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The Intra- and Inter-Evaluator Reliability of Coronal Plane Vertebra Displacement Measurements on Spinal Ultrasound Images of Adolescents with Idiopathic Scoliosis.

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Answer to the letter to the editor of Q. Hao, et al. concerning "Identifying predictors of brace treatment outcomes for adolescents or adults with idiopathic scoliosis: a systematic review" by khodaei, et al. (Eur spine J [2025]: doi: 10.1007/s00586-025-08736-w).

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Clinical Efficacy of Ultrasound-Assisted Scoliosis-Specific Exercise in Mild-Grade Adolescent Idiopathic Scoliosis
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Prescriptive analytics applied to brace treatment for AIS: a pilot demonstration.

Eric Chalmers1, Doug Hill2, Vicky Zhao1

  • 1Electrical & Computer Engineering Department, University of Alberta, 9107 116 Street, Edmonton, Alberta, Canada, T6V 2V4.

Scoliosis
|March 28, 2015
PubMed
Summary

Prescriptive analytics can optimize scoliosis brace corrections, potentially reducing progression by 26% and allowing for less aggressive, more comfortable bracing for Adolescent Idiopathic Scoliosis (AIS) patients.

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Area of Science:

  • Orthopedics
  • Biomedical Engineering
  • Data Science

Background:

  • Adolescent Idiopathic Scoliosis (AIS) treatment often involves bracing.
  • Prescriptive analytics offers a method to optimize treatment strategies.
  • This study explores using prescriptive analytics for in-brace correction recommendations in AIS.

Purpose of the Study:

  • To estimate the efficacy of prescriptive analytics in recommending optimal in-brace corrections for AIS patients.
  • To assess if model-recommended corrections can improve treatment outcomes compared to actual applied corrections.
  • To inform improved brace design and treatment protocols.

Main Methods:

  • A predictive model was used to determine optimal in-brace corrections for 90 AIS patients based on their data.
  • Clinical Trial Simulation (CTS) estimated the efficacy of these model-recommended corrections.
  • Permutation tests were used to calculate statistical significance.

Main Results:

  • Model-recommended corrections varied, with some cases suggesting less aggressive corrections than historically applied.
  • Clinical Trial Simulation estimated a 26% reduction in progressive cases with model-recommended corrections (p=0.05).
  • Patients receiving decreased correction under the model's recommendation did not experience increased progression.

Conclusions:

  • Optimal in-brace correction may be less than the maximum achievable.
  • Integrating model-generated recommendations into brace fitting shows promise for improving AIS outcomes.
  • Future research will expand the system to include wear-time recommendations, enhancing clinical utility.