Hyperglycemia in Medically Critically Ill Patients: Risk Factors and Clinical Outcomes

Autor: Michael Goldberg, Christian D. Becker, Ralph L. Sabang, Monica F. Nogueira Cordeiro, Corey Scurlock, Ibrahim A. Hassan
Rok vydání: 2020
Předmět:
Zdroj: The American journal of medicine. 133(10)
ISSN: 1555-7162
Popis: We aimed to robustly categorize glycemic control in our medical intensive care unit (ICU) as either acceptable or suboptimal based on time-weighted daily blood glucose averages of180 mg/dL or180 mg/dL; identify clinical risk factors for suboptimal control; and compare clinical outcomes between the 2 glycemic control categories.This was a retrospective cohort study in an academic tertiary and quaternary medical ICU.Out of total of 974 unit stays over a 2-year period, 920 had complete data sets available for analysis. Of unit stays 63% (575) were classified as having acceptable glycemic control and the remaining 37% were classified (345) as having suboptimal glycemic control. Adjusting for covariables, the odds of suboptimal glycemic control were highest for patients with diabetes mellitus (odds ratio [OR] 5.08, 95% confidence interval [CI] 3.72-6.93), corticosteroid use during the ICU stay (OR 4.50, 95% CI 3.21-6.32), and catecholamine infusions (OR 1.42, 95% CI 1.04-1.93). Adjusting for acuity, acceptable glycemic control was associated with decreased odds of hospital mortality but not ICU mortality (OR 0.65, 95% CI 0.48-0.88 and OR 0.81, 95% CI 0.55-1.17, respectively). Suboptimal glycemic control was associated with increased odds of longer-than-predicted ICU and hospital stays (OR 1.76, 95% CI 1.30-2.38 and OR 1.50, 95% CI 1.12-2.01, respectively).In our high-acuity medically critically ill patient population, achieving time-weighted average daily blood glucose levels180 mg/dL reliably while in the ICU significantly decreased the odds of subsequent hospital mortality. Suboptimal glycemic control during the ICU stay, on the other hand, significantly increased the odds of longer-than-predicted ICU and hospital stay.
Databáze: OpenAIRE