SESSION TYPE: ICU: Improving Outcomes
PRESENTED ON: Sunday, October 21, 2012 at 10:30 AM - 11:45 AM
PURPOSE: Despite initial recovery from critical illness requiring intensive care unit (ICU) admission, many patients remain at risk of subsequent deterioration and unplanned readmission to the ICU. Readmitted patients have higher mortality rates and significantly greater lengths of stay. Scoring systems designed to measure the severity of illness for patients admitted to the ICU have been used to predict the risk of readmission to the ICU, but are often too complex to be practical. The aim of this study is to identify risk factors that predict early unplanned ICU readmission through examining variables that are simple and readily available at the time of ICU dismissal.
METHODS: Consecutive adults discharged from the medical ICU of a tertiary referral teaching hospital between January 2009 and June 2011 were studied retrospectively. Patients were limited to medical critical care discharges. The analysis included demographic data, source of admission, co-morbidities, vital signs, laboratory values and Glascow Coma Score (GCS) prior to discharge from the ICU. Logistic regression was used to construct receiver operating characteristic (ROC) curves. Area under the ROC curve (AUROC) was used to judge the predictive power of the variables.
RESULTS: Complete information was available for 6194 patients. 48% were male, 62% were African American and the mean age was 58. 227 (3.66%) patients were readmitted or died unexpectedly within 72 hours from discharge. Risk factors that predicted early readmission to the ICU were the shock index (heart rate/ systolic blood pressure), absolute value of temperature difference from 37 C, respiratory rate, GCS, BUN/Cr ratio, hemoglobin level, and absolute lymphocyte count (p<0.015 for all). The AUROC was 0.74.
CONCLUSIONS: We identified a number of variables that showed good ability to predict patients at risk of early ICU readmission. These variables are readily available at the bedside and can be used at time of dismissal to influence the discharge decision. Developing practical scoring systems based on the above mentioned variables to predict ICU readmission should be pursued by other studies in the future.
CLINICAL IMPLICATIONS: Predict early unplanned ICU readmission through examining variables that are simple and readily available at the time of ICU dismissal.
DISCLOSURE: The following authors have nothing to disclose: Raid Abu-awwad, Gregory Buran
No Product/Research Disclosure InformationHenry Ford Hospital, Detroit, MI