Manual therapy and a suggested treatment based classification algorithm in patients with low back pain: a pilot study.
Objectives: The purpose of the study was to describe a classification process of patients with low back pain for physical treatment, present a treatment flow and report on short-term outcome. Methods: A multiple subject case study, using a pretest-posttest design was conducted. As short-term outcome...
| Publicado en: | Journal of Back & Musculoskeletal Rehabilitation Vol. 20; no. 2/3; pp. 61 - 71 |
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| Autores principales: | , , |
| Formato: | algorithm research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2007
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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=106012944&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 106012944 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10538127 3MD jtl: Journal of Back & Musculoskeletal Rehabilitation issn: 10538127 maglogo: N pubinfo: dt: 2007 vid: 20 iid: 2/3 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 106012944 106012944 2009776052 10.3233/bmr-2007-202-303 106012944 ppf: 61 ppct: 10 formats: tig: atl: Manual therapy and a suggested treatment based classification algorithm in patients with low back pain: a pilot study. aug: au: Widerstrom B Olofson N Arvidsson I affil: Fysioterapi-och Idrottsskade Metropolen, Ostersund, Sweden; birgitta.widerstrom@bredband.net sug: subj: Algorithms Low Back Pain Therapy Adult Aged Aged, 80 and Over Ambulatory Care Facilities Convenience Sample Female Funding Source Low Back Pain Classification Male Manual Therapy Methods Middle Age Physical Therapy Methods Pilot Studies Pretest-Posttest Design Questionnaires Scales Severity of Illness Indices Short Form-36 Health Survey (SF-36) Sweden Treatment Outcomes Human Adult: 19-44 years Aged: 65+ years Aged, 80 & over Middle Aged: 45-64 years Female Male ab: Objectives: The purpose of the study was to describe a classification process of patients with low back pain for physical treatment, present a treatment flow and report on short-term outcome. Methods: A multiple subject case study, using a pretest-posttest design was conducted. As short-term outcome measurements, Borg CR 10 pain intensity scale, Oswestry Low Back Pain Disability Questionnaire and the Physical Health Scale from SF36 were used. The subjects were a consecutive sample of 16 adult patients with low back pain, at a physiotherapy clinic in primary care. Inclusion criteria were low back pain, with or without radiating pain and regardless of duration. Exclusion criteria were pregnancy, previous back surgery, and known rheumatic or neurological disease. Patient interview, physical evaluation and two self-reported measurements were decisive for classification to one of four different treatments; pain modulation, stabilization exercise, mobilization, and training. Patients were treated and followed for up to twelve weeks after classification, and compared to baseline measurements at discharge. No comparisons between patients were made. Results: A clinical decision-making algorithm was constructed according to the differences in clinical presentations. A treatment flowchart describes how improved clinical status results in treatment adaptation. Improvements on all short-term outcome measurements were noted in the majority of patients. Conclusion: This pilot study describes an individualized clinical-decision algorithm for sub-grouping patients with low back pain into one of four treatment-based classifications: pain modulation, stabilization exercise, mobilization, and training. The follow up on classification, showing improvements in pain and disability scores at the individual level, suggests that the presented model may be used when clinical decisions on interventions for patients with chronic low back pain are made. pubtype: Academic Journal doctype: algorithm research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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