Literature DB >> 26144686

Prediction of outcome in patients with low back pain--A prospective cohort study comparing clinicians' predictions with those of the Start Back Tool.

Alice Kongsted1, Cathrine Hedegaard Andersen2, Martin Mørk Hansen2, Lise Hestbaek3.   

Abstract

The clinical course of low back pain (LBP) cannot be accurately predicted by existing prediction tools. Therefore clinicians rely largely on their experience and clinical judgement. The objectives of this study were to investigate 1) which patient characteristics were associated with chiropractors' expectations of outcome from a LBP episode, 2) if clinicians' expectations related to outcome, 3) how accurate clinical predictions were as compared to those of the STarT Back Screening Tool (SBT), and 4) if accuracy was improved by combining clinicians' expectations and the SBT. Outcomes were measured as LBP intensity (0-10) and disability (RMDQ) after 2-weeks, 3-months, and 12-months. The course of LBP in 859 patients was predicted to be short (54%), prolonged (36%), or chronic (7%). Clinicians' expectations were most strongly associated with education, LBP history, radiating pain, and neurological signs at baseline and related to all outcomes. The accuracies of predictions made by clinicians (AUC .58-.63) and the SBT (AUC .50-.61) were comparable and low. No substantial increase in the predictive capability was achieved by combining clinicians' expectations and the SBT. In conclusion, chiropractors' predictions were associated with well-established prognostic factors but not simply a product of these. Chiropractors were able to predict differences in outcome on a group level, but prediction of individual patients' outcomes were inaccurate and not substantially improved by the SBT. It is worth investigating if more accurate tools can be developed to assist clinicians in prediction of outcome.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Chiropractic; Low back pain; Prediction; Primary care; Prognosis

Mesh:

Year:  2015        PMID: 26144686     DOI: 10.1016/j.math.2015.06.008

Source DB:  PubMed          Journal:  Man Ther        ISSN: 1356-689X


  25 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.  Translation and Adaptation of the French Version of the Risk Stratification Index, a Tool for Stratified Care in Chronic Low Back Pain: A Pilot Study.

Authors:  Alexandra Naïr; Chiao-I Lin; Pia-Maria Wippert
Journal:  Medicina (Kaunas)       Date:  2022-03-23       Impact factor: 2.948

4.  Discriminative and Predictive Analysis of the Brazilian Version of the Örebro Musculoskeletal Pain Screening Questionnaire (ÖMPSQ) Short-Form in Patients With Low Back Pain.

Authors:  Fernanda F Fuhro; Felipe R C Fagundes; Ana Carolina T Manzoni; Cristina M N Cabral
Journal:  J Chiropr Med       Date:  2022-04-06

Review 5.  [Psychosocial risk factors for chronic back pain in the general population and in competitive sports : From theory to clinical screening-a review from the MiSpEx network].

Authors:  M I Hasenbring; C Levenig; D Hallner; A-K Puschmann; A Weiffen; J Kleinert; J Belz; M Schiltenwolf; A-C Pfeifer; J Heidari; M Kellmann; P-M Wippert
Journal:  Schmerz       Date:  2018-08       Impact factor: 1.107

6.  Exploring pain phenotypes in workers with chronic low back pain: Application of IMMPACT recommendations.

Authors:  Lisa C Carlesso; Yannick Tousignant-Laflamme; William Shaw; Christian Larivière; Manon Choinière
Journal:  Can J Pain       Date:  2021-03-03

7.  Psychological and behavioral differences between low back pain populations: a comparative analysis of chiropractic, primary and secondary care patients.

Authors:  Andreas Eklund; Gunnar Bergström; Lennart Bodin; Iben Axén
Journal:  BMC Musculoskelet Disord       Date:  2015-10-19       Impact factor: 2.362

8.  Do psychological and behavioral factors classified by the West Haven-Yale Multidimensional Pain Inventory (Swedish version) predict the early clinical course of low back pain in patients receiving chiropractic care?

Authors:  Andreas Eklund; Gunnar Bergström; Lennart Bodin; Iben Axén
Journal:  BMC Musculoskelet Disord       Date:  2016-02-12       Impact factor: 2.362

9.  Derivation of a Risk Assessment Tool for Prediction of Long-Term Pain Intensity Reduction After Physical Therapy.

Authors:  Maggie E Horn; Steven Z George; Cai Li; Sheng Luo; Trevor A Lentz
Journal:  J Pain Res       Date:  2021-05-28       Impact factor: 3.133

10.  Estimating the Risk of Chronic Pain: Development and Validation of a Prognostic Model (PICKUP) for Patients with Acute Low Back Pain.

Authors:  Adrian C Traeger; Nicholas Henschke; Markus Hübscher; Christopher M Williams; Steven J Kamper; Christopher G Maher; G Lorimer Moseley; James H McAuley
Journal:  PLoS Med       Date:  2016-05-17       Impact factor: 11.069

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