Literature DB >> 26149302

Respective impact of no escalation of treatment, withholding and withdrawal of life-sustaining treatment on ICU patients' prognosis: a multicenter study of the Outcomerea Research Group.

Alexandre Lautrette1,2, Maïté Garrouste-Orgeas3, Pierre-Marie Bertrand4, Dany Goldgran-Toledano5, Samir Jamali6, Virginie Laurent7, Laurent Argaud8, Carole Schwebel9, Bruno Mourvillier10, Michaël Darmon11, Stéphane Ruckly12, Anne-Sylvie Dumenil13, Virginie Lemiale14, Bertrand Souweine4,15, Jean-François Timsit10,12.   

Abstract

PURPOSE: To assess the prevalence of decisions to forgo life-sustaining treatment (DFLST), the patients characteristics, and to estimate the impact of DFLST stages on mortality.
METHODS: Observational study of a prospective database between 2005 and 2012 from 13 ICUs. DFLST were defined as follows: no escalation of treatment (stage 1), not to start or escalate treatment even if such treatment is considered in the future; withholding (stage 2), not to start or escalate necessary treatment; withdrawal (stage 3), to stop necessary treatment. The impact of daily DFLST stage on day-30 hospital mortality was tested with a discrete-time Cox's model and adjusted for admission severity and daily SOFA score.
RESULTS: Of 10,080 patients, 1290 (13%) made DFLST. The highest DFLST stage during the ICU stay was no escalation of treatment in 339 (26%) patients, withholding in 502 (39%) patients, and withdrawal in 449 (35%) patients. Older patients, patients with at least one chronic disease, and patients with greater ICU severity were significantly more numerous in the DFLST group. Day-30 mortality was 13% for non-DFLST patients, 35% for no escalation of treatment, 75% for withholding, 93% for withdrawal. After adjustment, an increase in day-30 mortality was associated with withholding and withdrawal (hazard ratio 95% CI 5.93 [4.95-7.12] and 20.05 [15.58-25.79], P < 0.0001), but not with no escalation of treatment (HR 1.14 [0.91-1.44], P = 0.25).
CONCLUSIONS: DFLST were made in 13% of ICU patients. Withholding, withdrawal, older age, more comorbidities, and higher severity of illness were associated with higher mortality. No escalation of treatment was not associated with increased mortality.

Entities:  

Keywords:  Critical care; Decision-making; Do-not-resuscitate; End-of-life; Prognosis

Mesh:

Year:  2015        PMID: 26149302     DOI: 10.1007/s00134-015-3944-5

Source DB:  PubMed          Journal:  Intensive Care Med        ISSN: 0342-4642            Impact factor:   17.440


  37 in total

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Review 2.  Care at the end of life in critically ill patients: the European perspective.

Authors:  Thomas Fassier; Alexandre Lautrette; Magali Ciroldi; Elie Azoulay
Journal:  Curr Opin Crit Care       Date:  2005-12       Impact factor: 3.687

3.  "No escalation of treatment" as a routine strategy for decision-making in the ICU: con.

Authors:  J Randall Curtis; Gordon D Rubenfeld
Journal:  Intensive Care Med       Date:  2014-08-05       Impact factor: 17.440

4.  Defining an Intermediate Step in End-of-Life Therapy.

Authors:  Dan R Thompson
Journal:  Crit Care Med       Date:  2014-02       Impact factor: 7.598

5.  Quality of dying in the ICU: is it worse for patients admitted from the hospital ward compared to those admitted from the emergency department?

Authors:  Ann C Long; Erin K Kross; Ruth A Engelberg; Lois Downey; Elizabeth L Nielsen; Anthony L Back; J Randall Curtis
Journal:  Intensive Care Med       Date:  2014-08-13       Impact factor: 17.440

6.  End-of-life decision-making and quality of ICU performance: an observational study in 84 Italian units.

Authors:  Guido Bertolini; Simona Boffelli; Paolo Malacarne; Mario Peta; Mariano Marchesi; Camillo Barbisan; Stefano Tomelleri; Simonetta Spada; Roberto Satolli; Bruno Gridelli; Ivo Lizzola; Davide Mazzon
Journal:  Intensive Care Med       Date:  2010-05-13       Impact factor: 17.440

7.  End-of-life practices in 282 intensive care units: data from the SAPS 3 database.

Authors:  Elie Azoulay; Barbara Metnitz; Charles L Sprung; Jean-François Timsit; François Lemaire; Peter Bauer; Benoît Schlemmer; Rui Moreno; Philipp Metnitz
Journal:  Intensive Care Med       Date:  2008-10-10       Impact factor: 17.440

8.  Epidemiology of and factors associated with end-of-life decisions in a surgical intensive care unit.

Authors:  Anne Meissner; Kelly Roveran Genga; Fernando Sérgio Studart; Utz Settmacher; Gunther Hofmann; Konrad Reinhart; Yasser Sakr
Journal:  Crit Care Med       Date:  2010-04       Impact factor: 7.598

9.  Effect of decisions to withhold life support on prolonged survival.

Authors:  Yen-Yuan Chen; Alfred F Connors; Allan Garland
Journal:  Chest       Date:  2008-01-15       Impact factor: 9.410

10.  Variation in the rates of do not resuscitate orders after major trauma and the impact of intensive care unit environment.

Authors:  Avery B Nathens; Frederick P Rivara; Jin Wang; Ellen J Mackenzie; Gregory J Jurkovich
Journal:  J Trauma       Date:  2008-01
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4.  Selection and Receipt of Kidney Replacement in Critically Ill Older Patients with AKI.

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Journal:  Clin J Am Soc Nephrol       Date:  2019-03-21       Impact factor: 8.237

Review 5.  Changes in critically ill cancer patients' short-term outcome over the last decades: results of systematic review with meta-analysis on individual data.

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Journal:  Intensive Care Med       Date:  2019-05-29       Impact factor: 17.440

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Journal:  Intensive Care Med       Date:  2016-10-18       Impact factor: 17.440

8.  Withholding or withdrawing of life-sustaining therapy in older adults (≥ 80 years) admitted to the intensive care unit.

Authors:  Bertrand Guidet; Hans Flaatten; Ariane Boumendil; Alessandro Morandi; Finn H Andersen; Antonio Artigas; Guido Bertolini; Maurizio Cecconi; Steffen Christensen; Loredana Faraldi; Jesper Fjølner; Christian Jung; Brian Marsh; Rui Moreno; Sandra Oeyen; Christina Agwald Öhman; Bernardo Bollen Pinto; Ivo W Soliman; Wojciech Szczeklik; Andreas Valentin; Ximena Watson; Tilemachos Zafeiridis; Dylan W De Lange
Journal:  Intensive Care Med       Date:  2018-05-17       Impact factor: 17.440

9.  Respective impact of implementation of prevention strategies, colonization with multiresistant bacteria and antimicrobial use on the risk of early- and late-onset VAP: An analysis of the OUTCOMEREA network.

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Journal:  Ann Intensive Care       Date:  2016-04-14       Impact factor: 6.925

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