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Can screening instruments accurately determine poor outcome risk in adults with recent onset low back pain? A systematic review and meta-analysis

Overview of attention for article published in BMC Medicine, January 2017
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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)

Mentioned by

2 blogs
26 tweeters
5 Facebook pages


53 Dimensions

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162 Mendeley
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Can screening instruments accurately determine poor outcome risk in adults with recent onset low back pain? A systematic review and meta-analysis
Published in
BMC Medicine, January 2017
DOI 10.1186/s12916-016-0774-4
Pubmed ID

Emma L. Karran, James H. McAuley, Adrian C. Traeger, Susan L. Hillier, Luzia Grabherr, Leslie N. Russek, G. Lorimer Moseley


Delivering efficient and effective healthcare is crucial for a condition as burdensome as low back pain (LBP). Stratified care strategies may be worthwhile, but rely on early and accurate patient screening using a valid and reliable instrument. The purpose of this study was to evaluate the performance of LBP screening instruments for determining risk of poor outcome in adults with LBP of less than 3 months duration. Medline, Embase, CINAHL, PsycINFO, PEDro, Web of Science, SciVerse SCOPUS, and Cochrane Central Register of Controlled Trials were searched from June 2014 to March 2016. Prospective cohort studies involving patients with acute and subacute LBP were included. Studies administered a prognostic screening instrument at inception and reported outcomes at least 12 weeks after screening. Two independent reviewers extracted relevant data using a standardised spreadsheet. We defined poor outcome for pain to be ≥ 3 on an 11-point numeric rating scale and poor outcome for disability to be scores of ≥ 30% disabled (on the study authors' chosen disability outcome measure). We identified 18 eligible studies investigating seven instruments. Five studies investigated the STarT Back Tool: performance for discriminating pain outcomes at follow-up was 'non-informative' (pooled AUC = 0.59 (0.55-0.63), n = 1153) and 'acceptable' for discriminating disability outcomes (pooled AUC = 0.74 (0.66-0.82), n = 821). Seven studies investigated the Orebro Musculoskeletal Pain Screening Questionnaire: performance was 'poor' for discriminating pain outcomes (pooled AUC = 0.69 (0.62-0.76), n = 360), 'acceptable' for disability outcomes (pooled AUC = 0.75 (0.69-0.82), n = 512), and 'excellent' for absenteeism outcomes (pooled AUC = 0.83 (0.75-0.90), n = 243). Two studies investigated the Vermont Disability Prediction Questionnaire and four further instruments were investigated in single studies only. LBP screening instruments administered in primary care perform poorly at assigning higher risk scores to individuals who develop chronic pain than to those who do not. Risks of a poor disability outcome and prolonged absenteeism are likely to be estimated with greater accuracy. It is important that clinicians who use screening tools to obtain prognostic information consider the potential for misclassification of patient risk and its consequences for care decisions based on screening. However, it needs to be acknowledged that the outcomes on which we evaluated these screening instruments in some cases had a different threshold, outcome, and time period than those they were designed to predict. PROSPERO international prospective register of systematic reviews registration number CRD42015015778 .

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 162 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 <1%
Unknown 161 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 26 16%
Student > Ph. D. Student 23 14%
Researcher 22 14%
Other 20 12%
Student > Bachelor 13 8%
Other 37 23%
Unknown 21 13%
Readers by discipline Count As %
Medicine and Dentistry 56 35%
Nursing and Health Professions 38 23%
Neuroscience 6 4%
Psychology 5 3%
Engineering 4 2%
Other 18 11%
Unknown 35 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 31. 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 20 November 2018.
All research outputs
of 13,887,828 outputs
Outputs from BMC Medicine
of 2,178 outputs
Outputs of similar age
of 348,648 outputs
Outputs of similar age from BMC Medicine
of 2 outputs
Altmetric has tracked 13,887,828 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 2,178 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 35.3. This one has done well, scoring higher than 77% 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 348,648 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 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them