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Readmission to medical intensive care units: Risk factors and prediction

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dc.contributor.authorJo, Yong Suk-
dc.contributor.authorLee, Yeon Joo-
dc.contributor.authorPark, Jong Sun-
dc.contributor.authorYoon, Ho Il-
dc.contributor.authorLee, Jae Ho-
dc.contributor.authorLee, Choon-Taek-
dc.contributor.authorCho, Young-Jae-
dc.date.accessioned2025-02-20T07:55:50Z-
dc.date.available2025-02-20T07:55:50Z-
dc.date.created2018-10-04-
dc.date.created2018-10-04-
dc.date.issued2015-03-
dc.identifier.citationYonsei Medical Journal, Vol.56 No.2, pp.543-549-
dc.identifier.issn0513-5796-
dc.identifier.urihttps://hdl.handle.net/10371/217071-
dc.description.abstractPurpose: 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 (Cl) 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.-
dc.language영어-
dc.publisher연세대학교의과대학-
dc.titleReadmission to medical intensive care units: Risk factors and prediction-
dc.typeArticle-
dc.identifier.doi10.3349/ymj.2015.56.2.543-
dc.citation.journaltitleYonsei Medical Journal-
dc.identifier.wosid000350011500032-
dc.identifier.scopusid2-s2.0-84922764184-
dc.citation.endpage549-
dc.citation.number2-
dc.citation.startpage543-
dc.citation.volume56-
dc.identifier.kciidART001965017-
dc.description.isOpenAccessY-
dc.contributor.affiliatedAuthorLee, Yeon Joo-
dc.contributor.affiliatedAuthorPark, Jong Sun-
dc.contributor.affiliatedAuthorYoon, Ho Il-
dc.contributor.affiliatedAuthorLee, Jae Ho-
dc.contributor.affiliatedAuthorLee, Choon-Taek-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.subject.keywordPlusCRITICALLY-ILL PATIENTS-
dc.subject.keywordPlusDISCHARGE-
dc.subject.keywordPlusSCORE-
dc.subject.keywordPlusDEATH-
dc.subject.keywordAuthorIntensive care unit-
dc.subject.keywordAuthordischarge-
dc.subject.keywordAuthorreadmission-
dc.subject.keywordAuthorrisk-
dc.subject.keywordAuthorprediction score-
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  • College of Medicine
  • Department of Medicine
Research Area Interstitial lung disease, Pneumonia, Pulmonary fibrosis, 간질성 폐질환, 폐렴, 폐섬유증

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