IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0265970.html
   My bibliography  Save this article

Derivation of clinical prediction rules for identifying patients with non-acute low back pain who respond best to a lumbar stabilization exercise program at post-treatment and six-month follow-up

Author

Listed:
  • Christian Larivière
  • Khalil Rabhi
  • Richard Preuss
  • Marie-France Coutu
  • Nicolas Roy
  • Sharon M Henry

Abstract

Low back pain (LBP) remains one of the most common and incapacitating health conditions worldwide. Clinical guidelines recommend exercise programs after the acute phase, but clinical effects are modest when assessed at a population level. Research needs to determine who is likely to benefit from specific exercise interventions, based on clinical presentation. This study aimed to derive clinical prediction rules (CPRs) for treatment success, using a lumbar stabilization exercise program (LSEP), at the end of treatment and at six-month follow-up. The eight-week LSEP, including clinical sessions and home exercises, was completed by 110 participants with non-acute LBP, with 100 retained at the six-month follow-up. Physical (lumbar segmental instability, motor control impairments, posture and range of motion, trunk muscle endurance and physical performance tests) and psychological (related to fear-avoidance and home-exercise adherence) measures were collected at a baseline clinical exam. Multivariate logistic regression models were used to predict clinical success, as defined by ≥50% decrease in the Oswestry Disability Index. CPRs were derived for success at program completion (T8) and six-month follow-up (T34), negotiating between predictive ability and clinical usability. The chosen CPRs contained four (T8) and three (T34) clinical tests, all theoretically related to spinal instability, making these CPRs specific to the treatment provided (LSEP). The chosen CPRs provided a positive likelihood ratio of 17.9 (T8) and 8.2 (T34), when two or more tests were positive. When applying these CPRs, the probability of treatment success rose from 49% to 96% at T8 and from 53% to 92% at T34. These results support the further development of these CPRs by proceeding to the validation stage.

Suggested Citation

  • Christian Larivière & Khalil Rabhi & Richard Preuss & Marie-France Coutu & Nicolas Roy & Sharon M Henry, 2022. "Derivation of clinical prediction rules for identifying patients with non-acute low back pain who respond best to a lumbar stabilization exercise program at post-treatment and six-month follow-up," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-22, April.
  • Handle: RePEc:plo:pone00:0265970
    DOI: 10.1371/journal.pone.0265970
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0265970
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0265970&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0265970?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0265970. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.