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Derivation and external validation of risk algorithms for cerebrovascular (re)hospitalisation in patients with type 2 diabetes: Two cohorts study.
Yu, Dahai; Cai, Yamei; Graffy, Jonathan; Holman, Daniel; Zhao, Zhanzheng; Simmons, David.
Afiliação
  • Yu D; Department of Nephrology, The First Affiliated Hospital, Zhengzhou University, Zhengzhou 450052, China; Arthritis Research UK Primary Care Centre, Research Institute for Primary Care & Health Sciences, Keele University, Keele ST5 5BG, United Kingdom.
  • Cai Y; Department of Nephrology, The First Affiliated Hospital, Zhengzhou University, Zhengzhou 450052, China.
  • Graffy J; Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, Cambridgeshire CB2 0SR, United Kingdom.
  • Holman D; Department of Sociological Studies, University of Sheffield, Sheffield S10 2TU, United Kingdom.
  • Zhao Z; Department of Nephrology, The First Affiliated Hospital, Zhengzhou University, Zhengzhou 450052, China. Electronic address: zhanzhengzhao@zzu.edu.cn.
  • Simmons D; Western Sydney University, Campbelltown, Sydney, NSW 2760, Australia. Electronic address: dsworkster@gmail.com.
Diabetes Res Clin Pract ; 144: 74-81, 2018 Oct.
Article em En | MEDLINE | ID: mdl-30114459
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Admissão do Paciente / Readmissão do Paciente / Algoritmos / Transtornos Cerebrovasculares / Diabetes Mellitus Tipo 2 / Hospitalização Idioma: En Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Admissão do Paciente / Readmissão do Paciente / Algoritmos / Transtornos Cerebrovasculares / Diabetes Mellitus Tipo 2 / Hospitalização Idioma: En Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Reino Unido