Literature DB >> 25573009

Diagnostic clinical prediction rules for specific subtypes of low back pain: a systematic review.

Robin Haskins1, Peter G Osmotherly, Darren A Rivett.   

Abstract

STUDY
DESIGN: Systematic review.
OBJECTIVES: To identify diagnostic clinical prediction rules (CPRs) for low back pain (LBP) and to assess their readiness for clinical application.
BACKGROUND: Significant research has been invested into the development of CPRs that may assist in the meaningful subgrouping of patients with LBP. To date, very little is known about diagnostic forms of CPRs for LBP, which relate to the present status or classification of an individual, and whether they have been developed sufficiently to enable their application in clinical practice.
METHODS: A sensitive electronic search strategy using 7 databases was combined with hand searching and citation tracking to identify eligible studies. Two independent reviewers identified relevant studies for inclusion using a 2-stage selection process. The quality appraisal of included studies was conducted by 2 independent raters using the Quality Assessment of Diagnostic Accuracy Studies-2 and checklists composed of accepted methodological standards for the development of CPRs.
RESULTS: Of 10 014 studies screened for eligibility, the search identified that 13 diagnostic CPRs for LBP have been derived. Among those, 1 tool for identifying lumbar spinal stenosis and 2 tools for identifying inflammatory back pain have undergone validation. No impact analysis studies were identified.
CONCLUSION: Most diagnostic CPRs for LBP are in their initial development phase and cannot be recommended for use in clinical practice at this time. Validation and impact analysis of the diagnostic CPRs identified in this review are warranted, particularly for those tools that meet an identified unmet need of clinicians who manage patients with LBP. LEVEL OF EVIDENCE: Diagnosis, level 2a-.

Entities:  

Keywords:  decision support techniques; sensitivity; specificity

Mesh:

Year:  2015        PMID: 25573009     DOI: 10.2519/jospt.2015.5723

Source DB:  PubMed          Journal:  J Orthop Sports Phys Ther        ISSN: 0190-6011            Impact factor:   4.751


  6 in total

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Authors:  Jon Lurie; Christy Tomkins-Lane
Journal:  BMJ       Date:  2016-01-04

Review 2.  Systematic Selection of Key Logistic Regression Variables for Risk Prediction Analyses: A Five-Factor Maximum Model.

Authors:  Timothy E Hewett; Kate E Webster; Wendy J Hurd
Journal:  Clin J Sport Med       Date:  2019-01       Impact factor: 3.638

3.  Evidence base and future research directions in the management of low back pain.

Authors:  Allan Abbott
Journal:  World J Orthop       Date:  2016-03-18

4.  Effectiveness of graded activity versus physiotherapy in patients with chronic nonspecific low back pain: midterm follow up results of a randomized controlled trial.

Authors:  Maurício Oliveira Magalhães; Josielli Comachio; Paulo Henrique Ferreira; Evangelos Pappas; Amélia Pasqual Marques
Journal:  Braz J Phys Ther       Date:  2017-07-12       Impact factor: 3.377

Review 5.  The Evolving Case Supporting Individualised Physiotherapy for Low Back Pain.

Authors:  Jon Ford; Andrew Hahne; Luke Surkitt; Alexander Chan; Matthew Richards
Journal:  J Clin Med       Date:  2019-08-28       Impact factor: 4.241

6.  ISSLS Prize Winner: Consensus on the Clinical Diagnosis of Lumbar Spinal Stenosis: Results of an International Delphi Study.

Authors:  Christy Tomkins-Lane; Markus Melloh; Jon Lurie; Matt Smuck; Michele C Battié; Brian Freeman; Dino Samartzis; Richard Hu; Thomas Barz; Kent Stuber; Michael Schneider; Andrew Haig; Constantin Schizas; Jason Pui Yin Cheung; Anne F Mannion; Lukas Staub; Christine Comer; Luciana Macedo; Sang-Ho Ahn; Kazuhisa Takahashi; Danielle Sandella
Journal:  Spine (Phila Pa 1976)       Date:  2016-08-01       Impact factor: 3.241

  6 in total

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