RT Journal Article
SR Electronic
T1 Development and validation of a prediction model for insulin-associated hypoglycemia in non-critically ill hospitalized adults
JF BMJ Open Diabetes Research & Care
JO BMJ Open Diab Res Care
FD American Diabetes Association
SP e000499
DO 10.1136/bmjdrc-2017-000499
VO 6
IS 1
A1 Nestoras Nicolas Mathioudakis
A1 Estelle Everett
A1 Shuvodra Routh
A1 Peter J Pronovost
A1 Hsin-Chieh Yeh
A1 Sherita Hill Golden
A1 Suchi Saria
YR 2018
UL http://drc.bmj.com/content/6/1/e000499.abstract
AB Objective To develop and validate a multivariable prediction model for insulin-associated hypoglycemia in non-critically ill hospitalized adults.Research design and methods We collected pharmacologic, demographic, laboratory, and diagnostic data from 128 657 inpatient days in which at least 1 unit of subcutaneous insulin was administered in the absence of intravenous insulin, total parenteral nutrition, or insulin pump use (index days). These data were used to develop multivariable prediction models for biochemical and clinically significant hypoglycemia (blood glucose (BG) of ≤70 mg/dL and <54 mg/dL, respectively) occurring within 24 hours of the index day. Split-sample internal validation was performed, with 70% and 30% of index days used for model development and validation, respectively.Results Using predictors of age, weight, admitting service, insulin doses, mean BG, nadir BG, BG coefficient of variation (CVBG), diet status, type 1 diabetes, type 2 diabetes, acute kidney injury, chronic kidney disease (CKD), liver disease, and digestive disease, our model achieved a c-statistic of 0.77 (95% CI 0.75 to 0.78), positive likelihood ratio (+LR) of 3.5 (95% CI 3.4 to 3.6) and negative likelihood ratio (−LR) of 0.32 (95% CI 0.30 to 0.35) for prediction of biochemical hypoglycemia. Using predictors of sex, weight, insulin doses, mean BG, nadir BG, CVBG, diet status, type 1 diabetes, type 2 diabetes, CKD stage, and steroid use, our model achieved a c-statistic of 0.80 (95% CI 0.78 to 0.82), +LR of 3.8 (95% CI 3.7 to 4.0) and −LR of 0.2 (95% CI 0.2 to 0.3) for prediction of clinically significant hypoglycemia.Conclusions Hospitalized patients at risk of insulin-associated hypoglycemia can be identified using validated prediction models, which may support the development of real-time preventive interventions.