Yu, D ORCID: 0000-0002-8449-7725, Cai, Y, Graffy, J, Holman, D, Zhao, Z and Simmons, D (2018) Derivation and external validation of risk algorithms for cerebrovascular (re)hospitalisation in patients with type 2 diabetes: two cohorts study. Diabetes Research and Clinical Practice, 144. pp. 74-81. ISSN 1872-8227

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Abstract

Aims
Cerebrovascular disease is one of more typical reasons for hospitalisation and re-hospitalisation in people with type 2 diabetes. We aimed to derive and externally validate two risk prediction algorithms for cerebrovascular hospitalisation and re-hospitalisation.

Methods
Two independent cohorts were used to derive and externally validate the two risk scores. The development cohort comprises 4704 patients with type 2 diabetes registered in 18 general practices across Cambridgeshire. The validation cohort includes 1121 type 2 patients from a post-trial cohort data. Outcomes were cerebrovascular hospitalisation within two years and cerebrovascular re-hospitalisation within ninety days of the previous cerebrovascular hospitalisation. Logistic regression was applied to derive the two risk scores for cerebrovascular hospitalisation and re-hospitalisation from development cohort, which were externally validated in the validation cohort.

Results
The incidence of cerebrovascular hospitalisation and re-hospitalisation was 3.76% and 1.46% in the development cohort, and 4.99% and 1.87% in the external validation cohort. Age, gender, body mass index, blood pressures, and lipid profiles were included in the final model. Model discrimination was similar in both cohorts, with all C-statistics > 0.70, and very good calibration of observed and predicted individual risks.

Conclusion
Two new risk scores that quantify individual risks of cerebrovascular hospitalisation and re-hospitalisation have been well derived and externally validated. Both scores are on the basis of a few of clinical measurements that are commonly available for patients with type 2 diabetes in primary care settings and could work as tools to identify individuals at high risk of cerebrovascular hospitalisation and re-hospitalisation.

Item Type: Article
Uncontrolled Keywords: cerebrovascular disease, diabetes population, risk prediction, primary care
Subjects: R Medicine > RC Internal medicine
Depositing User: Symplectic
Date Deposited: 01 Nov 2018 13:53
Last Modified: 01 Nov 2018 14:02
URI: http://eprints.keele.ac.uk/id/eprint/5248

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