Rouzé et al. Critical Care (2022) 26:11 https://doi.org/10.1186/s13054-021-03874-1 RESEARCH Open Access Invasive pulmonary aspergillosis among intubated patients with SARS‑CoV‑2 or influenza pneumonia: a European multicenter comparative cohort study Anahita Rouzé1,2, Elise Lemaitre1, Ignacio Martin‑Loeches3,4,5, Pedro Povoa6,7,8, Emili Diaz9, Rémy Nyga10, Antoni Torres11, Matthieu Metzelard10, Damien Du Cheyron12, Fabien Lambiotte13, Fabienne Tamion14, Marie Labruyere15, Claire Boulle Geronimi16, Charles‑Edouard Luyt17, Martine Nyunga18, Olivier Pouly19, Arnaud W. Thille20, Bruno Megarbane21, Anastasia Saade22, Eleni Magira23, Jean‑François Llitjos24, Iliana Ioannidou25, Alexandre Pierre26, Jean Reignier27, Denis Garot28, Louis Kreitmann29, Jean‑Luc Baudel30, Guillaume Voiriot31, Gaëtan Plantefeve32, Elise Morawiec33,34, Pierre Asfar35, Alexandre Boyer36, Armand Mekontso‑Dessap37, Demosthenes Makris38, Christophe Vinsonneau39, Pierre‑Edouard Floch40, Clémence Marois41,42, Adrian Ceccato43, Antonio Artigas44, Alexandre Gaudet1,45, David Nora6, Marjorie Cornu2,46, Alain Duhamel47,48, Julien Labreuche47,48, Saad Nseir1,2* and the coVAPid study group Abstract Background: Recent multicenter studies identified COVID-19 as a risk factor for invasive pulmonary aspergillosis (IPA). However, no large multicenter study has compared the incidence of IPA between COVID-19 and influenza patients. Objectives: To determine the incidence of putative IPA in critically ill SARS-CoV-2 patients, compared with influenza patients. Methods: This study was a planned ancillary analysis of the coVAPid multicenter retrospective European cohort. Con‑ secutive adult patients requiring invasive mechanical ventilation for > 48 h for SARS-CoV-2 pneumonia or influenza pneumonia were included. The 28-day cumulative incidence of putative IPA, based on Blot definition, was the primary outcome. IPA incidence was estimated using the Kalbfleisch and Prentice method, considering extubation (dead or alive) within 28 days as competing event. Results: A total of 1047 patients were included (566 in the SARS-CoV-2 group and 481 in the influenza group). The incidence of putative IPA was lower in SARS-CoV-2 pneumonia group (14, 2.5%) than in influenza pneumonia group (29, 6%), adjusted cause-specific hazard ratio (cHR) 3.29 (95% CI 1.53–7.02, p = 0.0006). When putative IPA and Aspergillus respiratory tract colonization were combined, the incidence was also significantly lower in the SARS-CoV-2 group, as compared to influenza group (4.1% vs. 10.2%), adjusted cHR 3.21 (95% CI 1.88–5.46, p < 0.0001). In the whole *Correspondence: s-nseir@chru-lille.fr 1 CHU de Lille, Médecine Intensive-Réanimation, 59000 Lille, France Full list of author information is available at the end of the article © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​ mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Rouzé et al. Critical Care (2022) 26:11 Page 2 of 14 study population, putative IPA was associated with significant increase in 28-day mortality rate, and length of ICU stay, compared with colonized patients, or those with no IPA or Aspergillus colonization. Conclusions: Overall, the incidence of putative IPA was low. Its incidence was significantly lower in patients with SARS-CoV-2 pneumonia than in those with influenza pneumonia. Clinical trial registration The study was registered at ClinicalTrials.gov, number NCT04​359693. Keywords: Invasive pulmonary aspergillosis, Severe influenza, COVID-19, Mechanical ventilation, Intensive care unit Background the coVAPid study are described elsewhere [20]. Briefly, Invasive pulmonary aspergillosis (IPA) was reported to consecutive adult patients with SARS-CoV-2 pneumonia, be common in critically ill patients with chronic obstruc- influenza pneumonia, or no viral infection at ICU admis- tive pulmonary disease (COPD) [1], acute respiratory sion, who required invasive mechanical ventilation for distress syndrome (ARDS) [2], cirrhosis [3], acute hepa- more than 48 h, were included. Only patients with SARS- titis [4], or immunosuppression [5]. Previous studies also CoV-2 pneumonia, or influenza pneumonia, were eligible highlighted a relationship between IPA and outcomes, for the current ancillary study. Patients with missing data including mortality, duration of mechanical ventilation, regarding the primary outcome were excluded from the and ICU length of