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Identification of clinical phenotypes in knee osteoarthritis: a systematic review of the literature

Overview of attention for article published in BMC Musculoskeletal Disorders, October 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

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1 news outlet
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22 X users
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2 Facebook pages

Citations

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226 Dimensions

Readers on

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364 Mendeley
Title
Identification of clinical phenotypes in knee osteoarthritis: a systematic review of the literature
Published in
BMC Musculoskeletal Disorders, October 2016
DOI 10.1186/s12891-016-1286-2
Pubmed ID
Authors

A. Dell’Isola, R. Allan, S. L. Smith, S. S. P. Marreiros, M. Steultjens

Abstract

Knee Osteoarthritis (KOA) is a heterogeneous pathology characterized by a complex and multifactorial nature. It has been hypothesised that these differences are due to the existence of underlying phenotypes representing different mechanisms of the disease. The aim of this study is to identify the current evidence for the existence of groups of variables which point towards the existence of distinct clinical phenotypes in the KOA population. A systematic literature search in PubMed was conducted. Only original articles were selected if they aimed to identify phenotypes of patients aged 18 years or older with KOA. The methodological quality of the studies was independently assessed by two reviewers and qualitative synthesis of the evidence was performed. Strong evidence for existence of specific phenotypes was considered present if the phenotype was supported by at least two high-quality studies. A total of 24 studies were included. Through qualitative synthesis of evidence, six main sets of variables proposing the existence of six phenotypes were identified: 1) chronic pain in which central mechanisms (e.g. central sensitisation) are prominent; 2) inflammatory (high levels of inflammatory biomarkers); 3) metabolic syndrome (high prevalence of obesity, diabetes and other metabolic disturbances); 4) Bone and cartilage metabolism (alteration in local tissue metabolism); 5) mechanical overload characterised primarily by varus malalignment and medial compartment disease; and 6) minimal joint disease characterised as minor clinical symptoms with slow progression over time. This study identified six distinct groups of variables which should be explored in attempts to better define clinical phenotypes in the KOA population.

X Demographics

X Demographics

The data shown below were collected from the profiles of 22 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 364 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 1 <1%
Unknown 363 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 56 15%
Student > Master 49 13%
Researcher 40 11%
Other 28 8%
Student > Bachelor 23 6%
Other 52 14%
Unknown 116 32%
Readers by discipline Count As %
Medicine and Dentistry 89 24%
Nursing and Health Professions 32 9%
Biochemistry, Genetics and Molecular Biology 19 5%
Agricultural and Biological Sciences 18 5%
Engineering 13 4%
Other 53 15%
Unknown 140 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 26 August 2020.
All research outputs
#1,513,076
of 23,577,761 outputs
Outputs from BMC Musculoskeletal Disorders
#283
of 4,162 outputs
Outputs of similar age
#28,525
of 321,842 outputs
Outputs of similar age from BMC Musculoskeletal Disorders
#4
of 68 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,162 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 92% 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 321,842 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 91% of its contemporaries.
We're also able to compare this research output to 68 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 94% of its contemporaries.