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Predictors of all-cause and cardiovascular disease mortality in type 2 diabetes: Diabetes Heart Study

Overview of attention for article published in Diabetology & Metabolic Syndrome, June 2015
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Title
Predictors of all-cause and cardiovascular disease mortality in type 2 diabetes: Diabetes Heart Study
Published in
Diabetology & Metabolic Syndrome, June 2015
DOI 10.1186/s13098-015-0055-y
Pubmed ID
Authors

Laura M. Raffield, Fang-Chi Hsu, Amanda J. Cox, J. Jeffrey Carr, Barry I. Freedman, Donald W. Bowden

Abstract

Many studies evaluated the best predictors for cardiovascular disease (CVD) events in individuals with type 2 diabetes (T2D), but few studies examined the factors most strongly associated with mortality in T2D. The Diabetes Heart Study (DHS), an intensively phenotyped family-based cohort enriched for T2D, provided an opportunity to address this question. Associations with mortality were examined in 1022 European Americans affected by T2D from 476 DHS families. All-cause mortality was 31.2 % over an average 9.6 years of follow-up. Cox proportional hazards models with sandwich-based variance estimation were used to evaluate associations between all-cause and CVD mortality and 24 demographic and clinical factors, including coronary artery calcified plaque (CAC), carotid artery intima-media thickness, medications, body mass index, waist hip ratio, lipids, blood pressure, kidney function, QT interval, educational attainment, and glycemic control. Nominally significant factors (p < 0.25) from univariate analyses were included in model selection (backward elimination, forward selection, and stepwise selection). Age and sex were included in all models. The all-cause mortality model selected from the full DHS sample included age, sex, CAC, urine albumin: creatinine ratio (UACR), insulin use, current smoking, and educational attainment. The CVD mortality model selected from the full sample included age, sex, CAC, UACR, triglycerides, and history of CVD events. Beyond age, the most significant associations for both mortality models were CAC (2.03 × 10(-4) ≤ p ≤ 0.001) and UACR (1.99 × 10(-8) ≤ p ≤ 2.23 × 10(-8)). To confirm the validity of the main predictors identified with model selection using the full sample, a two-fold cross-validation approach was used, and similar results were observed. This analysis highlights important demographic and clinical factors, notably CAC and albuminuria, which predict mortality in the general population of patients with T2D.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Unknown 49 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 16%
Researcher 8 16%
Student > Postgraduate 5 10%
Student > Master 5 10%
Other 3 6%
Other 10 20%
Unknown 11 22%
Readers by discipline Count As %
Medicine and Dentistry 22 44%
Biochemistry, Genetics and Molecular Biology 4 8%
Computer Science 4 8%
Agricultural and Biological Sciences 3 6%
Mathematics 1 2%
Other 4 8%
Unknown 12 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 July 2015.
All research outputs
#14,792,187
of 24,792,414 outputs
Outputs from Diabetology & Metabolic Syndrome
#326
of 763 outputs
Outputs of similar age
#129,516
of 268,487 outputs
Outputs of similar age from Diabetology & Metabolic Syndrome
#6
of 10 outputs
Altmetric has tracked 24,792,414 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 763 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.9. This one has gotten more attention than average, scoring higher than 55% 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 268,487 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 50% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.