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Repeat Cardiovascular Risk Assessment after Four Years: Is There Improvement in Risk Prediction?

Overview of attention for article published in PLoS ONE, February 2016
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  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

Mentioned by

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4 tweeters

Citations

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4 Dimensions

Readers on

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17 Mendeley
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Title
Repeat Cardiovascular Risk Assessment after Four Years: Is There Improvement in Risk Prediction?
Published in
PLoS ONE, February 2016
DOI 10.1371/journal.pone.0147417
Pubmed ID
Authors

Parinya Chamnan, Rebecca K. Simmons, Stephen J. Sharp, Kay-Tee Khaw, Nicholas J. Wareham, Simon J. Griffin

Abstract

Framingham risk equations are widely used to predict cardiovascular disease based on health information from a single time point. Little is known regarding use of information from repeat risk assessments and temporal change in estimated cardiovascular risk for prediction of future cardiovascular events. This study was aimed to compare the discrimination and risk reclassification of approaches using estimated cardiovascular risk at single and repeat risk assessments. Using data on 12,197 individuals enrolled in EPIC-Norfolk cohort, with 12 years of follow-up, we examined rates of cardiovascular events by levels of estimated absolute risk (Framingham risk score) at the first and second health examination four years later. We calculated the area under the receiver operating characteristic curve (aROC) and risk reclassification, comparing approaches using information from single and repeat risk assessments (i.e., estimated risk at different time points). The mean Framingham risk score increased from 15.5% to 17.5% over a mean of 3.7 years from the first to second health examination. Individuals with high estimated risk (≥20%) at both health examinations had considerably higher rates of cardiovascular events than those who remained in the lowest risk category (<10%) in both health examinations (34.0 [95%CI 31.7-36.6] and 2.7 [2.2-3.3] per 1,000 person-years respectively). Using information from the most up-to-date risk assessment resulted in a small non-significant change in risk classification over the previous risk assessment (net reclassification improvement of -4.8%, p>0.05). Using information from both risk assessments slightly improved discrimination compared to information from a single risk assessment (aROC 0.76 and 0.75 respectively, p<0.001). Using information from repeat risk assessments over a period of four years modestly improved prediction, compared to using data from a single risk assessment. However, this approach did not improve risk classification.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 6%
Unknown 16 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 29%
Unspecified 3 18%
Student > Postgraduate 2 12%
Student > Master 2 12%
Student > Bachelor 2 12%
Other 3 18%
Readers by discipline Count As %
Medicine and Dentistry 7 41%
Unspecified 4 24%
Nursing and Health Professions 3 18%
Agricultural and Biological Sciences 1 6%
Social Sciences 1 6%
Other 1 6%

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 06 April 2019.
All research outputs
#7,032,589
of 13,594,271 outputs
Outputs from PLoS ONE
#60,891
of 144,101 outputs
Outputs of similar age
#98,978
of 266,658 outputs
Outputs of similar age from PLoS ONE
#2,313
of 5,415 outputs
Altmetric has tracked 13,594,271 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 144,101 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.2. This one has gotten more attention than average, scoring higher than 56% 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 266,658 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 61% of its contemporaries.
We're also able to compare this research output to 5,415 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.