stay [6]. Recently, critically ill patients current analysis. receiving invasive mechanical ventilation for severe influ- The Ethics Committee and Institutional Review Board enza were identified as a high-risk population for IPA of the Lille University Hospital approved the study [7]. Influenza-associated IPA (IAPA) was also reported protocol (Comité de Protection des Personnes Ouest to be associated with increased risk for mortality in this VI; approved by April 14, 2020; registration number population. RIPH:20.04.09.60039) as minimal-risk research using Case series, rapidly followed by single-center and large data collected for routine clinical practice and waived multicenter studies, highlighted a link between COVID- the requirement for informed consent. Patients (or their 19 pneumonia and IPA. The incidence of IPA ranges proxies) received written information about the study from 4.8 to 23% of patients with SARS-CoV-2 pneumonia and could refuse to participate. The study was registered receiving invasive mechanical ventilation [8–17]. Some at ClinicalTrials.gov, number NCT04359693. of these studies also showed that COVID-19-associated IPA (CAPA) was associated with increased mortality and Definitions longer duration of mechanical ventilation, and ICU stay Blot criteria were used for IPA diagnosis, as primary out- [16]. To the best of our knowledge, only one retrospective come [21]. When at least one criterion necessary for the study compared the incidence of IPA between COVID- diagnosis of putative IPA according to Blot definition was 19 ARDS patients and other-viruses-related ARDS [18]. not met, the case was classified as Aspergillus coloniza- This study suggested that COVID-19 was associated with tion. Verweij criteria were used for probable IPA diagno- reduced incidence of IPA as compared to other ARDS sis, as a secondary outcome (Additional file 1: Table E1) patients. However, the number of included patients was [19]. Suspected IPA refers to clinical suspicion associ- limited (n = 172) and the study was performed in a single ated with any positive serum or respiratory sample for center. Aspergillus. Therefore, we conducted this planned ancillary study of the coVAPid European multicenter cohort to determine Outcomes the incidence of putative IPA in SARS-CoV-2 pneumo- The primary outcome of our study was the incidence of nia, compared to influenza pneumonia, in intubated crit- putative IPA, according to Blot definition. The second- ically ill patients. Secondary objectives were to determine ary outcomes included the incidence of probable IPA, the impact of putative IPA on morbidity and mortality, according to Verweij definition; and outcomes of puta- and the incidence of probable IPA, based on Verweij defi- tive IPA, including mechanical ventilation duration, ICU nition [19]. length of stay, and 28-day mortality. Methods Statistical analysis Study design and population Quantitative variables were expressed as median (inter- This study was a planned ancillary analysis of the coV- quartile range) and categorical variables were expressed APid multicenter retrospective observational cohort, as numbers (percentage). Patient characteristics at ICU conducted in 36 ICUs in Europe. The methods used in admission and during ICU stay were described, in each Rouzé et al. Critical Care (2022) 26:11 Page 3 of 14 Fig. 1 Flowchart. Suspected IPA refers to clinical suspicion associated with any positive serum or respiratory sample for Aspergillus. Putative IPA and Aspergillus colonization are defined according to Blot definition. IPA, invasive pulmonary aspergillosis group, according to aspergillosis status (none, Aspergil- before ICU admission, ARDS on admission, corticos- lus colonization, and putative IPA), without formal sta- teroid treatment during ICU stay) [23]. Cause-specific tistical comparisons. The 28-day cumulative incidence of hazard ratios (cHR) and their 95% confidence intervals putative or probable IPA, or combination of colonization (CIs) associated with SARS-CoV-2 pneumonia, against and putative IPA were estimated using Kalbfleisch and influenza pneumonia, were derived from Cox’s models as Prentice method, considering extubation (dead or alive) effect sizes. within 28 days as competing event. For the incidence of We assessed the association of putative IPA with putative IPA according to Blot definition, occurrence patient’s