ArticleBMC musculoskeletal disorders2023
Classifying patients with non-specific chronic low back pain using the impact stratification score in an online convenience sample.
Article in BMC musculoskeletal disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 3 citations in OpenAlex.
- A Tilburg Frailty Indicator (TFI)-based frailty classification model for older maintenance hemodialysis patients: a cross-sectional study.BMC geriatrics · 2026Article
- Research Trends and Insights in Chronic Nonspecific Low Back Pain: Bibliometric Analysis (1996-2025).Pain research & management · 2026Review
- Longitudinal validation of the PROMIS-16 in a sample of adults in the United States with back pain.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025Article
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5 authors at 2 institutions in 1 country.
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Abstract
backgroundIn 2014, the National Institute of Health Pain Consortium's research task force (RTF) on research standards for chronic low back pain (CLBP) proposed the Impact Stratification Score (ISS) as a patient-reported outcome measure that could stratify patients by the impact CLBP has on their lives. This work compares three newly developed ISS-based classifications to the RTF's original to provide an optimal recommendation.
methodsThe online sample included 1226 individuals from Amazon's Mechanical Turk who indicated having non-specific CLBP, average age of 40, 49% female, and 67% White. Participants completed the PROMIS-29 v2.1 profile survey that contains the 9 ISS items as well the Roland-Morris Disability Questionnaire (RMDQ) and Graded Chronic Pain Scale (GCPS). Other items included high-impact chronic pain; not working due to health problems; overall health; and number of healthcare visits for back pain in the past 6 months. Three new classifications were created using quartiles (Classification 2), latent profile analysis (Classification 3), and one modeled after the GCPS (Classification 4). Classifications were subsequently compared to the RTF-proposed classification (Classification 1) on several concurrent and prognostic criteria.
resultsClassification 1 had three CLBP severity groups, four in Classification 2, three in Classification 3, and four in Classification 4. All novel classifications improved upon the original. Classification 2 performed best at minimizing the classification of those with negative outcomes into the lowest severity groups at baseline (e.g., 11% with RMDQ ≥ 7) and 6 months (e.g., 8.2% had fair/poor health). Classification 4 performed best at maximizing classification of those with negative outcomes into the most severe group concurrently (e.g., 100% had GCPS grade ≥ 2) and at 6 months (e.g., 100% with RMDQ ≥ 7).
conclusionsWe developed three ISS-based classification schemes and tested them against several outcomes. All three improved upon the original scheme. While appearing more optimal than other classifications in the lowest severity groups, Classification 2 presents some considerations and limitations. Given that Classification 4 was an improvement at the lowest end of severity and was the best at the highest end, it is our tentative recommendation that this approach be adopted to classify individuals with non-specific CLBP.
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