Literature DB >> 28257616

Evaluation of the STarT Back Screening Tool for Prediction of Low Back Pain Intensity in an Outpatient Physical Therapy Setting.

Irene Toh, Hwei-Chi Chong, Jennifer Suet-Ching Liaw, Yong-Hao Pua.   

Abstract

Study Design Prospective cohort study. Background Optimal management of patients with low back pain (LBP) relies on accurate prognosis of future clinical outcomes. The STarT Back Screening Tool (SBT), a prognostic index developed and validated in the primary care setting, has 3 scoring measures: SBT overall, psychosocial, and categorical scores. Objective Our study aimed to compare the predictive validity of 3 SBT measures with future pain intensity in patients receiving physical therapy for LBP. Methods Two hundred seven patients with LBP receiving physical therapy completed the SBT at initial (baseline) evaluation and were evaluated 12 weeks later for their pain intensity. Multivariable proportional odds regression was used to evaluate the associations of the various SBT measures with pain intensity at follow-up. Results Adjusting for covariates, all SBT measures were positively and significantly associated with the odds of greater pain intensity at follow-up evaluation (P<.01). Adding SBT psychosocial scores to a covariate-only model improved its predictive accuracy (concordance statistic increase, 0.03; 95% confidence interval: 0.01, 0.09), while improvements in prediction were smaller or negligible with the SBT overall and categorical scores (concordance statistic increase, 0.02 and 0.007, respectively). In mutually adjusted analyses, SBT psychosocial scores added incremental predictive value over SBT overall scores in predicting future pain intensity (P = .03). Conclusion Among the 3 SBT measures, the SBT psychosocial subscale was a significant predictor of future pain intensity in patients with LBP and had comparable, if not better, prognostic significance compared with the SBT overall score. Level of Evidence Prognosis, level 4. J Orthop Sports Phys Ther 2017;47(4):261-267. Epub 3 Mar 2017. doi:10.2519/jospt.2017.7284.

Entities:  

Keywords:  low back pain; prognosis; psychosocial

Mesh:

Year:  2017        PMID: 28257616     DOI: 10.2519/jospt.2017.7284

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


  7 in total

Review 1.  Artificial intelligence to improve back pain outcomes and lessons learnt from clinical classification approaches: three systematic reviews.

Authors:  Scott D Tagliaferri; Maia Angelova; Xiaohui Zhao; Patrick J Owen; Clint T Miller; Tim Wilkin; Daniel L Belavy
Journal:  NPJ Digit Med       Date:  2020-07-09

2.  The use of STarT BACK Screening Tool in emergency departments for patients with acute low back pain: a prospective inception cohort study.

Authors:  Flávia Cordeiro Medeiros; Leonardo Oliveira Pena Costa; Indiara Soares Oliveira; Renan Kendy Oshima; Lucíola Cunha Menezes Costa
Journal:  Eur Spine J       Date:  2018-04-18       Impact factor: 3.134

3.  Nicotine dependence and the International Association for the Study of Pain neuropathic pain grade in patients with chronic low back pain and radicular pain: is there an association?

Authors:  Emanuel Schembri; Victoria Massalha; Karl Spiteri; Liberato Camilleri; Stephen Lungaro-Mifsud
Journal:  Korean J Pain       Date:  2020-10-01

4.  Use of the STarT Back Screening Tool in patients with chronic low back pain receiving physical therapy interventions.

Authors:  Flávia Cordeiro Medeiros; Evelyn Cassia Salomão; Leonardo Oliveira Pena Costa; Diego Galace de Freitas; Thiago Yukio Fukuda; Renan Lima Monteiro; Marco Aurélio Nemitalla Added; Alessandra Narciso Garcia; Lucíola da Cunha Menezes Costa
Journal:  Braz J Phys Ther       Date:  2020-07-29       Impact factor: 3.377

Review 5.  Artificial intelligence to improve back pain outcomes and lessons learnt from clinical classification approaches: three systematic reviews.

Authors:  Scott D Tagliaferri; Maia Angelova; Xiaohui Zhao; Patrick J Owen; Clint T Miller; Tim Wilkin; Daniel L Belavy
Journal:  NPJ Digit Med       Date:  2020-07-09

6.  Identifying psychosocial characteristics that predict outcome to the UPLIFT programme for people with persistent back pain: protocol for a prospective cohort study.

Authors:  Hayley Thomson; Kerrie Evans; Jonathon Dearness; John Kelley; Kylie Conway; Collette Morris; Leanne Bisset; Gwendolijne Scholten-Peeters; Pim Cuijpers; Michel W Coppieters
Journal:  BMJ Open       Date:  2019-08-10       Impact factor: 2.692

7.  Effect of low back pain on clinical-functional factors and its associated potential risk of chronicity in adolescent dancers of classical ballet: cross-sectional study.

Authors:  Brenda Luciano de Souza; Patricia Colombo de Souza; Ana Paula Ribeiro
Journal:  BMC Sports Sci Med Rehabil       Date:  2022-05-02
  7 in total

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