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Cochrane Database of Systematic Reviews

Risk scoring for the primary prevention of cardiovascular disease

Overview of attention for article published in Cochrane database of systematic reviews, March 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

news
2 news outlets
policy
2 policy sources
twitter
16 tweeters
facebook
1 Facebook page
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
77 Dimensions

Readers on

mendeley
284 Mendeley
citeulike
2 CiteULike
Title
Risk scoring for the primary prevention of cardiovascular disease
Published in
Cochrane database of systematic reviews, March 2017
DOI 10.1002/14651858.cd006887.pub4
Pubmed ID
Authors

Kunal N Karmali, Stephen D Persell, Pablo Perel, Donald M Lloyd-Jones, Mark A Berendsen, Mark D Huffman

Abstract

The current paradigm for cardiovascular disease (CVD) emphasises absolute risk assessment to guide treatment decisions in primary prevention. Although the derivation and validation of multivariable risk assessment tools, or CVD risk scores, have attracted considerable attention, their effect on clinical outcomes is uncertain. To assess the effects of evaluating and providing CVD risk scores in adults without prevalent CVD on cardiovascular outcomes, risk factor levels, preventive medication prescribing, and health behaviours. We searched the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library (2016, Issue 2), MEDLINE Ovid (1946 to March week 1 2016), Embase (embase.com) (1974 to 15 March 2016), and Conference Proceedings Citation Index-Science (CPCI-S) (1990 to 15 March 2016). We imposed no language restrictions. We searched clinical trial registers in March 2016 and handsearched reference lists of primary studies to identify additional reports. We included randomised and quasi-randomised trials comparing the systematic provision of CVD risk scores by a clinician, healthcare professional, or healthcare system compared with usual care (i.e. no systematic provision of CVD risk scores) in adults without CVD. Three review authors independently selected studies, extracted data, and evaluated study quality. We used the Cochrane 'Risk of bias' tool to assess study limitations. The primary outcomes were: CVD events, change in CVD risk factor levels (total cholesterol, systolic blood pressure, and multivariable CVD risk), and adverse events. Secondary outcomes included: lipid-lowering and antihypertensive medication prescribing in higher-risk people. We calculated risk ratios (RR) for dichotomous data and mean differences (MD) or standardised mean differences (SMD) for continuous data using 95% confidence intervals. We used a fixed-effects model when heterogeneity (I²) was at least 50% and a random-effects model for substantial heterogeneity (I² > 50%). We evaluated the quality of evidence using the GRADE framework. We identified 41 randomised controlled trials (RCTs) involving 194,035 participants from 6422 reports. We assessed studies as having high or unclear risk of bias across multiple domains. Low-quality evidence evidence suggests that providing CVD risk scores may have little or no effect on CVD events compared with usual care (5.4% versus 5.3%; RR 1.01, 95% confidence interval (CI) 0.95 to 1.08; I² = 25%; 3 trials, N = 99,070). Providing CVD risk scores may reduce CVD risk factor levels by a small amount compared with usual care. Providing CVD risk scores reduced total cholesterol (MD -0.10 mmol/L, 95% CI -0.20 to 0.00; I² = 94%; 12 trials, N = 20,437, low-quality evidence), systolic blood pressure (MD -2.77 mmHg, 95% CI -4.16 to -1.38; I² = 93%; 16 trials, N = 32,954, low-quality evidence), and multivariable CVD risk (SMD -0.21, 95% CI -0.39 to -0.02; I² = 94%; 9 trials, N = 9549, low-quality evidence). Providing CVD risk scores may reduce adverse events compared with usual care, but results were imprecise (1.9% versus 2.7%; RR 0.72, 95% CI 0.49 to 1.04; I² = 0%; 4 trials, N = 4630, low-quality evidence). Compared with usual care, providing CVD risk scores may increase new or intensified lipid-lowering medications (15.7% versus 10.7%; RR 1.47, 95% CI 1.15 to 1.87; I² = 40%; 11 trials, N = 14,175, low-quality evidence) and increase new or increased antihypertensive medications (17.2% versus 11.4%; RR 1.51, 95% CI 1.08 to 2.11; I² = 53%; 8 trials, N = 13,255, low-quality evidence). There is uncertainty whether current strategies for providing CVD risk scores affect CVD events. Providing CVD risk scores may slightly reduce CVD risk factor levels and may increase preventive medication prescribing in higher-risk people without evidence of harm. There were multiple study limitations in the identified studies and substantial heterogeneity in the interventions, outcomes, and analyses, so readers should interpret results with caution. New models for implementing and evaluating CVD risk scores in adequately powered studies are needed to define the role of applying CVD risk scores in primary CVD prevention.

Twitter Demographics

The data shown below were collected from the profiles of 16 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 284 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Netherlands 1 <1%
Unknown 282 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 44 15%
Student > Master 43 15%
Student > Bachelor 33 12%
Student > Ph. D. Student 28 10%
Student > Doctoral Student 20 7%
Other 49 17%
Unknown 67 24%
Readers by discipline Count As %
Medicine and Dentistry 92 32%
Nursing and Health Professions 36 13%
Psychology 12 4%
Social Sciences 9 3%
Biochemistry, Genetics and Molecular Biology 8 3%
Other 44 15%
Unknown 83 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 36. 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 01 January 2021.
All research outputs
#786,854
of 19,515,384 outputs
Outputs from Cochrane database of systematic reviews
#1,865
of 11,948 outputs
Outputs of similar age
#19,465
of 273,177 outputs
Outputs of similar age from Cochrane database of systematic reviews
#60
of 261 outputs
Altmetric has tracked 19,515,384 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,948 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.5. This one has done well, scoring higher than 84% 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 273,177 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 92% of its contemporaries.
We're also able to compare this research output to 261 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.