title: Diagnostic clinical prediction rules for specific subtypes of low back pain: a systematic review.
abstract: METHODS
  Systematic review.
  
  
  OBJECTIVE
  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.
  
  
  CONCLUSIONS
  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.
  
  
  METHODS
  Diagnosis, level 2a-.
authors.affiliation: School of Health Sciences, The University of Newcastle, Callaghan, Australia.
authors.forename: Robin
authors.initials: R
authors.lastname: Haskins
authors.forename: Peter G
authors.initials: PG
authors.lastname: Osmotherly
authors.forename: Darren A
authors.initials: DA
authors.lastname: Rivett
mesh_terms: D003661:Decision Support Techniques; D006801:Humans; D017116:Low Back Pain / Q000175:diagnosis* / Q000209:etiology; D011379:Prognosis; D013130:Spinal Stenosis / Q000175:diagnosis; D025241:Spondylarthritis / Q000175:diagnosis
keywords: decision support techniques; sensitivity; specificity