Derivation and validation model for hospital hypoglycemia

An objective and simple prognostic model for hospitalized patients with hypoglycemia could be helpful in guiding initial intensity of treatment.

We carried out a derivation rule for hypoglycemia using data from a nationwide retrospective cohort study of patients with diabetes or hyperglycemia carried out in 2014 (n=839 patients). The rule for hypoglycemia was validated using a second data set from a nationwide retrospective cohort study carried out in 2016 (n=561 patients). We derived our prediction rule using logistic regression with hypoglycemia (glucose less than 70mg/dL) as the primary outcome.

The incidence of hypoglycemia in the derivation cohort was 10.3%. Patient's characteristics independently associated with hypoglycemia included episodes of hypoglycemia during the previous three months (odds ratio [OR]: 6.29, 95% confidence interval [95%CI]: 3.37-11.79, p<0.001) estimated glomerular filtration rate lower than 30mL/min/1.73m² (OR: 2.32, 95%CI: 1.23-4.35, p=0.009), daily insulin dose greater than 0.3units per Kg (OR: 1.74, 95%CI: 1.06-2.85, p=0.028), and days of hospitalization (OR: 1.03, 95%CI: 1.01-1.04, p=0.001). The model showed an area under the curve (AUC): 0.72 (95%CI: 0.66-0.78, p<0.001). The AUC in the validation cohort was: 0.71 (95%CI: 0.63-0.79, p<0.001).

The rule showed fair accuracy to predict hypoglycemia. Implementation of the rule into computer systems could be used in guiding initial insulin therapy.