title: Usefulness of Glycemic Gap to Predict ICU Mortality in Critically Ill Patients With Diabetes.
abstract: Stress-induced hyperglycemia (SIH) has been independently associated with an increased risk of mortality in critically ill patients without diabetes. However, it is also necessary to consider preexisting hyperglycemia when investigating the relationship between SIH and mortality in patients with diabetes. We therefore assessed whether the gap between admission glucose and A1C-derived average glucose (ADAG) levels could be a predictor of mortality in critically ill patients with diabetes.We retrospectively reviewed the Acute Physiology and Chronic Health Evaluation II (APACHE-II) scores and clinical outcomes of patients with diabetes admitted to our medical intensive care unit (ICU) between 2011 and 2014. The glycosylated hemoglobin (HbA1c) levels were converted to the ADAG by the equation, ADAG = [(28.7 × HbA1c) - 46.7]. We also used receiver operating characteristic (ROC) curves to determine the optimal cut-off value for the glycemic gap when predicting ICU mortality and used the net reclassification improvement (NRI) to measure the improvement in prediction performance gained by adding the glycemic gap to the APACHE-II score.We enrolled 518 patients, of which 87 (17.0%) died during their ICU stay. Nonsurvivors had significantly higher APACHE-II scores and glycemic gaps than survivors (P < 0.001). Critically ill patients with diabetes and a glycemic gap ≥80 mg/dL had significantly higher ICU mortality and adverse outcomes than those with a glycemic gap <80 mg/dL (P < 0.001). Incorporation of the glycemic gap into the APACHE-II score increased the discriminative performance for predicting ICU mortality by increasing the area under the ROC curve from 0.755 to 0.794 (NRI = 13.6%, P = 0.0013).The glycemic gap can be used to assess the severity and prognosis of critically ill patients with diabetes. The addition of the glycemic gap to the APACHE-II score significantly improved its ability to predict ICU mortality.
authors.affiliation: From Department of Emergency Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan (W-IL, J-CW, S-HT); Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan (W-CC); Department of Emergency and Critical Care Medicine, Taipei Medical University-Wan Fang Hospital, Taipei, Taiwan (C-WH); and School of Public Health, National Defense Medical Center, Taipei, Taiwan (C-MC).
authors.forename: Wen-I
authors.initials: WI
authors.lastname: Liao
authors.forename: Jen-Chun
authors.initials: JC
authors.lastname: Wang
authors.forename: Wei-Chou
authors.initials: WC
authors.lastname: Chang
authors.forename: Chin-Wang
authors.initials: CW
authors.lastname: Hsu
authors.forename: Chi-Ming
authors.initials: CM
authors.lastname: Chu
authors.forename: Shih-Hung
authors.initials: SH
authors.lastname: Tsai
mesh_terms: D018806:APACHE; D000368:Aged; D000369:Aged, 80 and over; D001786:Blood Glucose / Q000032:analysis*; D016638:Critical Illness / Q000401:mortality; D003920:Diabetes Mellitus / Q000097:blood / Q000175:diagnosis; D005260:Female; D006442:Glycated Hemoglobin / Q000032:analysis; D017052:Hospital Mortality; D006801:Humans; D006943:Hyperglycemia / Q000097:blood / Q000175:diagnosis / Q000209:etiology; D007362:Intensive Care Units / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D017063:Outcome Assessment, Health Care; D011237:Predictive Value of Tests; D011379:Prognosis; D012189:Retrospective Studies; D012720:Severity of Illness Index; D013312:Stress, Physiological; D013624:Taiwan / Q000453:epidemiology
chemical_list: D001786:Blood Glucose; D006442:Glycated Hemoglobin