Literature DB >> 22172798

A model to predict short-term death or readmission after intensive care unit discharge.

Islem Ouanes1, Carole Schwebel, Adrien Français, Cédric Bruel, François Philippart, Aurélien Vesin, Lilia Soufir, Christophe Adrie, Maïté Garrouste-Orgeas, Jean-François Timsit, Benoît Misset.   

Abstract

OBJECTIVE: Early unplanned readmission to the intensive care unit (ICU) carries a poor prognosis, and post-ICU mortality may be related, in part, to premature ICU discharge. Our objectives were to identify independent risk factors for early post-ICU readmission or death and to construct a prediction model.
DESIGN: Retrospective analysis of a prospective database was done.
SETTING: Four ICUs of the French Outcomerea network participated. PATIENTS: Patients were consecutive adults with ICU stay longer than 24 hours who were discharged alive to same-hospital wards without treatment-limitation decisions. MAIN
RESULTS: Of 5014 admitted patients, 3462 met our inclusion criteria. Age was 60.6 ± 17.6 years, and admission Simplified Acute Physiology Score II (SAPS II) was 35.1 ± 15.1. The rate of death or ICU readmission within 7 days after ICU discharge was 3.0%. Independent risk factors for this outcome were age, SAPS II at ICU admission, use of a central venous catheter in the ICU, Sepsis-related Organ Failure Assessment and Systemic Inflammatory Response Syndrome scores before ICU discharge, and discharge at night. The predictive model based on these variables showed good calibration. Compared with SAPS II at admission or Stability and Workload Index for Transfer at discharge, discrimination was better with our model (area under receiver operating characteristics curve, 0.74; 95% confidence interval, 0.68-0.79).
CONCLUSION: Among patients without treatment-limitation decisions and discharged alive from the ICU, 3.0% died or were readmitted within 7 days. Independent risk factors were indicators of patients' severity and discharge at night. Our prediction model should be evaluated in other ICU populations.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 22172798     DOI: 10.1016/j.jcrc.2011.08.003

Source DB:  PubMed          Journal:  J Crit Care        ISSN: 0883-9441            Impact factor:   3.425


  30 in total

1.  Unplanned Transfers from Hospital Wards to the Neurological Intensive Care Unit.

Authors:  C A Gold; S A Mayer; L Lennihan; J Claassen; J Z Willey
Journal:  Neurocrit Care       Date:  2015-10       Impact factor: 3.210

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

Authors:  Yong Suk Jo; Yeon Joo Lee; Jong Sun Park; Ho Il Yoon; Jae Ho Lee; Choon-Taek Lee; Young-Jae Cho
Journal:  Yonsei Med J       Date:  2015-03       Impact factor: 2.759

Review 3.  Ethical aspects of admission or non-admission to the intensive care unit.

Authors:  Jean-Philippe Rigaud; Mikhael Giabicani; Marion Beuzelin; Antoine Marchalot; Fiona Ecarnot; Jean-Pierre Quenot
Journal:  Ann Transl Med       Date:  2017-12

4.  Dynamic Estimation of the Probability of Patient Readmission to the ICU using Electronic Medical Records.

Authors:  Karla Caballero; Ram Akella
Journal:  AMIA Annu Symp Proc       Date:  2015-11-05

Review 5.  Association of severity of illness and intensive care unit readmission: A systematic review.

Authors:  Evan G Wong; Ann M Parker; Doris G Leung; Emily P Brigham; Alicia I Arbaje
Journal:  Heart Lung       Date:  2016 Jan-Feb       Impact factor: 2.210

6.  Assessment of ICU readmission risk with the Stability and Workload Index for Transfer score.

Authors:  Daiane Ferreira Oakes; Ingrid Nemitz Krás Borges; Luiz Alberto Forgiarini Junior; Marcelo de Mello Rieder
Journal:  J Bras Pneumol       Date:  2014 Jan-Feb       Impact factor: 2.624

7.  Risk factors for intensive care unit readmission after lung transplantation: a retrospective cohort study.

Authors:  Hye-Bin Kim; Sungwon Na; Hyo Chae Paik; Hyeji Joo; Jeongmin Kim
Journal:  Acute Crit Care       Date:  2021-04-05

8.  Overview of medical errors and adverse events.

Authors:  Maité Garrouste-Orgeas; François Philippart; Cédric Bruel; Adeline Max; Nicolas Lau; B Misset
Journal:  Ann Intensive Care       Date:  2012-02-16       Impact factor: 6.925

9.  Predicting Intensive Care Unit Readmission with Machine Learning Using Electronic Health Record Data.

Authors:  Juan C Rojas; Kyle A Carey; Dana P Edelson; Laura R Venable; Michael D Howell; Matthew M Churpek
Journal:  Ann Am Thorac Soc       Date:  2018-07

10.  Development and implementation of a risk identification tool to facilitate critical care transitions for high-risk surgical patients.

Authors:  Rebecca L Hoffman; Jason Saucier; Serena Dasani; Tara Collins; Daniel N Holena; Meghan Fitzpatrick; Boris Tsypenyuk; Niels D Martin
Journal:  Int J Qual Health Care       Date:  2017-06-01       Impact factor: 2.038

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