Literature DB >> 25684007

Readmission to medical intensive care units: risk factors and prediction.

Yong Suk Jo1, Yeon Joo Lee1, Jong Sun Park1, Ho Il Yoon1, Jae Ho Lee1, Choon-Taek Lee1, Young-Jae Cho2.   

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.

Entities:  

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

Mesh:

Year:  2015        PMID: 25684007      PMCID: PMC4329370          DOI: 10.3349/ymj.2015.56.2.543

Source DB:  PubMed          Journal:  Yonsei Med J        ISSN: 0513-5796            Impact factor:   2.759


  19 in total

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Authors:  A L Rosenberg; C Watts
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2.  A nationwide survey of intensive care unit discharge practices.

Authors:  Claudia-Paula Heidegger; Miriam M Treggiari; Jacques-André Romand
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Review 3.  Severity of illness and risk of readmission to intensive care: a meta-analysis.

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4.  Bed rationing and allocation in the intensive care unit.

Authors:  G A Skowronski
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5.  Critically ill patients readmitted to intensive care units--lessons to learn?

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Journal:  Intensive Care Med       Date:  2002-12-18       Impact factor: 17.440

6.  Predicting death and readmission after intensive care discharge.

Authors:  A J Campbell; J A Cook; G Adey; B H Cuthbertson
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7.  The Stability and Workload Index for Transfer score predicts unplanned intensive care unit patient readmission: initial development and validation.

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8.  A modified McCabe score for stratification of patients after intensive care unit discharge: the Sabadell score.

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Review 10.  A systematic review of tools for predicting severe adverse events following patient discharge from intensive care units.

Authors:  F Shaun Hosein; Niklas Bobrovitz; Simon Berthelot; David Zygun; William A Ghali; Henry T Stelfox
Journal:  Crit Care       Date:  2013-06-29       Impact factor: 9.097

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4.  Explainable Machine Learning on AmsterdamUMCdb for ICU Discharge Decision Support: Uniting Intensivists and Data Scientists.

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5.  Clinical and Laboratory Profile of COVID-19 Pneumonia Patients With a Complicated Post-Intensive Care Unit Hospital Course.

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6.  Risk Stratification Model for Predicting Coronary Care Unit Readmission.

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7.  Prognostic value of National Early Warning Score and Modified Early Warning Score on intensive care unit readmission and mortality: A prospective observational study.

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