outcomes censored at day 28 (overall survival, of Aspergillus colonization was treated as a competing mechanical ventilation duration, length of ICU stay) event, in addition to extubation [22]. using a Cox’s regression model (with sandwich covari- Regarding the causal relationship of interest, we ance estimation to account for center clustering effect) assessed the association of study groups with IPA performed on the whole study population, combining (according to both definitions, as well as combining the two groups), with cause-specific hazard for mechani- together colonization and putative IPA) using cause- cal ventilation duration (considering extubation alive as specific Cox’s proportional hazard models, with sand- event of interest and death under mechanical ventilation wich covariance estimation to account for center as competing event), and for length of ICU stay (con- clustering effect. We considered previously cited compet- sidering ICU discharge alive as event of interest, and ing events, before and after adjustment for pre-specified death during ICU as competing event), including study confounders (simplified acute physiology score (SAPS) II, group, IPA, and interaction between IPA status and study COPD, immunosuppression, recent antibiotic treatment group. IPA was treated as a time-dependent covariate, as Rouzé et al. Critical Care (2022) 26:11 Page 4 of 14 Table 1 Patient characteristics at ICU admission according to study group and aspergillosis status based on Blot definition SARS-CoV-2 pneumonia Influenza pneumonia n = 566 n = 481 No putative IPA, Aspergillus Putative IPA No putative IPA, Aspergillus Putative IPA or colonization colonization (n = 14) or colonization colonization (n = 29) (n = 543) (n = 9) (n = 432) (n = 20) Age, years 64 (55 to 71) 63 (62 to 68) 67 (52 to 75) 62 (53 to 71) 61 (51 to 71) 58 (52 to 64) Men 387/543 (71.3) 8/9 (88.9) 11/14 (78.6) 271/432 (62.7) 13/20 (65.0) 14/29 (48.3) Body mass ­index†, kg/m2 28.7 (25.7 to 31.2 (26.5 to 32.5) 29.9 (28.6 to 31.8) 27.7 (23.3 to 32.7) 29.0 (25.7 to 30.4) 25.2 (21.5 to 28.5) 33.6) Severity scores SAPS ­II‡ 41 (32 to 56) 44 (37 to 48) 36 (31 to 48) 50 (39 to 64) 57 (42 to 65) 47 (36 to 63) SOFA ­score§ 6 (3 to 8) 6 (5 to 9) 5 (4 to 7) 8 (6 to 11) 7 (6 to 10) 7 (4 to 12) Comorbidities scores McCabe classification Non-fatal 454/518 (87.6) 8/9 (88.9) 11/14 (78.6) 288/410 (70.2) 17/18 (94.4) 19/27 (70.4) Fatal < 5 years 58/518 (11.2) 1/9 (11.1) 3/14 (21.4) 107/410 (26.1) 1/18 (5.6) 6/27 (22.2) Fatal < 1 year 6/518 (1.2) 0/9 (0.0) 0/14 (0.0) 15/410 (3.7) 0/18 (0.0) 2/27 (7.4) Charlson Comorbidity 3 (1 to 4) 4 (2 to 5) 2.5 (2 to 5) 3 (2 to 5) 4 (2 to 6) 3 (1 to 4) ­Indexll Chronic diseases Diabetes mellitus 159/540 (29.4) 5/9 (55.6) 4/14 (28.6) 94/425 (22.1) 4/20 (20.0) 6/28 (21.4) Chronic kidney disease 29/535 (5.4) 3/8 (37.5) 1/14 (7.1) 35/427 (8.2) 1/20 (5.0) 3/27 (11.1) Heart disease 98/535 (18.3) 2/9 (22.2) 2/14 (14.3) 108/426 (25.4) 3/20 (15.0) 6/29 (20.7) Chronic heart failure 19/534 (3.6) 2/8 (25.0) 0/14 (0.0) 35/426 (8.2) 1/20 (5.0) 1/28 (3.6) COPD 35/536 (6.5) 0/8 (0.0) 2/14 (14.3) 119/426 (27.9) 7/20 (35.0) 3/28 (10.7) Chronic respiratory failure 19/534 (3.6) 0/8 (0.0) 1/14 (7.1) 62/426 (14.6) 2/20 (10.0) 2/28 (7.1) Cirrhosis 8/535 (1.5) 0/8 (0.0) 0/14 (0.0) 14/426 (3.3) 1/20 (5.0) 1/28 (3.6) Immunosuppression 46/535 (8.6) 2/8 (25.0) 2/14 (14.3) 93/429 (21.7) 2/20 (10.0) 11/29 (37.9) Hematological malignancy 5/534 (0.9) 0/8 (0.0) 1/14 (7.1) 24/428 (5.6) 1/20 (5.0) 5/29 (17.2) Solid cancer 25/534 (4.7) 0/8 (0.0) 0/14 (0.0) 37/428 (8.6) 1/20 (5.0) 1/29 (3.4) Organ transplant 5/534 (0.9) 1/8 (12.5) 0/14 (0.0) 7/428 (1.6) 0/20 (0.0) 4/29 (13.8) HIV 3/534 (0.6) 0/8 (0.0) 0/14 (0.0) 5/428 (1.2) 0/20 (0.0) 0/29 (0.0) Immunosuppressive drugs 21/534 (3.9) 2/8 (25.0) 2/14 (14.3) 44/428 (10.3) 0/20 (0.0) 7/29 (24.1) Active smoking 29/536 (5.4) 0/8 (0.0) 0/14 (0.0) 130/426 (30.5) 8/20 (40.0) 11/29 (37.9) Alcohol abuse 33/534 (6.2) 1/8 (12.5) 0/14 (0.0) 75/425 (17.6) 3/20 (15.0) 7/29 (24.1) Location before ICU admis- sion Home 264/543 (48.6) 3/9 (33.3) 3/14 (21.4) 251/431 (58.2) 8/20 (40.0) 15/29 (51.7) Hospital ward 199/543 (36.6) 5/9 (55.6) 11/14 (78.6) 138/431 (32.0) 7/20 (35.0) 12/29 (41.4) Another ICU 80/543 (14.7) 1/9 (11.1) 0/14 (0.0) 42/431 (9.7) 5/20 (25.0) 2/29 (6.9) Recent hospitalization 39/541 (7.2) 2/9 (22.2) 3/14 (21.4) 61/429 (14.2) 6/20 (30.0) 5/29 (17.2) (< 3 months) Recent antibiotics 70/542 (12.9) 1/9 (11.1) 3/14 (21.4) 79/427 (18.5) 8/20 (40.0) 7/29 (24.1) (< 3 months) Hospital to ICU admission, 1 (0 to 2) 1 (0 to 2) 1 (0 to 2) 0 (0 to 1) 1 (0 to 2) 1 (0 to 4) ­days¥ Hospital admission to 1 (0 to 3) 2 (1 to 7) 2 (1 to 3) 1 (0 to 2) 1 (0 to 3) 2 (0 to 5) intubation, ­days¤ Antibiotic treatment on ICU 475/533 (89.1) 7/9 (77.8) 12/14 (85.7) 369/421 (87.6) 19/20 (95.0) 28/29 (96.6) admission Causes for ICU admission Shock 99/534 (18.5) 2/7 (28.6) 1/14 (7.1) 188/423 (44.4) 9/20 (45.0) 13/26 (50.0) Acute respiratory failure 500/542 (92.3) 8/9 (88.9) 13/14 (92.9) 386/430 (89.8) 18/20 (90.0) 28/29 (96.6) Rouzé et al. Critical Care (2022) 26:11 Page 5 of 14 Table 1 (continued) SARS-CoV-2 pneumonia Influenza pneumonia n = 566 n = 481 No putative IPA, Aspergillus Putative IPA No putative IPA, Aspergillus Putative IPA or colonization colonization (n = 14) or colonization colonization (n = 29) (n = 543) (n = 9) (n = 432) (n = 20) ARDS 370/538 (68.8) 6/9 (66.7) 8/14 (57.1) 192/422 (45.5) 13/20 (65.0) 15/26 (57.7) Neurological failure 25/525 (4.8) 1/7 (14.3) 0/14 (0.0) 66/419 (15.8) 1/20 (5.0) 2/25 (8.0) Cardiac arrest 3/524 (0.6) 0/7 (0.0) 0/14 (0.0) 23/419 (5.5) 0/20 (0.0) 2/25 (8.0) Acute kidney injury 92/425 (17.5) 2/7 (28.6) 2/14 (14.3) 118/415 (28.4) 6/20 (30.0) 9/25 (36.0) † ‡ Values are as n/N (%) or median (interquartile range). 100 missing values (SARS-CoV-2, n = 32; influenza, n = 68); 64 missing values (SARS-CoV-2, n = 43; influenza, n = 21); §25 missing values (SARS-CoV-2, n = 21; influenza, n = 4); ll30 missing values (SARS-CoV-2, n = 19; influenza, n = 11); ¥59 missing values (SARS-CoV-2, n = 31; influenza, n = 28); ¤ 75 missing values (SARS-CoV-2, n = 42; influenza, n = 33) McCabe classification of comorbidities and likelihood of survival, likely to survive > 5 years, 1–5 years, < 1 year; Chronic kidney disease, KDOQI CKD classification stage 4 or 5 (creatinine clearance < 30 ml/mn); Chronic heart failure, NYHA class III or IV; Heart disease, ischemic heart disease or atrial fibrillation; Cirrhosis, Child–Pugh score B or C; antibiotic treatment on ICU admission, at least one dose of antibiotics in the first day of ICU stay; More than one cause for ICU admission is possible ARDS, acute respiratory distress syndrome; COPD, chronic obstructive pulmonary disease; ICU, intensive care unit, SAPS II, simplified acute physiology score II; SOFA, sequential organ failure assessment 3-levels categorical variable: no putative IPA or Asper- were comparable in the two groups. The dose of corticos- gillus colonization, versus Aspergillus colonization, and teroids was higher in SARS-CoV-2 pneumonia group, as putative IPA. This model accounted for exposure time of compared to influenza group (Table 2). IPA, by comparing at each follow-up time event point, the current IPA status of patients who have the event to Incidence of putative IPA according to Blot definition patients who are at risk (without the event of interest and Seventy-two patients, from 25 out of 36 participat- without the competing event for mechanical ventilation ing centers, were suspected by clinicians as having IPA, duration and length of ICU stay). The associations were including 23 in SARS-CoV-2 group, and 49 in influenza further adjusted for the same previously mentioned con- group. Of these 72 patients, 43 were classified as puta- founders [24]. tive IPA, and 29 as Aspergillus colonization, according Statistical testing was performed at the two-tailed α to Blot definition. No proven IPA was diagnosed in study level of 0.05. Data were analyzed using the SAS software patients. package, release 9.4 (SAS Institute, Cary, NC). The incidence of putative IPA was significantly lower in SARS-CoV-2 pneumonia group than in influenza pneu- Results monia group (Fig. 2A, Table 3). This difference remained Patient characteristics at ICU admission significant after adjustment for confounding factors. In total, 1047 patients were included (Fig. 1). Percent- Similarly, when combining putative IPA and Aspergil- age of men, ARDS, and body mass index were higher lus respiratory tract colonization, the incidence was still in SARS-CoV-2 group than in influenza group. SAPS significantly lower in SARS-CoV-2 group than in influ- II, sequential organ failure assessment (SOFA) score, enza group (Fig. 3, Table 3). The classification of study