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Clinical assessment of patients with chest pain; a systematic review of predictive tools

Overview of attention for article published in BMC Cardiovascular Disorders, January 2016
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (73rd percentile)

Mentioned by

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7 tweeters

Citations

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15 Dimensions

Readers on

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119 Mendeley
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Title
Clinical assessment of patients with chest pain; a systematic review of predictive tools
Published in
BMC Cardiovascular Disorders, January 2016
DOI 10.1186/s12872-016-0196-4
Pubmed ID
Authors

Luis Ayerbe, Esteban González, Valentina Gallo, Claire L. Coleman, Andrew Wragg, John Robson

Abstract

The clinical assessment of patients with chest pain of recent onset remains difficult. This study presents a critical review of clinical predictive tools for the assessment of patients with chest pain. Systematic review of observational studies and estimation of probabilities of coronary artery disease (CAD) in patients with chest pain. Searches were conducted in PubMed, Embase, Scopus, and Web of Science to identify studies reporting tools, with at least three variables from clinical history, physical examination or ECG, produced with multivariate analysis, to estimate probabilities of CAD in patients with chest pain of recent onset, published from inception of the database to the 31(st) July 2015. The references of previous relevant reviews were hand searched. The methodological quality was assessed with standard criteria. Since the incidence of CAD has changed in the past few decades, the date of publication was acknowledged to be relevant in order to use the tool in clinical practice, and more recent papers were considered more relevant. Probabilities of CAD according to the studies of highest quality were estimated and the evidence provided was graded. Twelve papers were included out of the 19126 references initially identified. The methodological quality of all of them was high. The clinical characteristics of the chest pain, age, past medical history of cardiovascular disease, gender, and abnormalities in the ECG were the predictors of CAD most commonly reported across the studies. The most recent papers, with highest methodological quality, and most practical for use in clinical settings, reported prediction or exclusion of CAD with area under the curve 0.90 in Primary Care, 0.91 in Emergency department, and 0.79 in Cardiology. These papers provide evidence of high level (1B) and the recommendation to use their results in the management of patients with chest pain is strong (A). The risk of CAD can be estimated on clinical grounds in patients with chest pain in different clinical settings with high accuracy. The estimation of probabilities of CAD presented in these studies could be used for a better management of patients with chest pain and also in the development of future predictive tools.

Twitter Demographics

The data shown below were collected from the profiles of 7 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 119 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Argentina 1 <1%
Unknown 118 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 20 17%
Other 12 10%
Researcher 10 8%
Student > Master 10 8%
Student > Postgraduate 7 6%
Other 21 18%
Unknown 39 33%
Readers by discipline Count As %
Medicine and Dentistry 47 39%
Nursing and Health Professions 17 14%
Psychology 3 3%
Engineering 2 2%
Environmental Science 2 2%
Other 8 7%
Unknown 40 34%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 05 March 2016.
All research outputs
#4,485,015
of 16,207,511 outputs
Outputs from BMC Cardiovascular Disorders
#209
of 1,060 outputs
Outputs of similar age
#90,889
of 344,997 outputs
Outputs of similar age from BMC Cardiovascular Disorders
#1
of 1 outputs
Altmetric has tracked 16,207,511 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 1,060 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done well, scoring higher than 79% 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 344,997 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 73% of its contemporaries.
We're also able to compare this research output to 1 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