Age and Ageing 2022; 51: 1–10 © The Author(s) 2022. Published by Oxford University Press on behalf of the British Geriatrics https://doi.org/10.1093/ageing/afab278 Society. All rights reserved. For permissions, please email: journals.permissions@oup.com This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com RESEARCH PAPER Health-related quality of life in older patients surviving ICU treatment for COVID-19: results from an international observational study of patients older than 70 years Ivo W. Soliman1 , Susannah Leaver2 , Hans Flaatten3 , Jesper Fjølner4 , Bernhard Wernly5 , Raphael R. Bruno6 , Antonio Artigas7 , Bernardo Bollen Pinto8 , Joerg C. Schefold9 , Michael Beil10 , Sigal Sviri10 , Peter Vernon van Heerden11 , Wojciech Szczeklik12 , Muhammed Elhadi13 , Michael Joannidis14 , Sandra Oeyen15 , Tilemachos Zafeiridis16,† , Jakob Wollborn17 , Maria Jose Arche Banzo18 , Kristina Fuest19 , Brian Marsh20 , Finn H. Andersen21,22 , Rui Moreno23 , Ariane Boumendil24,25 , Bertrand Guidet24,25 , Christian Jung26 , Dylan W. De Lange1 , The COVIP-study group* 1 Department of Intensive Care Medicine, University Medical Center, University of Utrecht, Utrecht, the Netherlands 2 General Intensive Care, St George’s University Hospitals NHS Foundation Trust, London, UK 3 Department of Clinical Medicine, University of Bergen, Department of Anaestesia and Intensive Care, Haukeland University Hospital, Bergen, Norway 4 Department of Intensive Care, Aarhus University Hospital, Aarhus, Denmark 5 Department of Anaesthesiology, Perioperative Medicine and Intensive Care Medicine Paracelsus Medical University of Salzburg, Salzburg, Austria 6 Division of Cardiology, Pulmonology, and Vascular Medicine, University Duesseldorf, Duesseldorf, Germany 7 Department of Intensive Care Medicine, CIBER Enfermedades Respiratorias, Corporacion Sanitaria Universitaria Parc Tauli, Autonomous University of Barcelona, Sabadell, Spain 8 Department of Acute Medicine, Geneva University Hospitals, Geneva, Switzerland 9 Department of Intensive Care Medicine, Inselspital, Universitätsspital, University of Bern, Bern, Switzerland 10 Department of Medical Intensive Care, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel 11 General Intensive Care Unit, Department of Anesthesiology, Critical Care and Pain Medicine, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel 12 Center for Intensive Care and Perioperative Medicine, Jagiellonian University Medical College, Krakow, Poland 13 Faculty of Medicine, University of Tripoli, Tripoli, Libya 14 Division of Intensive Care and Emergency Medicine, Department of Internal Medicine, Medical University Innsbruck, Innsbruck, Austria 15 Department of Intensive Care 1K12IC, Ghent University Hospital, Ghent, Belgium 16 Intensive Care Unit, General Hospital of Larissa, Larissa, Greece 17 Department of Anesthesiolgy, Perioperative and Pain Medicine, Brigham and Women’s Hospital, Havard Medical School, Boston, MA, USA 18 Servicio de Medicina Intensiva, Hospital Clínico Universitario Lozano Blesa, Zaragoza, Spain 19 Department of Anesthesiology and Intensive Care, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany 20 Department of Anesthesia and Intensive Care Medicine, Mater Misericordiae University Hospital, Dublin, Ireland 21 Department of Anaesthesia and Intensive Care, Ålesund Hospital, Ålesund, Norway 22 Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway 23 Unidade de Cuidados Intensivos Neurocríticos e Trauma. Hospital de São José, Centro Hospitalar Universitário de Lisboa Central, Faculdade de Ciências Médicas de Lisboa, Nova Médical School, Lisbon, Portugal 1 I. W. Soliman et al. 24 Sorbonne Universités, UPMC Univ Paris 06, INSERM, UMR_S 1136, Institut Pierre Louis d’Epidémiologie et de Santé Publique, Equipe: épidémiologie hospitalière qualité et organisation des soins, F-75012 Paris, France 25 Assistance Publique - Hôpitaux de Paris, Hôpital Saint-Antoine, service de réanimation médicale, F-75012 Paris, France 26 Division of Cardiology, Pulmonology, and Vascular Medicine, University Duesseldorf, Duesseldorf, Germany Address correspondence to: D. W. de Lange, Department of Intensive Care Medicine, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands. Tel: +31 88 75 585 61; Fax: +31 88 75 556 77. Email: d.w.delange@umcutrecht.nl † In memory of our colleague and friend Tilemachos Zafeiridis ∗ Acknowledgement of the COVIP-study group collaborators: Philipp Eller, Michael Joannidis, Dieter Mesotten, Pascal Reper, Sandra Oeyen, Walter Swinnen, Helene Brix, Jens Brushoej, Maja Villefrance, Helene Korvenius Nedergaard, Anders Thais Bjerregaard, Ida Riise Balleby, Kasper Andersen, Maria Aagaard Hansen, Stine