comorbidity scores, chronic diseases, rate of recent hos- patients, based on different definitions, is presented in pitalization, shock, cardiac arrest, neurological failure, or Additional file 1: Table E2. acute kidney injury were lower in SARS-CoV-2 pneumo- nia group, as compared to influenza pneumonia group Incidence of probable IPA according to Verweij definition (Table 1). The distribution of study patients in different Among the 72 patients suspected by physicians as having centers is presented in Additional file 1: Table E3. IPA, 58 patients were classified as probable IPA accord- ing to Verweij definition. The incidence of probable IPA Patient characteristics during ICU stay was also significantly lower in SARS-CoV-2 group, as Percentage of prone positioning, as well as total duration compared to influenza group (Fig. 2B, Table 3). This dif- of antimicrobial treatment were higher in SARS-CoV-2 ference remained significant after adjustment for con- pneumonia group than in influenza pneumonia group. founding factors at ICU admission. Corticosteroid use, ECMO, and 28-day mortality rates Rouzé et al. Critical Care (2022) 26:11 Page 6 of 14 Table 2 Patient characteristics during ICU stay according to study group and aspergillosis status based on Blot definition SARS-CoV-2 pneumonia Influenza pneumonia n = 566 n = 481 No putative IPA, Aspergillus Putative IPA No putative IPA, Aspergillus Putative IPA or colonization colonization (n = 14) or colonization colonization (n = 29) (n = 543) (n = 9) (n = 432) (n = 20) Prone positioning 363/543 (66.9) 6/8 (75.0) 12/14 (85.7) 126/432 (29.2) 8/19 (42.1) 17/29 (58.6) ECMO 58/542 (10.7) 0/9 (0.0) 2/14 (14.3) 49/432 (11.3) 5/19 (26.3) 6/28 (21.4) Ventilator-associated 271/543 (49.9) 7/9 (77.8) 7/14 (50.0) 127/432 (29.4) 7/20 (35.0) 12/29 (41.4) lower respiratory tract infections Antimicrobial treatment 12 (7 to 18) 16 (10 to 19) 18 (8 to 20) 9 (6 to 16) 21 (12 to 28) 17 (9 to 27) duration, ­days† Corticosteroids 188/517 (36.4) 3/9 (33.3) 10/14 (71.4) 161/426 (37.8) 8/20 (40.0) 12/28 (42.9) Hydrocortisone 55/512 (10.7) 2/9 (22.2) 2/14 (14.3) 92/424 (21.7) 7/20 (35.0) 7/28 (25.0) Dexamethasone 44/512 (8.6) 0/9 (0.0) 4/14 (28.6) 1/424 (0.2) 0/20 (0.0) 0/28 (0.0) Methylprednisolone 85/512 (16.6) 1/9 (11.1) 4/14 (28.6) 67/424 (15.8) 1/20 (5.0) 5/28 (17.9) Highest daily dose, ­mg‡ 100 (50 to 133) 50 (50 to 100) 100 (50 to 133) 50 (50 to 100) 50 (50 to 100) 63 (50 to 100) 28-day outcomes Mechanical ventilation 14 (8 to 22) 23 (12 to 28) 23 (17 to 28) 9 (5 to 18) 24 (11 to 28) 21 (12 to 28) duration, days Ventilator-free days 6 (0 to 16) 0 (0 to 0) 1 (0 to 2) 13 (0 to 21) 1 (0 to 12) 0 (0 to 3) ICU length of stay, days 17 (12 to 27) 28 (13 to 28) 25 (19 to 28) 13 (8 to 25) 28 (17 to 28) 25 (15 to 28) ICU-free days 0 (0 to 12) 0 (0 to 0) 0 (0 to 0) 5 (0 to 18) 0 (0 to 2) 0 (0 to 0) ICUmortality 154/543 (28.4) 4/9 (44.4) 5/14 (35.7) 111/432 (25.7) 3/20 (15.0) 11/29 (37.9) 28-day mortality 156/543 (28.7) 4/9 (44.4) 5/14 (35.7) 118/432 (27.3) 3/20 (15.0) 11/29 (37.9) † ‡ Values are as n/N (%) or median (interquartile range). 18 missing values (SARS-CoV-2, n = 15; influenza, n = 3); 8 missing values (SARS-CoV-2, n = 4; influenza, n = 4) Data are collected until day 28 or discharge of ICU ECMO, extracorporeal membrane oxygenation; ICU, intensive care unit Outcomes of putative IPA Discussion In the whole study population, putative IPA was asso- Overall, the incidence of putative IPA was low in patients ciated with significant increase in 28-day mortality with COVID-19 or influenza. Further, putative IPA inci- rate, and length of ICU stay, compared with colonized dence was significantly lower in SARS-CoV-2 pneumonia patients, or those with no IPA or Aspergillus coloniza- patients than in those with influenza pneumonia. Similar tion. These results were not confirmed in the subgroups results were found regarding probable IPA, using Verweij of patients with SARS-CoV-2 or influenza pneumonia. definition. Putative IPA was associated with significantly Only in influenza group, duration of mechanical ventila- higher 28-day mortality rate and length of ICU stay, com- tion, and ICU stay were significantly longer in patients pared with colonized patients, or those with no IPA or with putative IPA, as compared with those with no puta- Aspergillus colonization. However, IPA was not signifi- tive IPA or Aspergillus colonization (Fig. 4). cantly associated with increased duration of mechanical ventilation. Characteristics of patients with putative IPA Median time from intubation to putative IPA diagnosis Incidence of invasive pulmonary aspergillosis was longer in SARS-CoV-2 than in influenza group (11 The incidence of IPA was low in our study, and some vs. 6 days). Bronchoalveolar lavage was less frequently previous studies reported higher incidence of IAPA and performed and antifungal treatment was less frequently CAPA [7, 12–14, 16, 17]. However, in most of these stud- prescribed in SARS-CoV-2 than in influenza group ies, screening for IPA was performed routinely. Further, (Table 4). Rouzé et al. Critical Care (2022) 26:11 Page 7 of 14 Fig. 2 Cumulative incidence of putative or probable invasive pulmonary aspergillosis according to Blot (A) and Verweij (B) definitions. Cumulative incidence was estimated using Kalbfleisch and Prentice method, considering extubation (alive or due to death) within 28 days as competing event. Time axis starts at the day of intubation. IPA, invasive pulmonary aspergillosis, MV, mechanical ventilation Rouzé et al. Critical Care (2022) 26:11 Page 8 of 14 Table 3 Incidence of invasive pulmonary aspergillosis SARS-CoV-2 Influenza pneumonia Unadjusted cHR Adjusted ­cHR* p ­value* pneumonia n = 481 (95% CI) (95% CI) n = 566 Blot definition Putative invasive pulmonary aspergillosis 14/566 (2.5) 29/481 (6.0) 3.07 (1.52 to 6.19) 3.29 (1.53 to 7.02) 0.0006 Putative invasive pulmonary aspergillosis or 23/566 (4.1) 49/481 (10.2) 3.17 (1.87 to 5.35) 3.21 (1.88 to 5.46) < 0.0001 Aspergillus colonization Verweij definition Probable invasive pulmonary aspergillosis 17/566 (3.0) 41/481 (8.5) 3.54 (1.86 to 6.73) 3.78 (1.96 to 7.27) < 0.0001 Values are number of invasive pulmonary aspergillosis (28-day cumulative incidence expressed as %, considering extubation (dead or alive) as a competing event) cHR calculated using cause-specific Cox’s proportional hazard model with sandwich covariance estimation to account for center clustering effect * Adjusted for pre-specified confounders (simplified acute physiology score II, chronic obstructive pulmonary disease, immunosuppression, recent antibiotic treatment, acute respiratory distress syndrome, corticosteroid treatment), and calculated after handling missing values on covariates by multiple imputation cHR, cause-specific hazard ratio; CI, confidence interval Fig. 3 Cumulative incidence of putative invasive pulmonary aspergillosis or Aspergillus colonization according to Blot definition. Cumulative incidence was estimated using Kalbfleisch and Prentice method, considering extubation (alive or due to death) within 28 days as competing event. Time axis starts at the day of intubation. IPA, invasive pulmonary aspergillosis, MV, mechanical ventilation Rouzé et al. Critical Care (2022) 26:11 Page 9 of 14 Fig. 4 Association of putative invasive pulmonary aspergillosis, and Aspergillus colonization, according to Blot definition, with 28-day outcomes in overall population and according to study groups (SARS-CoV-2 pneumonia and influenza pneumonia). HRs were calculated using cause-specific proportional hazard models, considering death as competing event for mechanical ventilation and length of ICU stay. Adjusted HRs were calculated by including simplified acute physiology score II, chronic obstructive pulmonary disease, immunosuppression, recent antibiotic treatment before ICU admission, acute respiratory distress syndrome on admission, and corticosteroid treatment during ICU stay, as pre-specified covariates in Cox’s models (after handling missing values by multiple imputation). A HR > 1 indicates a decrease in survival (i.e., an increased risk for mortality), MV duration (i.e., an increased risk for extubation alive) and ICU length of stay (i.e., an increased risk for discharge alive) and a HR < 1 indicates an increase in survival (i.e., a decreased risk for mortality), MV duration (i.e., a decreased risk for extubation alive) and ICU length of stay (i.e., a decreased risk for discharge alive). P het indicates p value for heterogeneity in association of invasive pulmonary aspergillosis and 28-day outcomes across study groups (SARS-CoV-2 pneumonia vs. influenza pneumonia). * Not estimable, as no patient was discharged alive within 28 days. CI, confidence interval; HR, hazard ratio; ICU, intensive care