ArticlePloS one2020
Predicting who responds to spinal manipulative therapy using a short-time frame methodology: Results from a 238-participant study.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Baseline individual factors associated with clinical outcomes in adults with non-specific low back pain following manual therapy: a systematic review.BMC complementary medicine and therapies · 2025Pooled it
- Comfort during side posture lumbopelvic manipulation in a low back pain population-effects of a typical versus modified flexed lumbopelvic position: a crossover randomized control trial.Chiropractic & manual therapies · 2025Trial
- Prognostic factors associated with improvement in patients with an episode of non-specific low back pain without radicular syndrome: a prospective observational exploratory study.Chiropractic & manual therapies · 2025Observational
- The effect of Schroth Therapy combined with spinal manipulation for the treatment of adolescent idiopathic scoliosis.Pakistan journal of medical sciences · 2025Article
- Comprehensive immune profiling and predictive modelling of paediatric acute hepatitis of unknown aetiology from a Spanish cohort.Frontiers in immunology · 2025Article
- Clinical Effectiveness and Efficacy of Chiropractic Spinal Manipulation for Spine Pain.Frontiers in pain research (Lausanne, Switzerland) · 2021Review
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundSpinal manipulative therapy (SMT) is among the nonpharmacologic interventions that has been recommended in clinical guidelines for patients with low back pain, however, some patients appear to benefit substantially more from SMT than others. Several investigations have examined potential factors to modify patients' responses prior to SMT application. The objective of this study was to determine if the baseline prediction of SMT responders can be improved through the use of a restricted, non-pragmatic methodology, established variables of responder status, and newly developed physical measures observed to change with SMT. MATERIALS AND
methodsWe conducted a secondary analysis of a prior study that provided two applications of standardized SMT over a period of 1 week. After initial exploratory analysis, principal component analysis and optimal scaling analysis were used to reduce multicollinearity among predictors. A multiple logistic regression model was built using a forward Wald procedure to explore those baseline variables that could predict response status at 1-week reassessment.
resultsTwo hundred and thirty-eight participants completed the 1-week reassessment (age 40.0± 11.8 years; 59.7% female). Response to treatment was predicted by a model containing the following 8 variables: height, gender, neck or upper back pain, pain frequency in the past 6 months, the STarT Back Tool, patients' expectations about medication and strengthening exercises, and extension status. Our model had a sensitivity of 72.2% (95% CI, 58.1-83.1), specificity of 84.2% (95% CI, 78.0-89.0), a positive likelihood ratio of 4.6 (CI, 3.2-6.7), a negative likelihood ratio of 0.3 (CI, 0.2-0.5), and area under ROC curve, 0.79.
conclusionIt is possible to predict response to treatment before application of SMT in low back pain patients. Our model may benefit both patients and clinicians by reducing the time needed to re-evaluate an initial trial of care.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.