Uhrenholt, Helle Bundgaard, Jesper Fjølner, Aliae Ar Hussein Mohamed, Rehab Salah, Yasmin Khairy NasrEldin Mohamed Ali, Kyrillos Wassim, Yumna A Elgazzar, Samar Tharwat, Ahmed Y Azzam, Ayman Abdelmawgoad Habib, Hazem Maarouf Abosheaishaa, Mohammed A Azab, Susannah Leaver, Arnaud Galbois, Bertrand Guidet, Cyril Charron, Emmanuel Guerot, Guillaume Besch, Jean-Philippe Rigaud, Julien Maizel, Michel Djibré, Philippe Burtin, Pierre Garcon, Saad Nseir, Xavier Valette, Nica Alexandru, Nathalie Marin, Marie Vaissiere, Gaëtan Plantefeve, Thierry Vanderlinden, Igor Jurcisin, Bruno Megarbane, Anais Caillard, Arnaud Valent, Marc Garnier, Sebastien Besset, Johanna Oziel, Jean-Herlé Raphaelen, Stéphane Dauger, Guillaume Dumas, Bruno Goncalves, Gaël Piton, Christian Jung, Raphael Romano Bruno, Malte Kelm, Georg Wolff, Eberhard Barth, Ulrich Goebel, Eberhard Barth, Anselm Kunstein, Michael Schuster, Martin Welte, Matthias Lutz, Patrick Meybohm, Stephan Steiner, Tudor Poerner, Hendrik Haake, Stefan Schaller, Detlef Kindgen-Milles, Christian Meyer, Muhammed Kurt, Karl Friedrich Kuhn, Winfried Randerath, Jakob Wollborn, Zouhir Dindane, Hans-Joachim Kabitz, Ingo Voigt, Gonxhe Shala, Andreas Faltlhauser, Nikoletta Rovina, Zoi Aidoni, Evangelia Chrisanthopoulou, Antonios Papadogoulas, Mohan Gurjar, Ata Mahmoodpoor, Abdullah Khudhur Ahmed, Brian Marsh, Ahmed Elsaka, Sigal Sviri, Vittoria Comellini, Ahmed Rabha, Hazem Ahmed, Silvio A Namendys-Silva, Abdelilah Ghannam, Martijn Groenendijk, Marieke Zegers, Dylan de Lange, Alex Cornet, Mirjam Evers, Lenneke Haas, Tom Dormans, Willem Dieperink, Luis Romundstad, Britt Sjøbø, Finn H Andersen, Hans Frank Strietzel, Theresa Olasveengen, Michael Hahn, Miroslaw Czuczwar, Ryszard Gawda, Jakub Klimkiewicz, Maria Campos de LurdesSantos, André Gordinho, Henrique Santos, Rui Assis, Ana Isabel Pinho Oliveira, Mohamed Raafat Badawy, David Perez-Torres, Gemma Gomà, Mercedes Ibarz Villamayor, Angela Prado Mira, Patricia Jimeno Cubero, Susana Arias Rivera, Teresa Tomasa, David Iglesias, Eric Mayor Vázquez, Cesar Aldecoa, Aida Fernández Ferreira, Begoña Zalba-Etayo, Isabel Canas-Perez, Luis Tamayo-Lomas, Cristina Diaz-Rodriguez, Susana Sancho, Jesús Priego, Enas M Y Abualqumboz, Momin Majed Yousuf Hilles, Mahmoud Saleh, Nawfel Ben-HAmouda, Andrea Roberti, Alexander Dullenkopf, Yvan Fleury, Bernardo Bollen Pinto, Joerg C Schefold, Mohammed Al-Sadawi, Nicolas Serck, Elisabeth Dewaele, Pritpal Kumar, Camilla Bundesen, Richard Innes, James Gooch, Lenka Cagova, Elizabeth Potter, Michael Reay, Miriam Davey, Sally Humphreys, Caroline Hauw Berlemont, Benjamin Glenn Chousterman, François Dépret, Alexis Ferre, Lucie Vettoretti, Didier Thevenin, Andreas Faltlhauser, Milena Milovanovic, Philipp Simon, Marco Lorenz, Sandra Emily Stoll, Simon Dubler, Kristina Fuest, Francesk Mulita, Eumorifa Kondili, Ioannis Andrianopoulos, Iwan Meynaar, Alexander Daniel Cornet, Britt Sjøbøe, Anna Kluzik, Paweł Zatorski, Tomasz Drygalski, Wojciech Szczeklik, Joanna Solek-Pastuszka, Dariusz Onichimowski, Jan Stefaniak, Karina Stefanska-Wronka, Ewa Zabul, Filipe Sousa Cardoso, Maria José Arche Banzo, Teresa Maria Tomasa-Irriguible, Ángela Prado Mira, Susana Arias-Rivera, Fernando Frutos-Vivar, Sonia Lopez-Cuenca, Pablo Ruiz de Gopegui, Nour Abidi, Ivan Chau, Richard Pugh, Sara Smuts. Abstract Background: health-related quality of life (HRQoL) is an important patient-centred outcome in patients surviving ICU admission for COVID-19. It is currently not clear which domains of the HRQoL are most affected. Objective: to quantify HRQoL in order to identify areas of interventions. Design: prospective observation study. Setting: admissions to European ICUs between March 2020 and February 2021. Subjects: patients aged 70 years or older admitted with COVID-19 disease. Methods: collected determinants include SOFA-score, Clinical Frailty Scale (CFS), number and timing of ICU procedures and limitation of care, Katz Activities of Daily Living (ADL) dependence score. HRQoL was assessed at 3 months after ICU admission with the Euro-QoL-5D-5L questionnaire. An outcome of ≥4 on any of Euro-QoL-5D-5L domains was considered unfavourable. Results: in total 3,140 patients from 14 European countries were included in this study. Three months after inclusion, 1,224 patients (39.0%) were alive and the EQ-5D-5L from was obtained. The CFS was associated with an increased odds ratio for an unfavourable HRQoL outcome after 3 months; OR 1.15 (95% confidence interval (CI): 0.71–1.87) for CFS 2 to OR 4.33 (95% CI: 1.57–11.9) for CFS  7. The Katz ADL was not statistically significantly associated with HRQoL after 3 months. 