unit; IPA, invasive pulmonary aspergillosis; MV, mechanical ventilation patients with no routine screening were excluded. For Comparison of invasive pulmonary aspergillosis incidence example, in the recent multicenter Mycovid study [16], between COVID‑19 and influenza patients only patients with at least 3 screening samples per- Our results suggest that IPA incidence might be lower in formed within 2 weeks were analyzed, which resulted in COVID-19 patients, compared with influenza patients. overestimating the reported incidence of CAPA (15%). Several explanations could be provided for this result. The population at risk are all patients receiving mechan- First, the percentage of patients with immunosuppression ical ventilation, and not only those receiving > 2 weeks at ICU admission was lower in COVID-19 than in influ- of invasive mechanical ventilation. Another potential enza patients (8.8% vs. 22%). However, adjustment was explanation for the high incidence of IPA reported in performed for immunosuppression, as well as for other these studies is the false positive results of galactoman- potential confounders. Second, BAL was performed nan in some patients, which is supported by the absence less frequently in COVID-19 than in influenza patients, of positive impact of antifungal treatment on mortality, which might have underestimated the incidence of IPA and the fact that some patients with CAPA survived in in the first group. This could be explained by the fear of spite of absence of any antifungal treatment [13]. On SARS-CoV-2 aerosolization and transmission to health the other hand, other well-performed single and multi- workers at the beginning of the pandemic. Other factors, center studies reported lower incidence of IPA in influ- such as most severe ARDS, and more common prone enza and COVID-19 patients [9, 10, 18, 25], which is in position use in COVID-19 than in influenza patients line with our findings. Geographical distribution and could also explain the lower rate of BAL in COVID-19 different case definitions might explain the variation in patients. Third, the mechanism of entry of SARS-CoV-2, IPA incidence. and influenza into the lower respiratory tract, and the Rouzé et al. Critical Care (2022) 26:11 Page 10 of 14 Table 4 Characteristics of patients with putative invasive pulmonary aspergillosis, according to Blot definition SARS-CoV-2 pneumonia Influenza pneumonia n = 14 n = 29 Time from hospital admission to IPA diagnosis 12 (7 to 14) 9 (6 to 11) Time from ICU admission to IPA diagnosis 11 (5 to 13) 6 (2 to 10) Time from intubation to IPA diagnosis 11 (4 to 12) 6 (2 to 9) Clinical presentation at the time of IPA diagnosis Hemoptysis 2/14 (14.3) 4/29 (13.8) Respiratory worsening 14/14 (100.0) 24/29 (82.8) New or increased fever 12/14 (85.7) 15/29 (51.7) Imaging at the time of IPA diagnosis Abnormal medical imaging (chest X-ray or CT scan) 14/14 (100.0) 29/29 (100.0) Predominant lesion on chest CT: Dense, well-circumscribed lesion with or without a halo sign 0/5 (0.0) 3/23 (13.0) Air-crescent sign 0/5 (0.0) 0/23 (0.0) Cavity 0/5 (0.0) 2/23 (8.7) Segmental or lobar consolidation 3/5 (60.0) 9/23 (39.1) Other 2/5 (40.0) 9/23 (39.1) Serum samples during ICU stay Galactomannan index > 0.5 6/12 (50.0) 20/26 (76.9) Galactomannan index at the time of IPA ­diagnosis† 0.2 (0.0 to 0.6) 0.2 (0.1 to 1.4) Highest Galactomannan ­index‡ 0.2 (0.1 to 0.8) 0.5 (0.1 to 1.4) 1,3-β-D-glucan level at time of IPA diagnosis (pg/mL)§ 63 (30 to 450) 111 (47 to 384) Highest level of 1,3-β-D-glucan (pg/mL)ll 170 (39 to 760) 178 (56 to501) Respiratory samples leading to IPA diagnosis Type of respiratory samples: Broncho-alveolar lavage 9/14 (64.3) 25/29 (86.2) Endotracheal aspirate 7/14 (50.0) 5/29 (17.2) Protected specimen brush 0/14 (0.0) 5/29 (17.2) Galactomannan index ≥ 1 4/5 (80.0) 12/17 (70.6) Galactomannan ­index¥ 3.9 (2.5 to 5.6) 2.1 (0.9 to 5.8) Positive Aspergillus PCR 9/12 (75.0) 11/15 (73.3) Mycological culture 14/14 (100.0) 29/29 (100.0) Identified species Aspergillus fumigatus 10/14 (71.4) 24/27 (88.9) Aspergillus niger 0/14 (0.0) 1/27 (3.7) Aspergillus flavus 0/14 (0.0) 1/27 (3.7) Aspergillus terreus 1/14 (7.1) 1/27 (3.7) Other species 3/14 (21.4) 0/27 (0.0) Antifungal treatment against aspergillosis Initiation of antifungal treatment 11/14 (78.6) 27/29 (93.1) Time from IPA diagnosis to first ­treatment¤ 1 (-1 to 2) 0 (0 to 2) First antifungal