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Using quantitative sensory testing to predict attrition in an interdisciplinary pain management program: a pilot

Jason Zafereo1, Brittany Uhlenbrock1, Seth Watson2

  • 1Department of Physical Therapy, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.

Pain Management
|March 29, 2022
PubMed
Summary
This summary is machine-generated.

Quantitative sensory testing (QST) can predict patient dropout in interdisciplinary pain programs (IPPs). Higher pain intensity and cold hyperalgesia indicate a greater risk of attrition, offering a novel clinical tool.

Keywords:
attritioncentral sensitizationchronic paininterdisciplinary pain management programquantitative sensory testing

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Area of Science:

  • Pain Medicine
  • Clinical Psychology

Background:

  • Interdisciplinary pain programs (IPPs) aim to improve patient outcomes.
  • Patient attrition from IPPs can hinder treatment effectiveness.
  • Predicting attrition is crucial for optimizing patient care and resource allocation.

Purpose of the Study:

  • To investigate the predictive value of quantitative sensory testing (QST) for attrition in an IPP.
  • To identify specific QST measures associated with patient dropout.

Main Methods:

  • Fifty-three participants in an IPP completed pretreatment quantitative sensory testing (QST) and the PROMIS-29 quality of life survey.
  • Statistical analyses were performed to compare completers and non-completers and to identify predictors of attrition.

Main Results:

  • Non-completers (24.5%) reported significantly higher pain intensity compared to completers.
  • Non-completers also exhibited significantly greater cold hyperalgesia.
  • Both higher pain intensity and cold hyperalgesia predicted attrition from the IPP.

Conclusions:

  • Quantitative sensory testing (QST) shows potential as a tool to predict patient dropout from interdisciplinary pain programs (IPPs).
  • Elevated pain intensity and the presence of cold hyperalgesia may identify patients at higher risk of attrition.
  • These findings suggest a novel clinical application for QST in pain management settings.