2 Health-related quality of life in older patients surviving ICU treatment for COVID-19 Conclusions: in critically ill old intensive care patients suffering from COVID-19, the CFS is associated with the subjectively perceived quality of life. The CFS on admission can be used to inform patients and relatives on the risk of an unfavourable qualitative outcome if such patients survive. Keywords: Intensive Care Unit (ICU), frailty, Quality of Life, Survival, Older people, COVID-19 Key Points • Three-month survival of patients ≥70 years admitted to the Intensive Care Unit for COVID-19 is limited (39%). • Half of the surviving patients have severe to extreme problems on at least one of the Health-related quality of life (HRQoL) domains. • Frailty is associated with severe to extreme problems on the HRQoL outcome. Introduction was endorsed by the European Society of Intensive Care Medicine. In short, the ‘COVID-19 in very old intensive In 2019, the novel corona virus (SARS-CoV-2) caused a care patients’ (COVIP-study) was conceived in the first worldwide pandemic. Particularly older patients (>70 years) months of 2021 when the first wave hit Europe. Basically, it became severely ill and a disproportionate number needed was an observational study looking at patients’ demograph- admission to an intensive care unit (ICU) [1]. Despite ics, treatment modalities while admitted to the ICU and improvements in treatments, a large proportion of these outcomes of these patients up to 3 months after admission older patients still succumb to the disease and the 30-day to the ICU [2]. Such research was already performed in a survival is 59% [2]. general but older ICU population (>80 years old) [2, 9, Patients who survive the ICU admission often experience 10]. As a consequence, research protocols could swiftly be serious sequelae: post-traumatic stress disorder, anxiety, adapted to the COVID-19 population and ethical clearance depression, muscle weakness, cognitive impairment and was swift because it had already been evaluated, albeit in many others [3]. Additionally, a significant number of another domain of patients. The study was registered at patients developed what is now named ‘long-covid’, which ClinicalTrials.gov (ID: NCT04321265) and adhered to the has a strong influence on the physical and mental aspects European Union General Data Privacy Regulation (GDPR). of life and well-being. Such unwanted side effects of This investigation aimed to understand which factors are ICU-treatment may profoundly impact the quality of associated with survival and quality of life in older COVID- life of surviving patients [3, 4]. However, which adverse 19 patients (the so-called COVIP-study, COVID-19 in VIP) outcomes have the largest impact on self-perceived, health- [2]. As in the previous VIP studies [2, 9, 10], national coor- related quality of life is currently unclear. Without such dinators recruited the ICUs, coordinated national and local information, we cannot properly intervene to prevent ethical permissions, and supervised patient recruitment at poor quality of life. Moreover, many older patients (and the national level. Ethical approval was mandatory for study their relatives) prioritise a good quality of life over long- participation and was obtained for each country separately. term survival [5]. Vice versa, there is a strong relationship Usually, informed consent was mandatory for inclusion, but between quality of life after ICU survival and the self- in some countries, this was not required with the reference to reported unacceptable outcome one year after intensive the critical condition and difficulties with patients consent. care treatment [6]. We might even consider intensive care treatment disproportionate if it only causes suffering and anguish while not reaching the personal goal of a good Study population quality of life [7]. For all these reasons, an assessment of The COVIP-study recruited consecutive patients with a the patient’s pre-ICU functional abilities at ICU admission positive COVID-19 test and aged 70 years or older who and assessments for post-intensive care syndrome-related were admitted to an ICU. The dataset was extracted from problems has been advocated [8]. the COVIP study database on 14th of May 2021 and This prospective multinational, observational study aims contained patients from 19th March to 4th February 2021. to report on outcomes of the various domains of the self- Prospective data collection commenced at ICU admission. reported health-related quality of life assessment of former The admission day was defined as day 1, and all consecutive critically ill COVID-19 patients. A second aim is to study days were numbered sequentially from that date. whether adverse outcomes are associated