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Several simple rules predicted complications in high risk patients with diabetes

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 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).

Description of prediction guide

A “best” model and 4 simpler …

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  • Source of funding: in part, Pfizer Pharmaceuticals.

  • For correspondence: Dr J V Selby, Division of Research, Kaiser Permanente, Oakland, CA, USA. jvs{at}