Literature DB >> 24648103

Predicting rapid recovery from acute low back pain based on the intensity, duration and history of pain: a validation study.

C M Williams1, M J Hancock, C G Maher, J H McAuley, C W C Lin, J Latimer.   

Abstract

BACKGROUND: Clinical prediction rules can assist clinicians to identify patients with low back pain (LBP) who are likely to recover quickly with minimal treatment; however, there is a paucity of validated instruments to assist with this task.
METHOD: We performed a pre-planned external validation study to assess the generalizability of a simple 3-item clinical prediction rule developed to estimate the probability of recovery from acute LBP at certain time points. The accuracy of the rule (calibration and discrimination) was determined in a sample of 956 participants enrolled in a randomized controlled trial.
RESULTS: The calibration of the rule was reasonable in the new sample with predictions of recovery typically within 5-10% of observed recovery. Discriminative performance of the rule was poor to moderate and similar to that found in the development sample.
CONCLUSIONS: The results suggest that the rule can be used to provide accurate information about expected recovery from acute LBP, within the first few weeks of patients presenting to primary care. Impact analysis to determine if the rule influences clinical behaviours and patient outcomes is required.
© 2014 European Pain Federation - EFIC®

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Year:  2014        PMID: 24648103     DOI: 10.1002/j.1532-2149.2014.00467.x

Source DB:  PubMed          Journal:  Eur J Pain        ISSN: 1090-3801            Impact factor:   3.931


  10 in total

1.  The economic burden of guideline-recommended first line care for acute low back pain.

Authors:  Chung-Wei Christine Lin; Qiang Li; Christopher M Williams; Christopher G Maher; Richard O Day; Mark J Hancock; Jane Latimer; Andrew J Mclachlan; Stephen Jan
Journal:  Eur Spine J       Date:  2016-09-21       Impact factor: 3.134

2.  Development and validation of a screening tool to predict the risk of chronic low back pain in patients presenting with acute low back pain: a study protocol.

Authors:  Adrian Traeger; Nicholas Henschke; Markus Hübscher; Christopher M Williams; Steven J Kamper; Chris G Maher; G Lorimer Moseley; James H McAuley
Journal:  BMJ Open       Date:  2015-07-15       Impact factor: 2.692

Review 3.  Can screening instruments accurately determine poor outcome risk in adults with recent onset low back pain? A systematic review and meta-analysis.

Authors:  Emma L Karran; James H McAuley; Adrian C Traeger; Susan L Hillier; Luzia Grabherr; Leslie N Russek; G Lorimer Moseley
Journal:  BMC Med       Date:  2017-01-19       Impact factor: 8.775

4.  Latent class analysis derived subgroups of low back pain patients - do they have prognostic capacity?

Authors:  Anne Molgaard Nielsen; Lise Hestbaek; Werner Vach; Peter Kent; Alice Kongsted
Journal:  BMC Musculoskelet Disord       Date:  2017-08-09       Impact factor: 2.362

5.  Pain interference and physical function demonstrate poor longitudinal association in people living with pain: a PROMIS investigation.

Authors:  Nicholas V Karayannis; John A Sturgeon; Ming Chih-Kao; Corinne Cooley; Sean C Mackey
Journal:  Pain       Date:  2017-06       Impact factor: 6.961

6.  Does the performance of five back-associated exercises relate to the presence of low back pain? A cross-sectional observational investigation in regional Australian council workers.

Authors:  Charles Philip Gabel; Hamid Reza Mokhtarinia; Jonathan Hoffman; Jason Osborne; E-Liisa Laakso; Markus Melloh
Journal:  BMJ Open       Date:  2018-08-08       Impact factor: 2.692

7.  Do sensorimotor cortex activity, an individual's capacity for neuroplasticity, and psychological features during an episode of acute low back pain predict outcome at 6 months: a protocol for an Australian, multisite prospective, longitudinal cohort study.

Authors:  Luke C Jenkins; Wei-Ju Chang; Valentina Buscemi; Matthew Liston; Barbara Toson; Michael Nicholas; Thomas Graven-Nielsen; Michael Ridding; Paul W Hodges; James H McAuley; Siobhan M Schabrun
Journal:  BMJ Open       Date:  2019-05-22       Impact factor: 2.692

8.  Using Postmarket Surveillance to Assess Safety-Related Events in a Digital Rehabilitation App (Kaia App): Observational Study.

Authors:  Deeptee Jain; Kevin Norman; Zachary Werner; Bar Makovoz; Turner Baker; Stephan Huber
Journal:  JMIR Hum Factors       Date:  2021-11-09

9.  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

10.  Predicting pain recovery in patients with acute low back pain: a study protocol for a broad validation of a prognosis prediction model.

Authors:  Fernanda Gonçalves Silva; Tatiane Mota da Silva; Gabriele Alves Palomo; Mark Jonathan Hancock; Lucíola da Cunha Menezes Costa; Leonardo Oliveira Pena Costa
Journal:  BMJ Open       Date:  2020-10-28       Impact factor: 2.692

  10 in total

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