with frailty. Data collection Methods The methods have been described in previous publications [2]. In short, all centres used a uniform online electronic case Design and settings report form (eCRF). Of each patient, we recorded (i) infor- This multicentre, prospective study is part of the Very old mation present on admission (i.e. gender, weight, length, Intensive care Patients (VIP) project (www.vipstudy.org) and days in hospital prior to ICU admission, days with symptoms 3 I. W. Soliman et al. prior to hospital admission, comorbidities, medication use, online). The self-perceived quality of life is by definition habitat before admission, arterial blood gasses on admis- subjective, and therefore, there is no normative value at sion, sequential organ failure assessment (SOFA), the clinical which one can dichotomise quality of life into ‘good’ or frailty scale (CFS) and the Katz activities of daily living), ‘poor’ [12]. For study purpose, we defined a level 4 answer (ii) we collected data on treatments provided to (or withheld or worse (‘I have severe/extreme problems’) as an outcome from) the patient while being admitted to ICU (i.e. mechan- considered ‘unfavourable’. ical ventilation, prone positioning, tracheostomy performed, vasoactive drugs used, use of renal replacement treatment Statistical analysis used, use of non-invasive ventilation, use of extra-corporeal Descriptive data were computed based on all case records, membrane oxygenation, use of antimicrobials, and life sus- showing the amount of missing data per variable. Contin- taining treatments withheld or withdrawn while being in the uous data points were expressed as median ± interquartile ICU) and (iii) outcomes of the patients (i.e. survival to ICU range. Differences between independent groups were calcu- discharge, ICU length of stay, vital status at 30 days, vital lated using the Mann–Whitney U-test. Categorical data are status at 3 months and EuroQoL quality of life questionnaire expressed as numbers (percentage). The Chi-square test was at 3 months). applied to calculate differences between groups. Records of patients for whom data were not complete Multiple variables showed missing data. For the multivari- were completed using multiple imputations (see Statistical able analysis of associating CFS to HRQoL (see below), the section). For the SOFA score on admission, each element complete cases considering all required variables numbered was entered and the eCRF calculated the total score. Fur- 585 of the total 1,224 patients (47.8%). We used multiple thermore, we assessed the need for non-invasive or invasive imputation techniques to avoid the bias due to loss to follow- ventilation, prone positioning, tracheostomy, vasopressor use up when a complete case analysis would have been per- and renal replacement therapy. The CRF also documented formed. A total of 100 imputed datasets were generated by any limitation of life-sustaining therapy during the ICU-stay. multiple imputations through chained equations using the ‘mice’ package in R v4.1.0. All imputation models allowed Frailty and comorbidities for non-linear associations of any included continuous The frailty level prior to the acute illness and hospital admis- variables. sion was assessed using the CFS [2, 9, 10]. Univariate and multivariable logistic regression analyses were performed to assess associations with baseline vari- Data storage ables and the studied HRQoL outcomes. We chose the co- The eCRF and database were hosted on a secure server in variables for the multivariable model (age, gender, Katz, Aarhus University, Denmark. SOFA score and CFS) based on clinical experience and previous literature [2, 9, 10]. In analyses where CFS was Health-related quality of life shown per level, CFS 7, 8 and 9 were combined because there were too few patients in CFS 8 and 9 to allow a The quality of life was assessed by the EurQol-5D-5L ques- proper analysis of these levels separately. Rubin’s rules were tionnaire at 3 months post-discharge. This is a self-reported used when pooling the results from the imputed datasets. All assessment of generic health that consists of five dimen- tests were two-sided, and a P-value of <0.05 was considered sions (mobility, self-care, usual activities, pain/discomfort statistically significant. R version 4.1.0 was used for all and anxiety/depression), each with five levels of functioning statistical analyses. (e.g. n ‘no problems’, ‘slight problems’, ‘moderate problems’, ‘severe problems’ and ‘unable to’/‘extreme problems’ for all of these dimensions) (see Supplementary Table 1, Supple- Results mentary data are available in Age and Ageing online). This health state classifier