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Diabetes Care. 2007 Jan;30(1):65-70.

Development and validation of stroke risk equation for Hong Kong Chinese patients with type 2 diabetes: the Hong Kong Diabetes Registry.

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  • 1Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, NT, Hong Kong, China.

Abstract

OBJECTIVE:

We sought to develop stroke risk equations for Chinese patients with type 2 diabetes in Hong Kong.

RESEARCH DESIGN AND METHODS:

A total of 7,209 Hong Kong Chinese type 2 diabetic patients without a history of stroke at baseline were analyzed. The data were randomly and evenly divided into the training subsample and the test subsample. In the training subsample, stepwise Cox models were used to develop the risk equation. Validation of the U.K. Prospective Diabetes Study (UKPDS) stroke risk engine and the current stroke equation was performed in the test dataset. The life-table method was used to check calibration, and the area under the receiver operating characteristic curve (aROC) was used to check discrimination.

RESULTS:

A total of 372 patients developed incident stroke during a median of 5.37 years (interquartile range 2.88-7.78) of follow-up. Age, A1C, spot urine albumin-to-creatinine ratio (ACR), and history of coronary heart disease (CHD) were independent predictors. The performance of the UKPDS stroke engine was suboptimal in our cohort. The newly developed risk equation defined by these four predictors had adequate performance in the test subsample. The predicted stroke-free probability by the current equation was within the 95% CI of the observed probability. The aROC was 0.77 for predicting stroke within 5 years. The risk score was computed as follows: 0.0634 x age (years) + 0.0897 x A1C + 0.5314 x log(10) (ACR) (mg/mmol) + 0.5636 x history of CHD (1 if yes). The 5-year stroke probability can be calculated by: 1 - 0.9707(EXP (Risk Score - 4.5674)).

CONCLUSIONS:

Although the risk equation performed reasonably well in Chinese type 2 diabetic patients, external validation is required in other populations.

PMID:
17192335
[PubMed - indexed for MEDLINE]
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