Literature DB >> 12577770

[Admission and discharge criteria for intensive care departments].

J Bakker1, J Damen, A R H van Zanten, J H Hubben.   

Abstract

Admission and discharge criteria for intensive care departments have been drawn up in order to optimise the use of scarce and costly intensive care facilities. Every patient who could benefit from admission must be assessed by the intensive care specialist beforehand. Admission is indicated for patients with disrupted vital functions in whom recovery of dysfunctioning or failing organ systems is expected, patients who will act as organ donors and patients who undergo diagnostic investigations associated with a high risk of vital complications. Frequent assessment (several times per day) of the 'indication to stay' is indicated in the case of many patients in order to maximise the admission capacity. Discharge from the intensive care department is indicated if the vital functions are stable without life support and no longer require monitoring or treatment, if nursing the patient in the ward is possible, if continuation of the medical treatment is no longer worthwhile, if the patient no longer consents to the treatment and if the benefit of a treatment no longer outweights its negative effects.

Entities:  

Mesh:

Year:  2003        PMID: 12577770

Source DB:  PubMed          Journal:  Ned Tijdschr Geneeskd        ISSN: 0028-2162


  5 in total

1.  A Machine Learning Based Discharge Prediction of Cardiovascular Diseases Patients in Intensive Care Units.

Authors:  Kaouter Karboub; Mohamed Tabaa
Journal:  Healthcare (Basel)       Date:  2022-05-24

2.  Optimizing intensive care capacity using individual length-of-stay prediction models.

Authors:  Mark Van Houdenhoven; Duy-Tien Nguyen; Marinus J Eijkemans; Ewout W Steyerberg; Hugo W Tilanus; Diederik Gommers; Gerhard Wullink; Jan Bakker; Geert Kazemier
Journal:  Crit Care       Date:  2007       Impact factor: 9.097

3.  Towards a decision support tool for intensive care discharge: machine learning algorithm development using electronic healthcare data from MIMIC-III and Bristol, UK.

Authors:  Christopher J McWilliams; Daniel J Lawson; Raul Santos-Rodriguez; Iain D Gilchrist; Alan Champneys; Timothy H Gould; Mathew Jc Thomas; Christopher P Bourdeaux
Journal:  BMJ Open       Date:  2019-03-07       Impact factor: 2.692

4.  Forecasting the spread of SARS-CoV-2 is inherently ambiguous given the current state of virus research.

Authors:  Melissa Koenen; Marleen Balvert; Ruud Brekelmans; Hein Fleuren; Valentijn Stienen; Joris Wagenaar
Journal:  PLoS One       Date:  2021-03-03       Impact factor: 3.240

5.  Quality Indicators Compliance Survey in Indian Intensive Care Units.

Authors:  Munta Kartik; Palepu B N Gopal; Rahul Amte
Journal:  Indian J Crit Care Med       Date:  2017-04
  5 in total

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