can describe 3,125 unique health states Study population that are often reported as vectors ranging from 11,111 In total, 3,140 patients ≥70 years old were included in the (full health) to 55,555 (worst health). Numerous societal COVIP-study. Ninety days after inclusion (ICU admission), value sets have been derived from population-based valu- 1,224 were still alive of which 707 (57.8% of the survivors) ation studies around the world that, when applied to the answered the quality of life questionnaire. Figure 1 depicts health state vector, resulting in a preference-based score that the flow of patients and Table 1 summarises the demograph- typically ranges from states worse than dead (<0) to 1 ics of all the patients that were included in the study versus (full health), anchoring dead at 0. In addition, the measure those who survived up to 3 months (but did not answer includes a visual analogue scale where health is rated by the versus those who answered the questionnaire). patient on a scale from 0 (worse imaginable health) to 100 The patients who answered the questionnaire were statis- (best imaginable health) [11]. tically similar to those who did not answer this questionnaire On each of the 5 domains of the Euro-QoL-5D-5L except for age. Those who did not answer the questionnaire patients can answer on 5 different levels (from level 1: no were younger (non-responders were 73 versus 74 years of problem to level 5: extreme problems) (see Supplemental the responders, P = 0.003). All other variables were equally Table 1, Supplementary data are available in Age and Ageing distributed among responders and non-responders. 4 Health-related quality of life in older patients surviving ICU treatment for COVID-19 Table 1. Patient demographics Patient characteristic Total population missing data from Respon- Non- P value for difference total population ders responders between responders and non-responders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . N 1,224 707 517 Age (years) 74 [72–77] 4 74 73 [71–77] 0.003 [72–77] Sex (male) 856 (70%) 3 487 369 (71%) 0.444 (69%) BMI 28 [25–31] 76 28 28 [25–31] 0.599 [25–31] Proven COVID-19 1,198 (98%) 6 693 505 (98%) 0.978 (98%) Hospital stay prior to ICU 2 [1–5] 9 2 [1–5] 2 [1–5] 0.13 admission (days) Duration of symptoms prior to 7 [4–10] 97 7 [4–10] 7 [4–10] 0.5 hospital admission Diabetes 360 (29%) 6 212 148 (29%) 0.664 (30%) Heart failure 135 (11%) 11 87 48 (9%) 0.122 (12%) Hypertension 802 (66%) 9 456 346 (67%) 0.355 (64%) Ischemic heart disease 239 (20%) 14 137 102 (20%) 1 (19%) Pulmonary failure 250 (20%) 5 156 94 (18%) 0.11 (22%) Clinical Frailty Scale 1 119 (10%) 68 78 41 (8%) 0.366 (11%) CFS 2 354 (29%) 222 132 (26%) (31%) CFS 3 427 (35%) 239 188 (36%) (34%) CFS 4 151 (12%) 93 58 (11%) (13%) CFS 5 43 (4%) 27 (4%) 16 (3%) CFS 6 40 (3%) 27 (4%) 13 (3%) CFS 7 21 (2%) 14 (2%) 7 (1%) CFS 8 1 (0%) 1 (0%) 0 (0%) CFS 9 0 (0%) 0 (0%) 0 (0%) SOFA-score 4 [3–7] 20 4 [3–7] 4 [2–7] 0.129 Intubated 775 (63%) 5 448 327 (63%) 0.947 (63%) Duration of invasive mechanical 14 [8–27] 26 14 14 [8–27] 0.478 ventilation (days) [7–26] Prone positioning 394 (32%) 454 227 167 (32%) 0.858 (32%) Initiation of prone positioning after 0 [0–0] 4 0 [0–0] 0 [0–0] 0.001 admission to the ICU (days) Vasoactive medication 735 (60%) 9 430 305 (59%) 0.566 (61%) Duration of vasoactive medication 4 [2–9] 39 5 [2–10] 4 [2–8] 0.015 (days) RRT 109 (9%) 3 68 41 (8%) 0.345 (10%) Duration of RRT (days) 6 [2–15] 6 11 4 [2–8] 0.006 [3–18] Non-invasive ventilation 303 (25%) 7 192 111 (21%) 0.025 (27%) Duration of non-invasive 1 [1–3] 19 1 [1–3] 1 [1–3] 0.140 ventilation (days) ECMO 2 (0%) 0 2 (0%) 0 (0%) 0.548 Length of stay on the ICU (days) 12 [6–27] 22 13 12 [6–27] 0.717 [6–27] BMI means Body Mass Index, SOFA means Sequential Organ Failure Score, RRT means renal replacement therapy, ECMO means Extracorporeal Membrane Oxygenation. All continuous variables are represented as median with [interquartile range]. 5 I. W. Soliman et al. Figure 1. Flow of patients. Health-related quality of life of the patients survived up to 90-days. Even worse, within The EQ-5D-5L questionnaire was completed by or com- the group of surviving patients 48% (n = 592) experienced pleted for n = 707 patients. In n = 441 (62.4%), the ques- ‘severe problems’ or ‘extreme problems’ in at least one of tionnaire was completed by the patients, in n = 146 (20.7%) the five domains of the EQ-5D-5L questionnaire. ‘Severe by family or care-givers, in n = 114 (16.1%) extracted from problems’ were mentioned by 41% (n = 496), and ‘extreme hospital records or by n = 6 (0.8%) through other means. problems’ on one of the five domains in 30% (n = 371). The patients that