A nomogram and online calculator for predicting subsequent hypoglycaemia after the first 24 h in critically ill patients

The incidence of hypoglycaemia in critically ill patients is almost three times higher than in general hospitalised patients. Considering the specificity of the population, current guidelines and expert consensus recommend that glycaemic management of critically ill patients should be differentiated from that of general hospitalised patients. This study aimed to identify independent risk factors for hypoglycaemia and to develop and temporally validate a nomogram and online calculator for predicting hypoglycaemia after the first 24 h of EICU admission. This retrospective model development study with prospective validation included 3,104 patients admitted to the emergency intensive care unit (EICU) of a premier hospital in western China from June 2021 to December 2022 as the development cohort, and 1,010 patients prospectively collected from the same hospital from January to July 2023 as the temporal validation cohort. Hypoglycaemia was defined as a blood glucose concentration ≤ 3.9 mmol/L (70 mg/dL). A hypoglycaemic prediction model was constructed using the development cohort through LASSO and logistic regression, and a nomogram and online calculator were subsequently developed. The model is intended for use after completion of the first 24 h of EICU observation; the predicted outcome is the first occurrence of hypoglycaemia after this landmark and before EICU discharge. The variables incorporated into the prediction model included a history of hypoglycaemia, the APACHE II score at ICU admission, the coefficient of variation of blood glucose, diabetes, sepsis, renal failure, and malnutrition. The area under the receiver operating characteristic curve of the development cohort and validation cohort was 0.833 and 0.815, respectively. Both the calibration curve and the decision curve demonstrated good consistency. This novel online calculator, designed for use after the first 24 h of EICU observation, shows good predictive performance for hypoglycaemia in EICU patients. It may therefore support risk stratification at that point in the admission. Prospective validation in independent multicentre cohorts is required before wider clinical use.