title: Statistical diagnosis of lumbar spine disorders using computerized patient pain drawings.
abstract: Discriminant analysis is applied to 250 quantified low back patient pain drawings to study the ability of a computerized statistical method for classifying novel cases into one of five clinically-significant lumbar spine disorders. Tests on independent data were 46.2 percent (%) correct overall. Benign disorder (55.6%), herniated disc (51.7%), and psychogenic (56.3%) pain drawings were more accurately discriminated than the spinal stenosis (32.2%) and underlying disorder cases (35.2%). It is concluded that computerized patient pain drawings provide valid "initial impressions" of lumbar spine disorders. Further research is suggested to better distinguish between herniated disc and spinal stenosis pain descriptions, and for better recognition of serious underlying disorder pain drawings.
authors.affiliation: Department of Orthopaedics and Rehabilitation, University of Miami, Florida.
authors.forename: N H
authors.initials: NH
authors.lastname: Mann
authors.forename: M D
authors.initials: MD
authors.lastname: Brown
authors.forename: I
authors.initials: I
authors.lastname: Enger
mesh_terms: D001416:Back Pain / Q000209:etiology*; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation*; D003937:Diagnosis, Differential; D006801:Humans; D007405:Intervertebral Disc Displacement / Q000150:complications / Q000175:diagnosis; D008159:Lumbar Vertebrae; D010147:Pain Measurement / Q000295:instrumentation* / Q000706:statistics & numerical data*; D011602:Psychophysiologic Disorders / Q000175:diagnosis; D012984:Software; D013122:Spinal Diseases / Q000150:complications / Q000175:diagnosis*; D013130:Spinal Stenosis / Q000150:complications / Q000175:diagnosis