TY - JOUR T1 - Several simple rules predicted complications in high risk patients with diabetes JF - Evidence Based Medicine JO - Evid Based Med SP - 96 LP - 96 DO - 10.1136/ebm.7.3.96 VL - 7 IS - 3 A2 - , Y1 - 2002/05/01 UR - http://ebm.bmj.com/content/7/3/96.1.abstract N2 - (2001) Diabetes Care 24, 1547. Selby JV, Karter AJ, Ackerson LM, et al.. Developing a prediction rule from automated clinical databases to identify high-risk patients in a large population with diabetes.. Aug;. :. –55.OpenUrlAbstract/FREE Full Text 
 
 QUESTION: What is the accuracy of a prediction rule for identifying patients with diabetes mellitus who are at high short term risk for macro- and microvascular events, infectious disease, and metabolic complications? A cohort of patients, randomly split into derivation and validation datasets. Kaiser Permanente health maintenance organization (HMO) in Oakland, California, USA. 57 722 members of the HMO who were ≥ 19 years of age, had diabetes, and were continuously enrolled in the health plan during the 2 year baseline period. The derivation dataset included 28 838 patients (mean age 61 y, 53% men), and the validation dataset included 28 884 patients (mean age 61 y, 52% men). A “best” model and 4 simpler … ER -