Literature DB >> 32534433

Development of a preliminary multivariable diagnostic prediction model for identifying active spondylolysis in young athletes with low back pain.

Taylor Therriault1, Alexander Rospert1, Mitchell Selhorst2, Anastasia Fischer3.   

Abstract

AIMS: The primary aim of this study was to develop a diagnostic cluster of common clinical findings that would assist in ruling out an active spondylolysis in adolescent athletes with low back pain (LBP).
DESIGN: Retrospective case-series.
SETTING: Hospital-based sports medicine clinic. PATIENTS: One thousand and twenty-five adolescent athletes with LBP (age 15.0 ± 1.8 years, 56% female) were reviewed. Active spondylolytic injuries were identified in 22% (n = 228) of these patients. MAIN OUTCOME MEASURE: presence or absence of active spondylolysis on advanced imaging.
RESULTS: Through logistic regression analysis, pain with extension (p < 0.001), difference between active and resting pain ≥3/10 (p < 0.001), and male sex (p = 0.002) were identified as significantly associated with active spondylolysis. The clinical cluster had a sensitivity of 88% (95% CI 83%-93%) to help rule out active spondylolysis. The negative likelihood ratio was 0.34 (95% CI 0.23-0.51) and the negative predictive value was 90% (95% CI 86%-93%). Diagnostic accuracy of the cluster was acceptable (area under the curve = 0.72 (95% CI 0.69, 0.76; p < 0.001).
CONCLUSION: This study found a cluster of three patient characteristics that may assist in ruling out active spondylolysis in adolescent athletes with LBP.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bone stress injury; Low back pain; Lumbar spine; Stress fracture

Year:  2020        PMID: 32534433     DOI: 10.1016/j.ptsp.2020.05.009

Source DB:  PubMed          Journal:  Phys Ther Sport        ISSN: 1466-853X            Impact factor:   2.365


  2 in total

Review 1.  Back pain in adolescent athletes: a narrative review.

Authors:  Neeraj Vij; Ian Naron; Hannah Tolson; Arthur Rezayev; Alan D Kaye; Omar Viswanath; Ivan Urits
Journal:  Orthop Rev (Pavia)       Date:  2022-08-05

2.  Logistic Model and Gradient Boosting Machine Model for Physical Therapy of Lumbar Disc Herniation.

Authors:  Ping Zhao; Jin Xue; Xiaomei Xu; Lifei Wang; Dan Chen
Journal:  Comput Math Methods Med       Date:  2022-05-11       Impact factor: 2.809

  2 in total

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