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Ngarmukos, C., Bunnag, P., Kosachunhanun, N., Krittiyawong, S., Leelawatana, R., Prathipanawatr, T., Plengvidhya, N., Benjasuratwong, Y., Suwanwalaikorn, S., Deerochanawong, C., Chetthakul, T., Mongkolsomlit, S. and Rawdaree, P. (2006) Thailand diabetes registry project: Prevalence, characteristics and treatment of patients with diabetic nephropathy. Journal of the Medical Association Thailand, 89, S37-S42.

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• TITLE: The development and validation of a risk score for predicting microalbuminuria in type 2 diabetic patients

  AUTHORS: Sirima Mongkolsomlit, Petch Rawdaree, Chulalux Komoltri, Chamaiporn Tawichasri, Jayanton Patumanond

  KEYWORDS: Microalbuminuria; Risk Score; Type 2 Diabetes; RIsk Factor; Scoring Scheme

  JOURNAL NAME: Journal of Diabetes Mellitus, Vol.2 No.2, May 25, 2012

  ABSTRACT: Objective: To develop and validate a prognostic scoring scheme for the prediction of microalbuminuria in type 2 diabetic patients of Thai descent. Methods: The clinical information from type 2 diabetic patients who were treated at community hospitals was used to develop a prediction model (derivation set). The model evaluated at a tertiary hospital (validation set). A stepwise logistic regression model was used to identify the independent risk variables from the derivation set and a simple point scoring system was derived from the beta-coefficients. The risk scoring scheme was validated by the validation set. Results: The risk scoring scheme is based on six risk predictors: the duration of diabetes, age at the onset of diabetes, systolic blood pressure, low density lipoprotein levels, creatinine levels, and alcohol consumption. The total score ranged from 0 to 11.5. The likelihood of microalbuminuria in patients with low risk (scores ≤ 2) was 0.28, with moderate risk (scores 2.5 to 5.5) was 0.86, and high risk (scores ≥ 6) was 7.36. The area under the ROC curve of the derivation set and validation set were 0.768 (95% CI 0.73 - 0.81) and 0.758 (95% CI 0.70 - 0.80), respectively. Conclusion: Our scoring system is a simple and reasonably accurate method for predicting the future presence of microalbuminuria in type 2 diabetic patients.