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Epidemiological characteristics of chronic fatigue- syndrome/myalgic encephalomyelitis in Australian patients

Overview of attention for article published in Clinical Epidemiology, May 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#31 of 780)
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

news
4 news outlets
blogs
2 blogs
policy
1 policy source
twitter
33 X users
facebook
12 Facebook pages

Citations

dimensions_citation
38 Dimensions

Readers on

mendeley
82 Mendeley
Title
Epidemiological characteristics of chronic fatigue- syndrome/myalgic encephalomyelitis in Australian patients
Published in
Clinical Epidemiology, May 2016
DOI 10.2147/clep.s96797
Pubmed ID
Authors

Samantha C Johnston, Donald R Staines, Sonya M Marshall-Gradisnik

Abstract

No epidemiological investigations have previously been conducted in Australia according to the current clinical definitions of chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME). The aim of this study was to describe sociodemographic and illness characteristics of Australian patients with CFS/ME. A cross-sectional survey on the medical history of patients enrolled in an Australian CFS/ME research database between April 2013 and April 2015. Participants were classified according to Fukuda criteria and International Consensus Criteria. A total of 535 patients diagnosed with CFS/ME by a primary care physician were identified. The mean age of all patients was 46.4 years (standard deviation 12.0); the majority were female (78.61%), Caucasian, and highly educated. Of these, 30.28% met Fukuda criteria. A further 31.96% met both Fukuda criteria and International Consensus Criteria. There were 14.58% reporting chronic fatigue but did not meet criteria for CFS/ME and 23.18% were considered noncases due to exclusionary conditions. Within those meeting CFS/ME criteria, the most common events prior to illness included cold or flu, gastrointestinal illness, and periods of undue stress. Of the 60 symptoms surveyed, fatigue, cognitive, and short-term memory symptoms, headaches, muscle and joint pain, unrefreshed sleep, sensory disturbances, muscle weakness, and intolerance to extremes of temperature were the most commonly occurring symptoms (reported by more than two-thirds of patients). Significant differences in symptom occurrence between Fukuda- and International Consensus Criteria-defined cases were also identified. This is the first study to summarize sociodemographic and illness characteristics of a cohort of Australian CFS/ME patients. This is vital for identifying potential risk factors and predictors associated with CFS/ME and for guiding decisions regarding health care provision, diagnosis, and management.

X Demographics

X Demographics

The data shown below were collected from the profiles of 33 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 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 82 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 17%
Student > Bachelor 13 16%
Other 8 10%
Researcher 7 9%
Student > Doctoral Student 5 6%
Other 14 17%
Unknown 21 26%
Readers by discipline Count As %
Medicine and Dentistry 18 22%
Nursing and Health Professions 13 16%
Psychology 5 6%
Agricultural and Biological Sciences 4 5%
Biochemistry, Genetics and Molecular Biology 4 5%
Other 16 20%
Unknown 22 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 64. 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 09 February 2022.
All research outputs
#677,287
of 25,582,611 outputs
Outputs from Clinical Epidemiology
#31
of 780 outputs
Outputs of similar age
#12,056
of 312,290 outputs
Outputs of similar age from Clinical Epidemiology
#2
of 18 outputs
Altmetric has tracked 25,582,611 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 780 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.7. This one has done particularly well, scoring higher than 96% 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 312,290 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 96% of its contemporaries.
We're also able to compare this research output to 18 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.