Evidence map›Paper›PMID 21943396›Full record

ArticleBMC medicine2011

Barriers and progress in the treatment of low back pain.

Nadine E Foster

Abstract readEditorial
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medicine, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 7 pooled it
–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

50 citing papers in PubMed, 7 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Identifying patients with chronic pain who respond to acupuncture: results from an individual patient data meta-analysis.Acupuncture in medicine : journal of the British Medical Acupuncture Society · 2021
    Pooled it
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  5. Multidisciplinary biopsychosocial rehabilitation for subacute low back pain.The Cochrane database of systematic reviews · 2017
    Pooled it
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  7. Multidisciplinary biopsychosocial rehabilitation for chronic low back pain.The Cochrane database of systematic reviews · 2014
    Pooled it
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  16. A meta-model of low back pain to examine collective expert knowledge of treatment effects and their mechanisms.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026
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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

1 author.

Nadine E FosterKeele University, Keele, Staffordshire, UK. n.foster@keele.ac.uk

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Low back pain is a common and costly condition and for most people is likely to be a recurrent problem throughout their lifetime. The management of patients with low back pain has been positively influenced by the rise in high quality clinical trials and systematic reviews in recent decades, and this body of evidence, synthesized in many clinical practice guidelines, has improved our knowledge about which treatments for low back pain are useful and which are not. For the largest group of patients, those with non-specific low back pain for whom a clear diagnosis cannot be given, the reality is that the treatments we have to offer tend to produce small effects, often only in the short term and none appear to effectively change long-term prognosis. This commentary summarizes the array of treatments currently available, notes the results of recent trials and guidelines and considers alternative approaches that may prove more valuable in achieving better patient outcomes in the future.

Indexed as

Biomedical ResearchHumansLow Back PainTreatment Outcome

Identifiers

PMID21943396
PMCPMC3192671

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.