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Evaluation of a Treatment-Based Classification Algorithm for Low Back Pain: A Cross-Sectional Study

Several studies have investigated criteria for classifying patients with low back pain (LBP) into treatment-based subgroups. A comprehensive algorithm was created to translate these criteria into a clinical decision-making guide. This study investigated the translation of the individual subgroup cri... Full description

Journal Title: Physical therapy 2011-04-01, Vol.91 (4), p.496-509
Main Author: Stanton, Tasha R
Other Authors: Fritz, Julie M , Hancock, Mark J , Latimer, Jane , Maher, Christopher G , Wand, Benedict M , Parent, Eric C
Format: Electronic Article Electronic Article
Language: English
Subjects:
Publisher: United States: American Physical Therapy Association
ID: ISSN: 0031-9023
Link: https://www.ncbi.nlm.nih.gov/pubmed/21330450
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recordid: cdi_proquest_miscellaneous_860194959
title: Evaluation of a Treatment-Based Classification Algorithm for Low Back Pain: A Cross-Sectional Study
format: Article
creator:
  • Stanton, Tasha R
  • Fritz, Julie M
  • Hancock, Mark J
  • Latimer, Jane
  • Maher, Christopher G
  • Wand, Benedict M
  • Parent, Eric C
subjects:
  • Abridged Index Medicus
  • Adult
  • Algorithm
  • Algorithms
  • Back pain
  • Care and treatment
  • Classification
  • Cross-Sectional Studies
  • Decision making
  • Decision Support Systems, Clinical
  • Exercise Therapy
  • Female
  • Health aspects
  • Human Movement
  • Humans
  • Hypotheses
  • Low back pain
  • Low Back Pain - classification
  • Low Back Pain - rehabilitation
  • Low Back Pain - therapy
  • Male
  • Manipulation, Orthopedic
  • Middle Aged
  • Physical therapy
  • Reproducibility of Results
  • Research
  • Spinal manipulation
  • Sports Science
  • Studies
  • Teaching hospitals
  • Therapeutics, Physiological
  • Traction
  • Usage
ispartof: Physical therapy, 2011-04-01, Vol.91 (4), p.496-509
description: Several studies have investigated criteria for classifying patients with low back pain (LBP) into treatment-based subgroups. A comprehensive algorithm was created to translate these criteria into a clinical decision-making guide. This study investigated the translation of the individual subgroup criteria into a comprehensive algorithm by studying the prevalence of patients meeting the criteria for each treatment subgroup and the reliability of the classification. This was a cross-sectional, observational study. Two hundred fifty patients with acute or subacute LBP were recruited from the United States and Australia to participate in the study. Trained physical therapists performed standardized assessments on all participants. The researchers used these findings to classify participants into subgroups. Thirty-one participants were reassessed to determine interrater reliability of the algorithm decision. Based on individual subgroup criteria, 25.2% (95% confidence interval [CI]=19.8%-30.6%) of the participants did not meet the criteria for any subgroup, 49.6% (95% CI=43.4%-55.8%) of the participants met the criteria for only one subgroup, and 25.2% (95% CI=19.8%-30.6%) of the participants met the criteria for more than one subgroup. The most common combination of subgroups was manipulation + specific exercise (68.4% of the participants who met the criteria for 2 subgroups). Reliability of the algorithm decision was moderate (kappa=0.52, 95% CI=0.27-0.77, percentage of agreement=67%). Due to a relatively small patient sample, reliability estimates are somewhat imprecise. These findings provide important clinical data to guide future research and revisions to the algorithm. The finding that 25% of the participants met the criteria for more than one subgroup has important implications for the sequencing of treatments in the algorithm. Likewise, the finding that 25% of the participants did not meet the criteria for any subgroup provides important information regarding potential revisions to the algorithm's bottom table (which guides unclear classifications). Reliability of the algorithm is sufficient for clinical use.
language: eng
source:
identifier: ISSN: 0031-9023
fulltext: no_fulltext
issn:
  • 0031-9023
  • 1538-6724
url: Link


