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Readmission to Medical Intensive Care Units: Risk Factors and Prediction

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 cons...

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Detalles Bibliográficos
Autores principales: Jo, Yong Suk, Lee, Yeon Joo, Park, Jong Sun, Yoon, Ho Il, Lee, Jae Ho, Lee, Choon-Taek, Cho, Young-Jae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Yonsei University College of Medicine 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4329370/
https://www.ncbi.nlm.nih.gov/pubmed/25684007
http://dx.doi.org/10.3349/ymj.2015.56.2.543
Descripción
Sumario: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.