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. 2019 Nov 13;7(1):e000735.
doi: 10.1136/bmjdrc-2019-000735. eCollection 2019.

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

Dahai Yu  1   2 , Jin Shang  1 , Yamei Cai  1 , Zheng Wang  1 , Xiaoxue Zhang  1 , Bin Zhao  3 , Zhanzheng Zhao  1 , David Simmons  1   4
Affiliations

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

Dahai Yu et al. BMJ Open Diabetes Res Care. .

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.

Keywords: cardiovascular mortality; prediction; prognostic models; statistical.

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Conflict of interest statement

Competing interests: None declared.

Figures

Figure 1
Figure 1
Assessing calibration in the derivation cohort (left) and the validation cohort (right) for cardiovascular death.
Figure 2
Figure 2
Assessing calibration in the validation cohort for cardiovascular death by applying the United Kingdom Prospective Diabetes Study (UKPDS) risk score.
Figure 3
Figure 3
Practical prognostic score charts for predicting cardiovascular death among patients with incident DN. DN; diabetic nephropathy.
See this image and copyright information in PMC

References

    1. Gross JL, de Azevedo MJ, Silveiro SP, et al. . Diabetic nephropathy: diagnosis, prevention, and treatment. Diabetes Care 2005;28:164–76. 10.2337/diacare.28.1.164 - DOI - PubMed
    1. Nazar CMJ. Diabetic nephropathy; principles of diagnosis and treatment of diabetic kidney disease. J Nephropharmacol 2014;3:15–20. - PMC - PubMed
    1. Doshi SM, Friedman AN. Diagnosis and management of type 2 diabetic kidney disease. Clin J Am Soc Nephrol 2017;12:1366–73. 10.2215/CJN.11111016 - DOI - PMC - PubMed
    1. Pontuch P. [Microalbuminuria–a risk factor for diabetic nephropathy and cardiovascular disease]. Vnitr Lek 2001;47:307–10. - PubMed
    1. Chen H-S, Wu T-EJ, Jap T-S, et al. . Subclinical hypothyroidism is a risk factor for nephropathy and cardiovascular diseases in type 2 diabetic patients. Diabet Med 2007;24:1336–44. 10.1111/j.1464-5491.2007.02270.x - DOI - PubMed

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