Evaluation of a Treatment-Based Classification Algorithm for Low Back Pain: A Cross-Sectional Study.
Background. Several studies have investigated criteria for classifying patientswith low back pain (LBP) into treatment-based subgroups. A comprehensive algorithm was created to translate these criteria into a clinical decision-making guide. Objective. This study investigated the translation of the i...
| Publicado en: | Physical Therapy Vol. 91; no. 4; pp. 496 - 510 |
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| Autores principales: | , , , , , , |
| Formato: | algorithm research tables/charts Journal Article |
| Publicado: |
Oxford University Press / USA
Apr2011
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104868988&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104868988 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00319023 PTH jtl: Physical Therapy issn: 00319023 maglogo: N pubinfo: dt: Apr2011 vid: 91 iid: 4 pid: 10398 pub: Oxford University Press / USA artinfo: ui: 104868988 59908331 10.2522/ptj.20100272 NLM21330450 104868988 ppf: 496 ppct: 14 formats: fmt: @attributes: type: P tig: atl: Evaluation of a Treatment-Based Classification Algorithm for Low Back Pain: A Cross-Sectional Study. aug: au: Stanton, Tasha R. Fritz, Julie M. Hancock, Mark J. Latimer, Jane Maher, Christopher G. Wand, Benedict M. Parent, Eric C. affil: PhD student in the Musculoskeletal Division, The George Institute for Global Health and Sydney Medical School, The University of Sydney. sug: subj: Low Back Pain Classification Physical Therapy Low Back Pain Symptoms Human Cross Sectional Studies Nonexperimental Studies Acute Disease Utah New South Wales Exercise Test Prevalence Test-Retest Reliability Interrater Reliability Clinical Assessment Tools Questionnaires Scales Physical Examination Adult Female Male Sample Size kappa Statistic Confidence Intervals Low Back Pain Therapy External Validity Funding Source Low Back Pain Physiopathology Adult: 19-44 years Female Male ab: Background. Several studies have investigated criteria for classifying patientswith low back pain (LBP) into treatment-based subgroups. A comprehensive algorithm was created to translate these criteria into a clinical decision-making guide. Objective. 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. Design. This was a cross-sectional, observational study. Methods. 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. Results. 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% CI43.4%-55.8%) of the participants met the criteria for only one subgroup, and 25.2% (95% CI19.8%-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 (kappa0.52, 95% CI0.27- 0.77, percentage of agreement67%).Limitations. Due to a relatively small patient sample, reliability estimates aresomewhat imprecise. Conclusions. 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. pubtype: Academic Journal doctype: algorithm research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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