Literature DB >> 12486357

A clinical prediction rule for classifying patients with low back pain who demonstrate short-term improvement with spinal manipulation.

Timothy Flynn1, Julie Fritz, Julie Whitman, Robert Wainner, Jake Magel, Daniel Rendeiro, Barbara Butler, Matthew Garber, Stephen Allison.   

Abstract

STUDY
DESIGN: A prospective, cohort study of patients with nonradicular low back pain referred to physical therapy.
OBJECTIVE: Develop a clinical prediction rule for identifying patients with low back pain who improve with spinal manipulation. SUMMARY OF BACKGROUND DATA: Development of clinical prediction rules for classifying patients with low back pain who are likely to respond to a particular intervention, such as manipulation, would improve clinical decision-making and research.
METHODS: Patients with nonradicular low back pain underwent a standardized examination and then underwent a standardized spinal manipulation treatment program. Success with treatment was determined using percent change in disability scores over three sessions and served as the reference standard for determining the accuracy of examination variables. Examination variables were first analyzed for univariate accuracy in predicting success and then combined into a multivariate clinical prediction rule.
RESULTS: Seventy-one patients participated. Thirty-two had success with the manipulation intervention. A clinical prediction rule with five variables (symptom duration, fear-avoidance beliefs, lumbar hypomobility, hip internal rotation range of motion, and no symptoms distal to the knee) was identified. The presence of four of five of these variables (positive likelihood ratio = 24.38) increased the probability of success with manipulation from 45% to 95%.
CONCLUSION: It appears that patients with low back pain likely to respond to manipulation can be accurately identified before treatment.

Entities:  

Mesh:

Year:  2002        PMID: 12486357     DOI: 10.1097/00007632-200212150-00021

Source DB:  PubMed          Journal:  Spine (Phila Pa 1976)        ISSN: 0362-2436            Impact factor:   3.468


  161 in total

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8.  Exploring the contribution of patient-reported and clinician based variables for the prediction of low back work status.

Authors:  Martijn W Heymans; Jon J Ford; Joan M McMeeken; Alexander Chan; Henrica C W de Vet; Willem van Mechelen
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9.  Development of a clinical prediction rule to identify patients with neck pain likely to benefit from cervical traction and exercise.

Authors:  Nicole H Raney; Evan J Petersen; Tracy A Smith; James E Cowan; Daniel G Rendeiro; Gail D Deyle; John D Childs
Journal:  Eur Spine J       Date:  2009-01-14       Impact factor: 3.134

10.  Spinal manipulative therapy for acute low back pain: a clinical perspective.

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Journal:  J Man Manip Ther       Date:  2008
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