Yonsei Med J.  2015 Mar;56(2):543-549. 10.3349/ymj.2015.56.2.543.

Readmission to Medical Intensive Care Units: Risk Factors and Prediction

• Jo YS
• Lee YJ
• Park JS
• Yoon HI
• Lee JH
• Lee CT
• Cho YJ

• KMID: 2070036
• DOI: http://doi.org/10.3349/ymj.2015.56.2.543

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.

Keyword

Intensive care unit; discharge; readmission; risk; prediction score

MeSH Terms

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

Figure

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  Fig. 1 Flow diagram of patients through the study. ICU, intensive care unit.

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  Fig. 2 Nomogram predicting the probability of ICU readmission. Instruction: locate the patient's sex on the axis. Draw a line straight upward to the point axis to determine how many points toward the probability of ICU readmission the patients receive for his or her sex. After repeating the process for each additional variable, sum the points for each of the predictors. Locate the final sum on the total point axis, and then, draw a line straight down to find the patient's probability of ICU readmission. DM, diabetes mellitus; CRRT, continuous renal replacement therapy; WBC, white blood cell; HR, heart rate; ICU, intensive care unit.

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  Fig. 3 Area under the receiver operator curve (AUC) for risk score model in discriminating ICU readmission (AUC 0.76; 95% CI 0.67-0.80 vs. AUC 0.76; 95% CI 0.66-0.86). P/F ratio, PaO2/FiO2 ratio; CI, confidence interval.

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