Comment in:

Diabetes Care. 2006 Dec;29(12):2755-7.

Diabetes Care. 2007 Sep;30(9):e96; author reply e97.

Nat Clin Pract Endocrinol Metab. 2007 Jul;3(7):506-7.

Accuracy and predictive value of classification schemes for ketosis-prone diabetes.

Translational Metabolism Unit, Baylor College of Medicine, One Baylor Plaza, Room 520 N, Houston, TX 77030, USA.

OBJECTIVE: Ketosis-prone diabetes (KPD) is an emerging, heterogeneous syndrome. A sound classification scheme for KPD is essential to guide clinical practice and pathophysiologic studies. Four schemes have been used and are based on immunologic criteria, immunologic criteria and insulin requirement, BMI, and immunologic criteria and beta-cell function (Abeta classification). The aim of the present study is to compare the four schemes for accuracy and predictive value in determining whether KPD patients have absent or preserved beta-cell function, which is a strong determinant of long-term insulin dependence and clinical phenotype. RESEARCH DESIGN AND METHODS: Consecutive patients (n = 294) presenting with diabetic ketoacidosis and followed for 12-60 months were classified according to all four schemes. They were evaluated longitudinally for beta-cell autoimmunity, clinical and biochemical features, beta-cell function, and insulin dependence. beta-Cell function was defined by peak plasma C-peptide response to glucagon >or=1.5 ng/ml. The accuracy of each scheme to predict absent or preserved beta-cell function after 12 months of follow-up was tested using multiple statistical analyses. RESULTS: The "Abeta" classification scheme was the most accurate overall, with a sensitivity and specificity of 99.4 and 95.9%, respectively, positive and negative likelihood ratios of 24.55 and 0.01, respectively, and an area under the receiver operator characteristic curve of 0.972. CONCLUSIONS: The Abeta scheme has the highest accuracy and predictive value in classifying KPD patients with regard to clinical outcomes and pathophysiologic subtypes.

PMID: 17130187 [PubMed - indexed for MEDLINE]