Development and validation of a prediction model for insulin-associated hypoglycemia in non-critically ill hospitalized adults

Abstract

ObjectiveTo develop and validate a multivariable prediction model for insulin-associated hypoglycemia in non-critically ill hospitalized adults.Research design and methodsWe 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.ResultsUsing 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.ConclusionsHospitalized patients at risk of insulin-associated hypoglycemia can be identified using validated prediction models, which may support the development of real-time preventive interventions.

Glycemic Control and Hypoglycemia in Patients Treated with Insulin Pump Therapy: An Observational Study

“…Another possible reason to this relation is that patients who require a higher amount of insulin could have an underlying condition causing insulin resistance. A prediction model established that the risk of hypoglycemia is directly proportional to increases in the total insulin dose until reaching a threshold of 0.8 units/kg where this relationship can no longer be observed [ 25 – 27 ]. Studies with a greater sample that show a stronger association are necessary.…”

“…Coefficient of variation and standard deviation of glucose measures calculated by CGM have been described as ways of representing glycemic fluctuation. Diverse studies have demonstrated the association between the coefficient of variation and adequate control of HbA1C or presence of hypoglycemia [ 27 – 29 ]. By prediction models, it has been established that for every 10% increase in the value of coefficient of variation, risk of hypoglycemia increases by 19% [ 27 ].…”

“…Diverse studies have demonstrated the association between the coefficient of variation and adequate control of HbA1C or presence of hypoglycemia [ 27 – 29 ]. By prediction models, it has been established that for every 10% increase in the value of coefficient of variation, risk of hypoglycemia increases by 19% [ 27 ]. In our study, it was found that a low coefficient constitutes a protective factor to develop hypoglycemia.…”

Value of Capillary Glucose Profiles in Assessing Risk of Nocturnal Hypoglycemia in Type 1 Diabetes Based on Continuous Glucose Monitoring

“…Mathioudakis et al established a prediction model for insulinassociated hypoglycemia in non-critically ill hospitalized adults. The model is based on multiple variables including mean BG, nadir BG, BG coefficient of variation, age, weight, diet status, insulin doses, types of diabetes, stage of chronic kidney disease, and liver function [25]. The sensitivity and specificity of this model were 81.9% and 78.6%.…”

Hypoglycaemia in hospitalized patients with or without heart failure

“…6 Many factors contribute to hypoglycaemia among hospitalized patients, including increasing age, higher insulin doses, basal insulin, mistiming of insulin administration, lower body weight, decreased renal function, and changes in diet or medications. 7 Hypoglycaemia in the hospital is associated with longer length of stay, increased inpatient and 1-year mortality, and increased costs. 8 In ambulatory settings, HF is associated with increased risk of severe hypoglycaemia.…”