did answer the questionnaire (n = 707) There was a clear association between the level of frailty showed that n = 182 patients (25.7%) complained of having before hospitalisation and reporting severe problems in any an impairment at a level 4 or 5 answer (‘I have severe/extreme one of the 5 domains of the health-related quality of life ques- problems’) in at least one of the five domains (see Figure 2). tionnaire. Particularly pre-frail and frail patients (defined as a After correction for various variables in the multivariable CFS of 4 or above) showed an independent association with analysis, the odds of having a complaint of level 4 or worse persisting problems after 90 days leading to a diminished were correlated with increasing frailty scales: the odds for quality of life. CFS 2 were 1.17 (95% confidence interval (CI): 0.72– The association between frailty before acute ICU admis- 1.91) and increased to an odds of 4.22 (95%CI: 1.06–16.8) sion and outcome at 90-days was as expected. Frailty is for patients with CFS 7 and over (combined group) (see defined as ‘a clinically recognisable state of increased vul- Table 2). If the patients with a CFS 1–3 are combined into nerability resulting from ageing-associated decline in reserve the reference group (‘non-frail’) then patients with CFS 4–5 and function across multiple physiologic systems such that have an odds of 1.61 (95%CI: 1.13–2.3) and patients with the ability to cope with acute stressors is comprised’. Being a CFS  7 have an odds of 2.99 (95%CI: 1.43–6.25) of admitted with a severe disease such as COVID-19 definitely having a complaint of equal to or more than a level 4 in fulfils the criteria of an acute stressor. However, this research any of the domains. The differences between these groups is one of the first to show which proportion of older patients are summarised in a spider graph depicting all 5 domains with COVID-19 will have persisting problems and their (see Figure 3). severity. Previous research in a small cohort of a slightly younger ICU population (mean age 65 years) showed that 67% of the surviving patients had a decreased HRQoL Discussion and 62% had a decline in functional status [13]. These patients were asked to recall their quality of life prior to In this multicentre study in patients older than 70 years becoming ill and compare it to their current functioning and admitted to an ICU with COVID-19 found that only 39% self-perceived quality of life. A small Italian observational 6 Health-related quality of life in older patients surviving ICU treatment for COVID-19 Figure 2. Association between CFS and severe or worse complaints on any of the 5 domains of the Quality of Life questionnaire. Percentage of patients complaining of any impairment more than or equal to level 4 answer (‘I have severe complaints . . . ’) on one of the 5 domains of the Health-Related Quality of Life questionnaire (EuroQoL-5D-5L). Based on data after multiple imputation. Table 2. Odds of having at least one outcome in the quality of life domains of level 4 (moderate to extreme complaints) corrected for Katz, age, gender and day 1 SOFA score CFS score OR 95%CI lower limit 95%CI upper limit P-value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.17 0.72 1.91 0.526 3 1.62 1.01 2.6 0.046 4 1.89 1.08 3.29 0.025 5 3.77 1.66 8.59 0.002 6 4.17 1.71 10.17 0.002 7+ 4.22 1.06 16.78 0.041 study looked at the HRQoL of surviving adult patients and patients not affected by COVID-19. However, in another, compared that to age- and gender-matched controls [3]. In younger age group (mean age 48 years), the HRQoL was that study, survival at 90-days was 58% and the response reduced in one third of the patients, but the patients assessed rate among survivors was impressive; 78% of the surviving their overall health-related quality of life as expressed by an patients answered their questionnaire. They showed that visual analogue scale (the EQ-VAS) to be equivalent to nor- surviving COVID-19 patients had a HRQoL that was (sta- mative values for the general adult Italian population [14]. tistically) worse than an age- and gender-matched control The authors of that study realised that this rather young and 7 I. W. Soliman et al. Figure 3. Spider graph depicting outcome of quality of life in non-frail, pre-frail and frail patients. Patients with a CFS 1-3 are considered ‘non-frail’ (green line). Patients with a CFS 4-5 are considered ‘pre-frail’ (purple line) and patients with CFS 7+ are considered ‘frail’ (orange line). On the QoL domains, 1 denotes ‘no problems’, 2 ‘slight problems’, 3 ‘moderate problems’, 4 ‘severe problems’ and 5 ‘extreme problems’. previously healthy population might not be