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Comparison of different vascular risk engines in the identification of type 2 diabetes patients with high cardiovascular risk

Overview of attention for article published in BMC Cardiovascular Disorders, October 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

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Title
Comparison of different vascular risk engines in the identification of type 2 diabetes patients with high cardiovascular risk
Published in
BMC Cardiovascular Disorders, October 2015
DOI 10.1186/s12872-015-0120-3
Pubmed ID
Authors

Antonio Rodriguez-Poncelas, Gabriel Coll-de-Tuero, Marc Saez, José M. Garrido-Martín, José M. Millaruelo-Trillo, Joan Barrot de-la-Puente, Josep Franch-Nadal, on behalf RedGDPS Study Group

Abstract

Some authors consider that secondary prevention should be conducted for all DM2 patients, while others suggest that the drug preventive treatment should start or be increased depending on each patient's individual CVR, estimated using cardiovascular or coronary risk functions to identify the patients with a higher CVR. The principal objective of this study was to assess three different cardiovascular risk prediction models in type 2 diabetes patients. Multicentre, cross-sectional descriptive study of 3,041 patients with type 2 diabetes and no history of cardiovascular disease. The demographic, clinical, analytical, and cardiovascular risk factor variables associated with type 2 diabetes were analysed. The risk function and probability that a cardiovascular disease could occur were estimated using three risk engines: REGICOR, UKPDS and ADVANCE. A patient was considered to have a high cardiovascular risk when REGICOR ≥ 10 % or UKPDS ≥ 15 % in 10 years or when ADVANCE ≥ 8 % in 4 years. The ADVANCE and UKPDS risk engines identified a higher number of diabetic patients with a high cardiovascular risk (24.2 % and 22.7 %, respectively) compared to the REGICOR risk engine (10.2 %). The correlation using the REGICOR risk engine was low compared to UKPDS and ADVANCE (r = 0.288 and r = 0.153, respectively; p < 0.0001). The agreement values in the allocation of a particular patient to the high risk group was low between the REGICOR engine and the UKPDS and ADVANCE engines (k = 0.205 and k = 0.123, respectively; p < 0.0001) and acceptable between the ADVANCE and UKPDS risk engines (k = 0.608). There are discrepancies between the general population and the type 2 diabetic patient-specific risk engines. The results of this study indicate the need for a prospective study which validates specific equations for diabetic patients in the Spanish population, as well as research on new models for cardiovascular risk prediction in these patients.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 12%
Student > Postgraduate 5 10%
Researcher 4 8%
Student > Bachelor 4 8%
Professor 3 6%
Other 15 31%
Unknown 12 24%
Readers by discipline Count As %
Medicine and Dentistry 16 33%
Pharmacology, Toxicology and Pharmaceutical Science 4 8%
Agricultural and Biological Sciences 4 8%
Nursing and Health Professions 3 6%
Computer Science 3 6%
Other 5 10%
Unknown 14 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 17 October 2015.
All research outputs
#3,362,768
of 24,041,016 outputs
Outputs from BMC Cardiovascular Disorders
#142
of 1,764 outputs
Outputs of similar age
#46,213
of 283,423 outputs
Outputs of similar age from BMC Cardiovascular Disorders
#5
of 32 outputs
Altmetric has tracked 24,041,016 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,764 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 91% 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 283,423 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.