Literature DB >> 1838724

Statistical diagnosis of lumbar spine disorders using computerized patient pain drawings.

N H Mann1, M D Brown, I Enger.   

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.

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Year:  1991        PMID: 1838724     DOI: 10.1016/0010-4825(91)90040-g

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  5 in total

1.  Pearls: Patient-generated Pain Drawings.

Authors:  Mark D Brown
Journal:  Clin Orthop Relat Res       Date:  2017-03-13       Impact factor: 4.176

Review 2.  Medical diagnostic decision support systems--past, present, and future: a threaded bibliography and brief commentary.

Authors:  R A Miller
Journal:  J Am Med Inform Assoc       Date:  1994 Jan-Feb       Impact factor: 4.497

3.  Is sheep lumbar spine a suitable alternative model for human spinal researches? Morphometrical comparison study.

Authors:  Mahmoud Mageed; Dagmar Berner; Henriette Jülke; Christian Hohaus; Walter Brehm; Kerstin Gerlach
Journal:  Lab Anim Res       Date:  2013-12-20

4.  From Paper to Digital Applications of the Pain Drawing: Systematic Review of Methodological Milestones.

Authors:  Nour Shaballout; Till-Ansgar Neubert; Shellie Boudreau; Florian Beissner
Journal:  JMIR Mhealth Uhealth       Date:  2019-09-05       Impact factor: 4.773

5.  Digital Pain Mapping and Tracking in Patients With Chronic Pain: Longitudinal Study.

Authors:  Maria Galve Villa; Thorvaldur S Palsson; Albert Cid Royo; Carsten R Bjarkam; Shellie A Boudreau
Journal:  J Med Internet Res       Date:  2020-10-26       Impact factor: 5.428

  5 in total

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