Evidence map›Paper›PMID 40968376›Full record

SynthesisBMC complementary medicine and therapies2025

Baseline individual factors associated with clinical outcomes in adults with non-specific low back pain following manual therapy: a systematic review.

Gaetan Barbier, Mathieu Picchiottino, Arnaud Delafontaine, Guillaume Goncalves, André Bussières, François Cottin, Arnaud Lardon

Abstract readSystematic Review
In one paragraph

Synthesis in BMC complementary medicine and therapies, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Gaetan BarbierCIAMS, Université Paris-Saclay, 91405, Orsay Cedex, France. gbarbier@ifec.net.ORCID http://orcid.org/0000-0001-8613-7777
Mathieu PicchiottinoInstitut Franco-Européen de Chiropraxie, 94200, Ivry-Sur-Seine, France.ORCID http://orcid.org/0000-0002-3086-9909
Arnaud DelafontaineCIAMS, Université Paris-Saclay, 91405, Orsay Cedex, France.ORCID http://orcid.org/0000-0002-3093-0183
Guillaume GoncalvesInstitut Franco-Européen de Chiropraxie, 94200, Ivry-Sur-Seine, France.ORCID http://orcid.org/0000-0002-1992-1876
André BussièresUniversité du Québec À Trois-Rivières, Trois-Rivières, Québec, Canada.ORCID http://orcid.org/0000-0002-2818-6949
François CottinUniversité Paris-Saclay, Inria, CIAMS, Gif-Sur-Yvette, 91190, France.ORCID http://orcid.org/0000-0002-7950-2163
Arnaud LardonCIAMS, Université Paris-Saclay, 91405, Orsay Cedex, France.ORCID http://orcid.org/0000-0002-0935-445X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrimary care providers consider the identification of patient subgroups as a high research priority. Unfortunately, evidence to support the benefit of treatments targeting subgroups of patients with NSLBP remains inconsistent. Specifically, little is known about baseline individual patient characteristics associated with optimal clinical improvement from manual therapy. This systematic review aims to identify baseline individual factors (BIFs), including patient characteristics, self-reported questionnaires, clinical examination, and ancillary test factors associated with clinical improvement (or lack of) among adult patients with Non-Specific Low Back Pain (NSLBP) following manual therapy.

methodsA systematic review of published evidence in Medline, Embase, Cochrane, Index To Chiropractic Literature, and CINAHL was conducted until April 2024. Studies included participants aged 18 years and over with NSLBP and without radiculopathy. Participants received manual therapies, including musculoskeletal manipulation/mobilization (spinal and extremities) and soft tissue therapy. We excluded mechanically assisted manipulations and interventions mainly involving exercise, education, and/or advice. Two independent assessors screened studies for inclusion, extracted data, and assessed risks of bias using the Quality In Prognosis Studies (QUIPS) Tools. A qualitative synthesis of findings was undertaken. BIFs were synthesized according to patient-reported outcomes measure domains: 1) pain intensity measures, 2) disability measures, 3) global perceived effect, and 4) other factors (e.g., satisfaction with care, total number of visits).

resultsData from 19 studies (reported in 21 articles) involving 4,689 participants were analyzed. Twelve studies reported pain intensity, 18 reported disability outcomes, and 4 reported patient's global perceived effect. Over 70% of the included studies had a high risk of confounding bias. Included studies explored the potential association between clinical outcomes and 172 BIFs. BIFs were categorized into patient characteristics (n = 40), self-reported questionnaire (n = 31), clinical examination (n = 82), and ancillary tests (n = 20). Fourteen multivariate models explored the association with clinical improvement, and four others investigated the association with non-improvement. Findings were inconsistent across studies.

conclusionUsing BIFs in clinical practice to predict clinical outcomes following manual therapy treatment appears to be premature. Future studies should aim to replicate the results and differentiate prognostic factors from treatment effect modifiers.

trial registrationCRD42019131416.

Indexed as

Low Back PainMusculoskeletal ManipulationsAdultHumansTreatment OutcomeClinical outcomesLow back painMusculoskeletal manipulationsPhysical examinationPopulation characteristicsPrognosis factorsSurveys and questionnairesSystematic reviewTreatment effect modifier

Identifiers

PMID40968376
PMCPMC12447601

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.