↓ Skip to main content

Development of a new scoring system to predict 5-year incident diabetes risk in middle-aged and older Chinese

Overview of attention for article published in Acta Diabetologica, September 2017
Altmetric Badge

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
10 Mendeley
Title
Development of a new scoring system to predict 5-year incident diabetes risk in middle-aged and older Chinese
Published in
Acta Diabetologica, September 2017
DOI 10.1007/s00592-017-1047-1
Pubmed ID
Authors

Xu Han, Jing Wang, Yaru Li, Hua Hu, Xiulou Li, Jing Yuan, Ping Yao, Xiaoping Miao, Sheng Wei, Youjie Wang, Yuan Liang, Xiaomin Zhang, Huan Guo, An Pan, Handong Yang, Tangchun Wu, Meian He

Abstract

The aim of this study was to develop a new risk score system to predict 5-year incident diabetes risk among middle-aged and older Chinese population. This prospective study included 17,690 individuals derived from the Dongfeng-Tongji cohort. Participants were recruited in 2008 and were followed until October 2013. Incident diabetes was defined as self-reported clinician diagnosed diabetes, fasting glucose ≥7.0 mmol/l, or the use of insulin or oral hypoglycemic agent. A total of 1390 incident diabetic cases were diagnosed during the follow-up period. β-Coefficients were derived from Cox proportional hazard regression model and were used to calculate the risk score. The diabetes risk score includes BMI, fasting glucose, hypertension, hyperlipidemia, current smoking status, and family history of diabetes. The β-coefficients of these variables ranged from 0.139 to 1.914, and the optimal cutoff value was 1.5. The diabetes risk score was calculated by multiplying the β-coefficients of the significant variables by 10 and rounding to the nearest integer. The score ranges from 0 to 36. The area under the receiver operating curve of the score was 0.751. At the optimal cutoff value of 15, the sensitivity and specificity were 65.6 and 72.9%, respectively. Based upon these risk factors, this model had the highest discrimination compared with several commonly used diabetes prediction models. The newly established diabetes risk score with six parameters appears to be a reliable screening tool to predict 5-year risk of incident diabetes in a middle-aged and older Chinese population.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 4 40%
Student > Master 2 20%
Other 1 10%
Librarian 1 10%
Student > Ph. D. Student 1 10%
Other 1 10%
Readers by discipline Count As %
Unspecified 4 40%
Agricultural and Biological Sciences 2 20%
Computer Science 1 10%
Pharmacology, Toxicology and Pharmaceutical Science 1 10%
Sports and Recreations 1 10%
Other 1 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 18 September 2017.
All research outputs
#10,450,875
of 11,788,552 outputs
Outputs from Acta Diabetologica
#374
of 473 outputs
Outputs of similar age
#226,036
of 267,354 outputs
Outputs of similar age from Acta Diabetologica
#8
of 11 outputs
Altmetric has tracked 11,788,552 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 473 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 267,354 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.