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Prediction of new onset of end stage renal disease in Chinese patients with type 2 diabetes mellitus – a population-based retrospective cohort study

Overview of attention for article published in BMC Nephrology, August 2017
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Title
Prediction of new onset of end stage renal disease in Chinese patients with type 2 diabetes mellitus – a population-based retrospective cohort study
Published in
BMC Nephrology, August 2017
DOI 10.1186/s12882-017-0671-x
Pubmed ID
Authors

Eric Yuk Fai Wan, Daniel Yee Tak Fong, Colman Siu Cheung Fung, Esther Yee Tak Yu, Weng Yee Chin, Anca Ka Chun Chan, Cindy Lo Kuen Lam

Abstract

Since diabetes mellitus (DM) is the leading cause of end stage renal disease (ESRD), this study aimed to develop a 5-year ESRD risk prediction model among Chinese patients with Type 2 DM (T2DM) in primary care. A retrospective cohort study was conducted on 149,333 Chinese adult T2DM primary care patients without ESRD in 2010. Using the derivation cohort over a median of 5 years follow-up, the gender-specific models including the interaction effect between predictors and age were derived using Cox regression with a forward stepwise approach. Harrell's C-statistic and calibration plot were applied to the validation cohort to assess discrimination and calibration of the models. Prediction models showed better discrimination with Harrell's C-statistics of 0.866 (males) and 0.862 (females) and calibration power from the plots than other established models. The predictors included age, usages of anti-hypertensive drugs, anti-glucose drugs, and Hemogloblin A1c, blood pressure, urine albumin/creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR). Specific predictors for male were smoking and presence of sight threatening diabetic retinopathy while additional predictors for female included longer duration of diabetes and quadratic effect of body mass index. Interaction factors with age showed a greater weighting of insulin and urine ACR in younger males, and eGFR in younger females. Our newly developed gender-specific models provide a more accurate 5-year ESRD risk predictions for Chinese diabetic primary care patients than other existing models. The models included several modifiable risk factors that clinicians can use to counsel patients, and to target at in the delivery of care to patients.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 66 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 12%
Student > Master 7 11%
Other 5 8%
Researcher 5 8%
Student > Doctoral Student 4 6%
Other 12 18%
Unknown 25 38%
Readers by discipline Count As %
Medicine and Dentistry 15 23%
Nursing and Health Professions 9 14%
Social Sciences 3 5%
Agricultural and Biological Sciences 2 3%
Computer Science 2 3%
Other 6 9%
Unknown 29 44%
Attention Score in Context

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 09 August 2017.
All research outputs
#20,441,465
of 22,996,001 outputs
Outputs from BMC Nephrology
#2,208
of 2,497 outputs
Outputs of similar age
#276,936
of 317,444 outputs
Outputs of similar age from BMC Nephrology
#56
of 67 outputs
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So far Altmetric has tracked 2,497 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 67 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.