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descriptionSeveral studies have investigated criteria for classifying patients with low back pain (LBP) into treatment-based subgroups. A comprehensive algorithm was created to translate these criteria into a clinical decision-making guide. This study investigated the translation of the individual subgroup criteria into a comprehensive algorithm by studying the prevalence of patients meeting the criteria for each treatment subgroup and the reliability of the classification. This was a cross-sectional, observational study. Two hundred fifty patients with acute or subacute LBP were recruited from the United States and Australia to participate in the study. Trained physical therapists performed standardized assessments on all participants. The researchers used these findings to classify participants into subgroups. Thirty-one participants were reassessed to determine interrater reliability of the algorithm decision. Based on individual subgroup criteria, 25.2% (95% confidence interval [CI]=19.8%-30.6%) of the participants did not meet the criteria for any subgroup, 49.6% (95% CI=43.4%-55.8%) of the participants met the criteria for only one subgroup, and 25.2% (95% CI=19.8%-30.6%) of the participants met the criteria for more than one subgroup. The most common combination of subgroups was manipulation + specific exercise (68.4% of the participants who met the criteria for 2 subgroups). Reliability of the algorithm decision was moderate (kappa=0.52, 95% CI=0.27-0.77, percentage of agreement=67%). Due to a relatively small patient sample, reliability estimates are somewhat imprecise. These findings provide important clinical data to guide future research and revisions to the algorithm. The finding that 25% of the participants met the criteria for more than one subgroup has important implications for the sequencing of treatments in the algorithm. Likewise, the finding that 25% of the participants did not meet the criteria for any subgroup provides important information regarding potential revisions to the algorithm's bottom table (which guides unclear classifications). Reliability of the algorithm is sufficient for clinical use.
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subjectAbridged Index Medicus ; Adult ; Algorithm ; Algorithms ; Back pain ; Care and treatment ; Classification ; Cross-Sectional Studies ; Decision making ; Decision Support Systems, Clinical ; Exercise Therapy ; Female ; Health aspects ; Human Movement ; Humans ; Hypotheses ; Low back pain ; Low Back Pain - classification ; Low Back Pain - rehabilitation ; Low Back Pain - therapy ; Male ; Manipulation, Orthopedic ; Middle Aged ; Physical therapy ; Reproducibility of Results ; Research ; Spinal manipulation ; Sports Science ; Studies ; Teaching hospitals ; Therapeutics, Physiological ; Traction ; Usage
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descriptionSeveral studies have investigated criteria for classifying patients with low back pain (LBP) into treatment-based subgroups. A comprehensive algorithm was created to translate these criteria into a clinical decision-making guide. This study investigated the translation of the individual subgroup criteria into a comprehensive algorithm by studying the prevalence of patients meeting the criteria for each treatment subgroup and the reliability of the classification. This was a cross-sectional, observational study. Two hundred fifty patients with acute or subacute LBP were recruited from the United States and Australia to participate in the study. Trained physical therapists performed standardized assessments on all participants. The researchers used these findings to classify participants into subgroups. Thirty-one participants were reassessed to determine interrater reliability of the algorithm decision. Based on individual subgroup criteria, 25.2% (95% confidence interval [CI]=19.8%-30.6%) of the participants did not meet the criteria for any subgroup, 49.6% (95% CI=43.4%-55.8%) of the participants met the criteria for only one subgroup, and 25.2% (95% CI=19.8%-30.6%) of the participants met the criteria for more than one subgroup. The most common combination of subgroups was manipulation + specific exercise (68.4% of the participants who met the criteria for 2 subgroups). Reliability of the algorithm decision was moderate (kappa=0.52, 95% CI=0.27-0.77, percentage of agreement=67%). Due to a relatively small patient sample, reliability estimates are somewhat imprecise. These findings provide important clinical data to guide future research and revisions to the algorithm. The finding that 25% of the participants met the criteria for more than one subgroup has important implications for the sequencing of treatments in the algorithm. Likewise, the finding that 25% of the participants did not meet the criteria for any subgroup provides important information regarding potential revisions to the algorithm's bottom table (which guides unclear classifications). Reliability of the algorithm is sufficient for clinical use.
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abstractSeveral studies have investigated criteria for classifying patients with low back pain (LBP) into treatment-based subgroups. A comprehensive algorithm was created to translate these criteria into a clinical decision-making guide. This study investigated the translation of the individual subgroup criteria into a comprehensive algorithm by studying the prevalence of patients meeting the criteria for each treatment subgroup and the reliability of the classification. This was a cross-sectional, observational study. Two hundred fifty patients with acute or subacute LBP were recruited from the United States and Australia to participate in the study. Trained physical therapists performed standardized assessments on all participants. The researchers used these findings to classify participants into subgroups. Thirty-one participants were reassessed to determine interrater reliability of the algorithm decision. Based on individual subgroup criteria, 25.2% (95% confidence interval [CI]=19.8%-30.6%) of the participants did not meet the criteria for any subgroup, 49.6% (95% CI=43.4%-55.8%) of the participants met the criteria for only one subgroup, and 25.2% (95% CI=19.8%-30.6%) of the participants met the criteria for more than one subgroup. The most common combination of subgroups was manipulation + specific exercise (68.4% of the participants who met the criteria for 2 subgroups). Reliability of the algorithm decision was moderate (kappa=0.52, 95% CI=0.27-0.77, percentage of agreement=67%). Due to a relatively small patient sample, reliability estimates are somewhat imprecise. These findings provide important clinical data to guide future research and revisions to the algorithm. The finding that 25% of the participants met the criteria for more than one subgroup has important implications for the sequencing of treatments in the algorithm. Likewise, the finding that 25% of the participants did not meet the criteria for any subgroup provides important information regarding potential revisions to the algorithm's bottom table (which guides unclear classifications). Reliability of the algorithm is sufficient for clinical use.
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