Readmission to Medical Intensive Care Units: Risk Factors and Prediction.
10.3349/ymj.2015.56.2.543
- Author:
Yong Suk JO
1
;
Yeon Joo LEE
;
Jong Sun PARK
;
Ho Il YOON
;
Jae Ho LEE
;
Choon Taek LEE
;
Young Jae CHO
Author Information
1. Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Korea. lungdrcho@gmail.com
- Publication Type:Original Article ; Comparative Study
- Keywords:
Intensive care unit;
discharge;
readmission;
risk;
prediction score
- MeSH:
Aged;
Aged, 80 and over;
Cohort Studies;
Female;
Humans;
Intensive Care Units/*statistics & numerical data;
Male;
Medical Records;
Middle Aged;
Odds Ratio;
Patient Readmission/*statistics & numerical data;
Predictive Value of Tests;
Regression Analysis;
Republic of Korea;
Retrospective Studies;
Risk Factors
- From:Yonsei Medical Journal
2015;56(2):543-549
- CountryRepublic of Korea
- Language:English
-
Abstract:
PURPOSE: The objectives of this study were to find factors related to medical intensive care unit (ICU) readmission and to develop a prediction index for determining patients who are likely to be readmitted to medical ICUs. MATERIALS AND METHODS: We performed a retrospective cohort study of 343 consecutive patients who were admitted to the medical ICU of a single medical center from January 1, 2008 to December 31, 2012. We analyzed a broad range of patients' characteristics on the day of admission, extubation, and discharge from the ICU. RESULTS: Of the 343 patients discharged from the ICU alive, 33 (9.6%) were readmitted to the ICU unexpectedly. Using logistic regression analysis, the verified factors associated with increased risk of ICU readmission were male sex [odds ratio (OR) 3.17, 95% confidence interval (CI) 1.29-8.48], history of diabetes mellitus (OR 3.03, 95% CI 1.29-7.09), application of continuous renal replacement therapy during ICU stay (OR 2.78, 95% CI 0.85-9.09), white blood cell count on the day of extubation (OR 1.13, 95% CI 1.07-1.21), and heart rate just before ICU discharge (OR 1.03, 95% CI 1.01-1.06). We established a prediction index for ICU readmission using the five verified risk factors (area under the curve, 0.76, 95% CI 0.66-0.86). CONCLUSION: By using specific risk factors associated with increased readmission to the ICU, a numerical index could be established as an estimation tool to predict the risk of ICU readmission.