representative Limitations and strengths for a frailer population. However, this points towards one of the most important One of the major limitations of this study is that it has been limitations of self-perceived and self-reported HRQoL: it is performed in a ‘selected ICU population’. This means that subjective, cultural and changes over time [12]. While the the patients had been subject to triage decisions prior to ICU Euro-QoL questionnaire tries to objectify certain persisting admission. Some patients have been considered to be ‘too complaints, the normative societal values for the HRQoL good’ or ‘too bad’ for ICU admission and these patients were index are different for various countries. This implies that never part of the study population. This might result in a various countries, religions and/or cultures value outcomes potentially biased study population, with a better outcome differently. It, therefore, remains difficult to compare out- than the overall patient group of ≥70 years. This, however, is comes between individuals or between countries. This is reality in every day ICU care and is true for every ICU study. illustrated by the fact that many European countries do Indeed, the starting point of our study was the older patient not yet have a normative societal value sets to calculate that had been admitted to the ICU. an HRQoL index based on the EQ5D five-level variant, The follow-up was limited to 3 months. Some disabilities specially stratified by age. We have chosen to circumvent this require more time to improve and it is, therefore, con- limitation by assessing which proportion of patients will have ceivable that some of the patients will experience further severe problems in one of the five domains of the HRQoL. improvements of their present health-related quality of life. We find this to be clinically relevant regardless of country Another limitation is that in most countries, written and might be used to counsel older patients or their relatives. informed consent was mandatory. We know, from previous Many critically ill patients and particularly their relatives research, that this results in a selected study population that want to know the chances of survival and their health- is less ill than when written informed consent would not related quality of life if they survive COVID-19. Depending have been necessary (the real ICU population will be more upon the level of frailty prior to admission, we can now severely ill) [15]. inform which proportion of patients will have persisting And finally, association should not be confused with problems (see Supplementary Table 2, Supplementary data causation. The fact that frail patients with end up with more are available in Age and Ageing online). severe problems in the health-related quality of life domains 8 Health-related quality of life in older patients surviving ICU treatment for COVID-19 does not mean that frailty is causing this or will always study was supported in France by a grant from Fondation cause this. Assistance Publique-Hôpitaux de Paris pour la recherche is However, the strong features of this observational cohort greatly appreciated. In Norway, the study was supported are that it is performed in many European countries, is by a grant from the Health Region West. In addition, quite large and represents a diverse mixture of cultures and the study was supported by a grant from the European religions. The results of this research can be translated into Open Science Cloud (EOSC). EOSCsecretariat.eu has advice for older patients in whom are admitted to the ICU received funding from the European Union’s Horizon and want to discuss outcome trajectories. Again, particularly, Programme call H2020-INFRAEOSC-05-2018-2019, older patients (and their relatives) prioritise a good quality grant agreement number 831644. This work was supported of life over long-term survival [5]. Future research might by the Forschungskommission of the Medical Faculty of focus on a certain quality of life that is unacceptable for the Heinrich-Heine-University Düsseldorf, No. 2018-32 to individual patients and we need to establish predictors for G.W. and No. 2020-21 to R.R.B. for a Clinician Scientist such unwanted outcomes. Track. Conclusion References Half of the older critically ill old patients who have sur- 1. Reports of the Dutch ICU registry. https://stichting-nice.nl/ vived COVID-19 reported severe to extreme problem after COVID_report.pdf (26 July 2021, date last accessed). 