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Can pathoanatomical pathways of degeneration in lumbar motion segments be identified by clustering MRI findings

Overview of attention for article published in BMC Musculoskeletal Disorders, July 2013
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3 X users

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11 Dimensions

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62 Mendeley
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Title
Can pathoanatomical pathways of degeneration in lumbar motion segments be identified by clustering MRI findings
Published in
BMC Musculoskeletal Disorders, July 2013
DOI 10.1186/1471-2474-14-198
Pubmed ID
Authors

Rikke K Jensen, Tue S Jensen, Per Kjaer, Peter Kent

Abstract

Magnetic Resonance Imaging (MRI) is the gold standard for detailed visualisation of spinal pathological and degenerative processes, but the prevailing view is that such imaging findings have little or no clinical relevance for low back pain. This is because these findings appear to have little association with treatment effects in clinical populations, and mostly a weak association with the presence of pain in the general population.However, almost all research into these associations is based on the examination of individual MRI findings, despite its being very common for multiple MRI findings to coexist. Therefore, this proof-of-concept study investigated the capacity of a multivariable statistical method to identify clusters of MRI findings and for those clusters to be grouped into pathways of vertebral degeneration.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
United States 1 2%
Unknown 60 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 21%
Researcher 7 11%
Student > Master 7 11%
Other 6 10%
Student > Doctoral Student 5 8%
Other 10 16%
Unknown 14 23%
Readers by discipline Count As %
Medicine and Dentistry 23 37%
Nursing and Health Professions 10 16%
Engineering 3 5%
Computer Science 2 3%
Agricultural and Biological Sciences 1 2%
Other 5 8%
Unknown 18 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 22 July 2020.
All research outputs
#14,572,791
of 23,341,064 outputs
Outputs from BMC Musculoskeletal Disorders
#2,185
of 4,138 outputs
Outputs of similar age
#111,382
of 196,081 outputs
Outputs of similar age from BMC Musculoskeletal Disorders
#45
of 75 outputs
Altmetric has tracked 23,341,064 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,138 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
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 196,081 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 75 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.