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Classification of patients with low back-related leg pain: a systematic review

Overview of attention for article published in BMC Musculoskeletal Disorders, May 2016
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

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1 blog
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36 X users
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3 Facebook pages

Citations

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49 Dimensions

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183 Mendeley
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Title
Classification of patients with low back-related leg pain: a systematic review
Published in
BMC Musculoskeletal Disorders, May 2016
DOI 10.1186/s12891-016-1074-z
Pubmed ID
Authors

Siobhán Stynes, Kika Konstantinou, Kate M. Dunn

Abstract

The identification of clinically relevant subgroups of low back pain (LBP) is considered the number one LBP research priority in primary care. One subgroup of LBP patients are those with back related leg pain. Leg pain frequently accompanies LBP and is associated with increased levels of disability and higher health costs than simple low back pain. Distinguishing between different types of low back-related leg pain (LBLP) is important for clinical management and research applications, but there is currently no clear agreement on how to define and identify LBLP due to nerve root involvement. The aim of this systematic review was to identify, describe and appraise papers that classify or subgroup populations with LBLP, and summarise how leg pain due to nerve root involvement is described and diagnosed in the various systems. The search strategy involved nine electronic databases including Medline and Embase, reference lists of eligible studies and relevant reviews. Selected papers were appraised independently by two reviewers using a standardised scoring tool. Of 13,358 initial potential eligible citations, 50 relevant papers were identified that reported on 22 classification systems. Papers were grouped according to purpose and criteria of the classification systems. Five themes emerged: (i) clinical features (ii) pathoanatomy (iii) treatment-based approach (iv) screening tools and prediction rules and (v) pain mechanisms. Three of the twenty two systems focused specifically on LBLP populations. Systems that scored highest following quality appraisal were ones where authors generally included statistical methods to develop their classifications, and supporting work had been published on the systems' validity, reliability and generalisability. There was lack of consistency in how LBLP due to nerve root involvement was described and diagnosed within the systems. Numerous classification systems exist that include patients with leg pain, a minority of them focus specifically on distinguishing between different presentations of leg pain. Further work is needed to identify clinically meaningful subgroups of LBLP patients, ideally based on large primary care cohort populations and using recommended methods for classification system development.

X Demographics

X Demographics

The data shown below were collected from the profiles of 36 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 183 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 <1%
Unknown 182 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 29 16%
Student > Master 24 13%
Other 18 10%
Student > Ph. D. Student 17 9%
Student > Doctoral Student 11 6%
Other 32 17%
Unknown 52 28%
Readers by discipline Count As %
Medicine and Dentistry 50 27%
Nursing and Health Professions 48 26%
Social Sciences 7 4%
Sports and Recreations 5 3%
Agricultural and Biological Sciences 4 2%
Other 15 8%
Unknown 54 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 33. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 February 2022.
All research outputs
#1,063,896
of 23,314,015 outputs
Outputs from BMC Musculoskeletal Disorders
#172
of 4,132 outputs
Outputs of similar age
#20,984
of 334,871 outputs
Outputs of similar age from BMC Musculoskeletal Disorders
#6
of 76 outputs
Altmetric has tracked 23,314,015 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,132 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 334,871 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 76 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.