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Associations between signs and symptoms of dry eye disease: a systematic review

Overview of attention for article published in Clinical Ophthalmology, September 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

twitter
2 tweeters
googleplus
1 Google+ user

Citations

dimensions_citation
129 Dimensions

Readers on

mendeley
120 Mendeley
Title
Associations between signs and symptoms of dry eye disease: a systematic review
Published in
Clinical Ophthalmology, September 2015
DOI 10.2147/opth.s89700
Pubmed ID
Authors

Jimmy Bartlett, Michael Keith, Lavanya Sudharshan, Sonya Snedecor

Abstract

The accurate diagnosis and classification of dry eye disease (DED) is challenging owing to wide variations in symptoms and lack of a single reliable clinical assessment. In addition, changes and severity of clinical signs often do not correspond to patient-reported symptoms. To better understand the inconsistencies observed between signs and symptoms, we conducted a systematic literature review to evaluate published studies reporting associations between patient-reported symptoms and clinical signs of DED. PubMed and Embase were searched for English-language articles on the association between clinical signs and symptoms of DED up to February 2014 (no lower limit was set). Thirty-four articles were identified that assessed associations between signs and symptoms, among which 33 unique studies were reported. These included 175 individual sign-symptom association analyses. Statistical significance was reported for associations between sign and symptom measures in 21 of 33 (64%) studies, but for only 42 of 175 (24%) individual analyses. Of 175 individual analyses, 148 reported correlation coefficients, of which the majority (129/148; 87%) were between -0.4 and 0.4, indicating low-to-moderate correlation. Of all individual analyses that demonstrated a statistically significant association, one-half (56%) of reported correlation coefficients were in this range. No clear trends were observed in relation to the strength of associations relative to study size, statistical methods, or study region, although results from three studies did suggest that disease severity may be a factor. Associations between DED signs and symptoms are low and inconsistent, which may have implications for monitoring the response to treatment, both in the clinic and in clinical trials. Further studies to increase understanding of the etiopathogenesis of DED and to identify the most reliable and relevant measures of disease are needed to enhance clinical assessment of DED and the measurement of response to therapeutic interventions.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Austria 1 <1%
Unknown 118 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 14%
Student > Ph. D. Student 16 13%
Student > Master 15 13%
Other 13 11%
Student > Bachelor 13 11%
Other 23 19%
Unknown 23 19%
Readers by discipline Count As %
Medicine and Dentistry 55 46%
Nursing and Health Professions 12 10%
Agricultural and Biological Sciences 4 3%
Biochemistry, Genetics and Molecular Biology 4 3%
Psychology 4 3%
Other 13 11%
Unknown 28 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 23 September 2015.
All research outputs
#7,249,283
of 14,054,251 outputs
Outputs from Clinical Ophthalmology
#466
of 1,890 outputs
Outputs of similar age
#89,064
of 246,250 outputs
Outputs of similar age from Clinical Ophthalmology
#11
of 84 outputs
Altmetric has tracked 14,054,251 research outputs across all sources so far. This one is in the 47th percentile – i.e., 47% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,890 research outputs from this source. They receive a mean Attention Score of 3.5. This one has gotten more attention than average, scoring higher than 73% 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 246,250 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 84 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.