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Clinical utility of brachial-ankle pulse wave velocity in the prediction of cardiovascular events in diabetic patients

Overview of attention for article published in Cardiovascular Diabetology, September 2014
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  • Good Attention Score compared to outputs of the same age (76th percentile)

Mentioned by

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6 tweeters

Citations

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45 Dimensions

Readers on

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42 Mendeley
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Title
Clinical utility of brachial-ankle pulse wave velocity in the prediction of cardiovascular events in diabetic patients
Published in
Cardiovascular Diabetology, September 2014
DOI 10.1186/s12933-014-0128-5
Pubmed ID
Authors

Naoto Katakami, Takeshi Osonoi, Mitsuyoshi Takahara, Miyoko Saitou, Taka-aki Matsuoka, Yoshimitsu Yamasaki, Iichiro Shimomura

Abstract

BackgroundBrachial-ankle pulse wave velocity (baPWV) is a method to estimate arterial stiffness, which reflects the stiffness of both the aorta and peripheral artery; it would be applicable to general practice, since its measurementis automated. The aim of this study was to evaluate whether baPWV can be predictors of future cardiovascular events (CVE) in diabetic patients.MethodsWe prospectively evaluated the association between baPWV or carotid intima-media thickness (carotid IMT) at baseline and new onset of CVE in 1040 type 2 diabetic patients without CVE. The predictability of baPWV and/or carotid IMT for identifying patients at high risk for CVE was evaluated by time-dependent receiver-operating-characteristic (ROC) curve analysis.ResultsDuring a median follow-up of 7.5 years, 113 had new CVD events. The cumulative incidence rates of CVE were significantly higher in patients with high baPWV values (¿1550 cm/s) as compared to those with low baPWV values (<1550 cm/s) (p¿<¿0.001, log-rank test). Similarly, the cumulative incidence rate of CVE was significantly higher in patients with higher maximum carotid IMT (maxIMT) values (¿1.0 mm) as compared to those with lower maxIMT values (<1.0 mm) (p¿<¿0.001, log-rank test). Subjects with both ¿high PWV¿ and ¿high IMT¿ had a significantly higher risk of developing CVE as compared to those with either ¿high PWV¿ or ¿high IMT,¿ as well as those with neither. A multivariate Cox proportional hazards regression model revealed that both baPWV (HR¿=¿1.30, [95%CI: 1.07-1.57]; p¿=¿0.009) and maxIMT (HR¿=¿1.20, [95%CI: 1.01-1.41]; p¿=¿0.033) were independent predictors for CVE, even after adjustment for the conventional risk factors. Time-dependent ROC curve analyses revealed that the addition of maxIMT to the Framingham risk score resulted in significant increase in AUC (from 0.60 [95%CI: 0.54-0.67] to 0.63 [95%CI: 0.60-0.82]; p¿=¿0.01). Notably, the addition of baPWV to the Framingham risk score and maxIMT resulted in further and significant (p¿=¿0.02) increase in AUC (0.72 [95%CI: 0.67-0.78]).ConclusionsEvaluation of baPWV, in addition to carotid IMT and conventional risk factors, improved the ability to identify the diabetic individuals with high risk for CVE.

Twitter Demographics

The data shown below were collected from the profiles of 6 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 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 21%
Student > Bachelor 7 17%
Student > Master 4 10%
Student > Ph. D. Student 4 10%
Student > Postgraduate 3 7%
Other 2 5%
Unknown 13 31%
Readers by discipline Count As %
Medicine and Dentistry 17 40%
Nursing and Health Professions 2 5%
Computer Science 2 5%
Engineering 2 5%
Social Sciences 1 2%
Other 3 7%
Unknown 15 36%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 26 September 2014.
All research outputs
#4,288,473
of 16,398,486 outputs
Outputs from Cardiovascular Diabetology
#220
of 945 outputs
Outputs of similar age
#47,695
of 204,586 outputs
Outputs of similar age from Cardiovascular Diabetology
#1
of 1 outputs
Altmetric has tracked 16,398,486 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 945 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one has done well, scoring higher than 76% 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 204,586 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 76% 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