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. 2022 Sep;292(3):438-449.
doi: 10.1111/joim.13492. Epub 2022 Apr 22.

Variations in end-of-life care practices in older critically ill patients with COVID-19 in Europe

Bernhard Wernly  1   2 , Richard Rezar  3 , Hans Flaatten  4 , Michael Beil  5 , Jesper Fjølner  6 , Raphael R Bruno  7 , Antonio Artigas  8 , Bernardo B Pinto  9 , Joerg C Schefold  10 , Malte Kelm  7 , Sviri Sigal  5 , Peter V van Heerden  11 , Wojciech Szczeklik  12 , Muhammed Elhadi  13 , Michael Joannidis  14 , Sandra Oeyen  15 , Georg Wolff  7 , Brian Marsh  16 , Finn H Andersen  17   18 , Rui Moreno  19 , Susannah Leaver  20 , Sarah Wernly  1   2 , Ariane Boumendil  21 , Dylan W De Lange  22 , Bertrand Guidet  21 , Christian Jung  7 ; COVIP study group  1
Affiliations

Variations in end-of-life care practices in older critically ill patients with COVID-19 in Europe

Bernhard Wernly et al. J Intern Med. 2022 Sep.

Abstract

Background: Previous studies reported regional differences in end-of-life care (EoLC) for critically ill patients in Europe.

Objectives: The purpose of this post-hoc analysis of the prospective multicentre COVIP study was to investigate variations in EoLC practices among older patients in intensive care units during the coronavirus disease 2019 pandemic.

Methods: A total of 3105 critically ill patients aged 70 years and older were enrolled in this study (Central Europe: n = 1573; Northern Europe: n = 821; Southern Europe: n = 711). Generalised estimation equations were used to calculate adjusted odds ratios (aORs) to population averages. Data were adjusted for patient-specific variables (demographic, disease-specific) and health economic data (gross domestic product, health expenditure per capita). The primary outcome was any treatment limitation, and 90-day mortality was a secondary outcome.

Results: The frequency of the primary endpoint (treatment limitation) was highest in Northern Europe (48%), intermediate in Central Europe (39%) and lowest in Southern Europe (24%). The likelihood for treatment limitations was lower in Southern than in Central Europe (aOR 0.39; 95% confidence interval [CI] 0.21-0.73; p = 0.004), even after multivariable adjustment, whereas no statistically significant differences were observed between Northern and Central Europe (aOR 0.57; 95%CI 0.27-1.22; p = 0.15). After multivariable adjustment, no statistically relevant mortality differences were found between Northern and Central Europe (aOR 1.29; 95%CI 0.80-2.09; p = 0.30) or between Southern and Central Europe (aOR 1.07; 95%CI 0.66-1.73; p = 0.78).

Conclusion: This study shows a north-to-south gradient in rates of treatment limitation in Europe, highlighting the heterogeneity of EoLC practices across countries. However, mortality rates were not affected by these results.

Keywords: COVID-19; critical care; frail elderly; public health systems research; resuscitation orders.

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Conflict of interest statement

J.C.S. (full departmental disclosure) reports grants from Orion Pharma, Abbott Nutrition International, B. Braun Medical AG, CSEM AG, Edwards Lifesciences Services GmbH, Kenta Biotech Ltd, Maquet Critical Care AB, Omnicare Clinical Research AG, Nestle, Pierre Fabre Pharma AG, Pfizer, Bard Medica S.A., Abbott AG, Anandic Medical Systems, Pan Gas AG Healthcare, Bracco, Hamilton Medical AG, Fresenius Kabi, Getinge Group Maquet AG, Dräger AG, Teleflex Medical GmbH, Glaxo Smith Kline, Merck Sharp and Dohme AG, Eli Lilly and Company, Baxter, Astellas, Astra Zeneca, CSL Behring, Novartis, Covidien, Phagenesis and Nycomed outside of the submitted work. The money was paid into departmental funds. No personal financial gain applied. The other authors declare that they have no conflict of interests.

Figures

Fig. 1
Fig. 1
Kaplan–Meier curve depicting survival (with 95%CI) of patients in Northern Europe (red), Central Europe (blue) and Southern Europe (green). Abbreviation: CI, confidence interval.
Fig. 2
Fig. 2
Sensitivity analyses stratifying any treatment limitations in subgroups for patient‐specific characteristics using generalised estimation equations producing population average odds ratios. The depicted adjusted ORs from model‐1 include only the intensive care unit as the panel. Abbreviations: CI, confidence interval; OR, odds ratio.
Fig. 3
Fig. 3
Sensitivity analyses stratifying any treatment limitations in subgroups for patient‐specific characteristics using generalised estimation equations producing population average odds ratios. The depicted adjusted ORs from model‐1 include only the intensive care unit as the panel. Abbreviations: CI, confidence interval; OR, odds ratio.
See this image and copyright information in PMC

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