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Derivation and external validation of a risk prediction algorithm to estimate future risk of cardiovascular death among patients with type 2 diabetes and incident diabetic nephropathy: prospective cohort study

Yu, Dahai; Shang, Jin; Cai, Yamei; Zhang, Xiaoxue; Zhao, Bin; Zhao, Zhanzheng; Simmons, David

Derivation and external validation of a risk prediction algorithm to estimate future risk of cardiovascular death among patients with type 2 diabetes and incident diabetic nephropathy: prospective cohort study Thumbnail


Authors

Jin Shang

Yamei Cai

Xiaoxue Zhang

Bin Zhao

Zhanzheng Zhao

David Simmons



Abstract

Objective
To derive, and externally validate, a risk score for cardiovascular death among patients with type 2 diabetes and newly diagnosed diabetic nephropathy (DN).

Research design and methods
Two independent prospective cohorts with type 2 diabetes were used to develop and externally validate the risk score. The derivation cohort comprised 2282 patients with an incident, clinical diagnosis of DN. The validation cohort includes 950 patients with incident, biopsy-proven diagnosis of DN. The outcome was cardiovascular death within 2 years of the diagnosis of DN. Logistic regression was applied to derive the risk score for cardiovascular death from the derivation cohort, which was externally validated in the validation cohort. The score was also estimated by applying the United Kingdom Prospective Diabetes Study (UKPDS) risk score in the external validation cohort.

Results
The 2-year cardiovascular mortality was 12.05% and 11.79% in the derivation cohort and validation cohort, respectively. Traditional predictors including age, gender, body mass index, blood pressures, glucose, lipid profiles alongside novel laboratory test items covering five test panels (liver function, serum electrolytes, thyroid function, blood coagulation and blood count) were included in the final model. C-statistics was 0.736 (95% CI 0.731 to 0.740) and 0.747 (95% CI 0.737 to 0.756) in the derivation cohort and validation cohort, respectively. The calibration slope was 0.993 (95% CI 0.974 to 1.013) and 1.000 (95% CI 0.981 to 1.020) in the derivation cohort and validation cohort, respectively. The UKPDS risk score substantially underestimated cardiovascular mortality.

Conclusions
A new risk score based on routine clinical measurements that quantified individual risk of cardiovascular death was developed and externally validated. Compared with the UKPDS risk score, which underestimated the cardiovascular disease risk, the new score is a more specific tool for patients with type 2 diabetes and DN. The score could work as a tool to identify individuals at the highest risk of cardiovascular death among those with DN.

Journal Article Type Article
Acceptance Date Oct 10, 2019
Online Publication Date Nov 13, 2019
Publication Date Nov 13, 2019
Publicly Available Date Mar 28, 2024
Journal BMJ Open Diabetes Research and Care
Electronic ISSN 2052-4897
Publisher BMJ Publishing Group
Peer Reviewed Peer Reviewed
Volume 7
Issue 1
DOI https://doi.org/10.1136/bmjdrc-2019-000735
Keywords cardiovascular mortality; prediction; prognostic models; statistical.
Publisher URL http://dx.doi.org/10.1136/bmjdrc-2019-000735

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