3 months, which was associated with the level of frailty: 2. Jung C, Flaatten H, Fjølner J et al. The impact of frail patients had a larger proportion of patients experiencing frailty on survival in elderly intensive care patients with severe to extreme problems on any of the HRQoL domains. COVID-19: the COVIP study. Crit Care 2021; 25: 149. Such information is important to convey to older patients (or https://doi.org/10.1186/s13054-021-03551-3. their relatives) when they need to be admitted to the ICU. 3. Gamberini L, Mazzoli CA, Sintonen H et al. Quality of life of COVID-19 critically ill survivors after ICU discharge: 90 Supplementary Data: Supplementary data mentioned in days follow-up. Qual Life Res 2021; 30: 2805–17. the text are available to subscribers in Age and Ageing online. 4. Albu S, Zozaya NR, Murillo N, García-Molina A, Chacón CAF, Kumru H. What’s going on following acute covid-19? Acknowledgements: Individual participant data that Clinical characteristics of patients in an out-patient rehabili- underlie the results reported in this article are available tation program. NeuroRehabilitation 2021; 48: 469–80. to investigators whose proposed use of the data has 5. Heyland DK, Dodek P, Mehta S et al. Admission of the very been approved by the COVIP steering committee. The elderly to the intensive care unit: family members’ perspectives anonymised data can be requested from the authors if on clinical decision-making from a multicenter cohort study. required, provided that both parties will adhere to all the Palliat Med 2015; 29: 324–35. legal GDPR requirements. 6. Kerckhoffs MC, Kosasi FFL, Soliman IW et al. Determinants of self-reported unacceptable outcome of intensive care treat- Declaration of Conflicts of Interest: The authors declare ment 1 year after discharge. Intensive Care Med 2019; 45: that they have no competing interests. J.C.S. reports grants 806–14. (full departmental disclosure) from Orion Pharma, Abbott 7. Kon AA, Shepard EK, Sederstrom NO et al. Defining futile Nutrition International, B. Braun Medical AG, CSEM and potentially inappropriate interventions: a policy state- AG, Edwards Lifesciences Services GmbH, Kenta Biotech ment from the Society of Critical Care Medicine Ethics Committee. Crit Care Med 2016; 44: 1769–74. Ltd, Maquet Critical Care AB, Omnicare Clinical Research 8. Mikkelsen ME, Still M, Anderson BJ et al. Society of Critical AG, Nestle, Pierre Fabre Pharma AG, Pfizer, Bard Medica Care Medicine’s international consensus conference on predic- S.A., Abbott AG, Anandic Medical Systems, Pan Gas AG tion and identification of long-term impairments after critical Healthcare, Bracco, Hamilton Medical AG, Fresenius Kabi, illness. Crit Care Med 2020; 48: 1670–9. Getinge Group Maquet AG, Dräger AG, Teleflex Medical 9. Flaatten H, De Lange DW, Morandi A et al. The impact of GmbH, Glaxo Smith Kline, Merck Sharp and Dohme AG, frailty on ICU and 30-day mortality and the level of care in Eli Lilly and Company, Baxter, Astellas, Astra Zeneca, CSL very elderly patients (≥ 80 years). Intensive Care Med 2017; Behring, Novartis, Covidien, Philips Medical, Phagenesis 43: 1820–8. Ltd, Prolong Pharmaceuticals and Nycomed outside the 10. Guidet B, de Lange DW, Boumendil A et al. The contribution submitted work. The money went into departmental funds. of frailty, cognition, activity of daily life and comorbidities No personal financial gain applied. on outcome in acutely admitted patients over 80 years in European ICUs: the VIP2 study. Intensive Care Med 2020; 46: 57–69. Declaration of Sources of Funding: No (industry) spon- 11. van Hout B, Janssen MF, Feng YS et al. Interim scoring for sorship has been received for this investigator-initiated study. the EQ-5D-5L: mapping the EQ-5D-5L to EQ-5D-3L value This study was endorsed by the European Society of Intensive sets. Value Health 2012; 15: 708–15. Care Medicine (ESICM). Free support for running the 12. Carr AJ, Gibson B, Robinson PG. Measuring quality of life: is electronic database and was granted from the Department quality of life determined by expectations or experience? BMJ of Epidemiology, University of Aarhus, Denmark. The 2001; 322: 1240–3. 9 I. W. Soliman et al. 13. Taboada M, Moreno E, Cariñena A et al. Quality of life, 15. Kho ME, Duffett M, Willison DJ, Cook DJ, Brouwers MC. functional status, and persistent symptoms after intensive care Written informed consent and selection bias in observational of COVID-19 patients. Br J Anaesth 2021; 126: e110–3. studies using medical records: systematic review. BMJ 2009; 14. Carenzo L, Protti A, Dalla Corte F et al. Short-term health- 338: b866. https://doi.org/10.1136/bmj.b866. related quality of life, physical function and psychological consequences of severe COVID-19. Ann Intensive Care 2021; Received 29 September 2021; editorial decision 17 11: 91. https://doi.org/10.1186/s13613-021-00881-x. November 2021 10