical Phenomena, Chronic Disease, Diagnosis, Differential, Female, Humans, Low Back Pain, Lumbar Vertebrae, Lumbosacral Region, Male, Models, Statistical, Movement Disorders, Muscle Contraction, Muscle, Skeletal, Posture, Predictive Value of Tests, Range of Motion, Articular, Sacrum, Sensitivity and Specificity, Spine, 0903 Biomedical Engineering, 1103 Clinical Sciences, 3202 Clinical sciences, 3209 Neurosciences, 4201 Allied health and rehabilitation science

Abstract:

Study Design. Statistical Classification Model for nonspecific chronic low back pain (NS-CLBP) patients and controls based on parameters of motor control. Objective. Develop a Statistical Classification Model to discriminate between 2 subgroups of NS-CLBP (Flexion Pattern [FP] and Active Extension Pattern [AEP]) and a control group using biomechanical variables quantifying parameters of motor control. Summary of Background Data. It has been well documented that many CLBP patients have motor control impairments of their lumbar spine. O’Sullivan proposed a mechanism-based classification system for NS-CLBP with motor control impairments based on a comprehensive subjective and physical examination to establish the relationship between pain provocation and spinal motor control. For the FP and AEP s, 2 groups defined by O’Sullivan and under investigation is this study, the motor control impairment is considered to be the mechanism maintaining their CLBP. No previous studies have used a Statistical Model with measurements of motor control impairment to subclassify NS-CLBP patients. Methods. Thirty-three NS-CLBP patients (20 FP and 13 AEP) and 34 asymptomatic subjects had synchronized lumbosacral kinematics and trunk muscle activation recorded during commonly reported aggravating postures and movements. Biomechanical variables were quantified and a Statistical Classification Model was developed. Results. The Statistical Model used 5 kinematic and 2 electromyography variables. The model correctly classified 96.4% of cases. Conclusion. Selected biomechanical variables were predictors for subgroup membership and were able to discriminate the 3 subgroups. This study adds further support toward the validation of the proposed classification system. Key words: low back pain, subclassification, electromyography, motion analysis, posture, motor control impairment. Spine 2009;34:1610–1618