treatment Voriconazole 7/11 (63.6) 22/27 (81.5) Isavuconazole 1/11 (9.1) 0/27 (0.0) Caspofungin 2/11 (18.2) 2/27 (7.4) Anidulafungin 0/11 (0.0) 1/27 (3.7) Liposomal Amphotericin B 1/11 (9.1) 2/27 (7.4) Number of treatment lines used 1 7/14 (50.0) 17/29 (58.6) 2 3/14 (21.4) 7/29 (24.1) 3 1/14 (7.1) 3/29 (10.3) Rouzé et al. Critical Care (2022) 26:11 Page 11 of 14 Table 4 (continued) Values are as n/N (%) or median (interquartile range). †10 missing values (SARS-CoV-2, n = 4; influenza, n = 6); ‡5 missing values (SARS-CoV-2, n = 2; influenza, n = 3); § 20 missing values (SARS-CoV-2, n = 5; influenza, n = 15); ll15 missing values (SARS-CoV-2, n = 4; influenza, n = 11); ¥22 missing values (SARS-CoV-2, n = 5; influenza, n = 17); ¤5 missing values (SARS-CoV-2, n = 3; influenza, n = 2) Respiratory worsening is defined by significant PaO2/FiO2 ratio deterioration within 72 h of IPA diagnosis. New or increased fever is defined within 72 h of IPA diagnosis. All patients were intubated on the day of IPA diagnosis. More than on respiratory sample may be performed for IPA diagnosis ICU, intensive care unit; IPA, invasive pulmonary aspergillosis; PCR, polymerase chain reaction pulmonary lesions associated with these viruses are dif- large international study. However, galactomannan is not ferent [26, 27]. This suggests that the lower incidence of considered by this definition and some patients could IPA in COVID-19 patients might be specifically related have IPA with no Aspergillus identified in respiratory to SARS-CoV-2 infection. specimen. This might have also resulted in underestimat- ing the overall incidence of IPA. However, Verweij defini- Impact of invasive pulmonary aspergillosis on outcomes tion was also used as a secondary outcome and although In the whole study population, combining COVID-19 the overall IPA incidence was slightly higher in the two and influenza patients, IPA was significantly associated groups, IPA incidence was still significantly lower in with increased 28-day mortality and ICU length of stay. COVID-19 than in influenza patients. However, the relationship between IPA and duration of mechanical ventilation did not reach significance. In sub- Conclusions group analyses, IPA was associated with increased dura- Overall, the incidence of IPA was low in study patients. tion of mechanical ventilation and ICU length of stay in Further, putative IPA incidence was lower in SARS- influenza, but not in COVID-19 patients. Our study is COV-2 pneumonia than in influenza pneumonia probably underpowered to determine the relationship patients. Our study was performed at the beginning of between IPA and outcomes, or the relationship between COVID-19 pandemic, it would be interesting to deter- antifungal treatment and outcomes. However, previous mine how IPA incidence has evolved, especially with studies have shown a negative impact on outcome in routine use of corticosteroids in COVID-19 patients. IAPA and CAPA patients [7, 12]. Screening for IPA should be performed, based on recent recommendations, in patients with clinical deterioration Strengths and limitations or absence of improvement. To the best of our knowledge, our study is the first large multicenter cohort to compare the incidence of IPA Abbreviations between COVID-19 and influenza patients. Further, ARDS: Acute respiratory distress syndrome; CAPA: COVID-19-associated IPA; CI: competing risk analysis, and cause-specific Cox mod- Confidence interval; COPD: Chronic obstructive pulmonary disease; COVID: els were used to adjust for potential confounders. How- Coronavirus disease; HR: Hazard ratio; ICU: Intensive care unit; IPA: Invasive pulmonary aspergillosis; IAPA: Influenza-associated IPA; MV: Mechanical ever, several limitations should be acknowledged. First, ventilation; SAPS II: Simplified acute physiology score II; SARS-CoV-2: Severe the study was retrospective and there was no systematic acute respiratory syndrome coronavirus 2; SOFA: Sequential organ failure screening for IPA, which might have underestimated the assessment. overall IPA incidence. Nevertheless, physicians prospec- tively identified IPA, based on clinical suspicion; and a Supplementary Information recent taskforce recommended against routine screen- The online version contains supplementary material available at https://​doi.​ org/​10.​1186/​s13054-​021-​03874-1. ing for IPA in critically ill patients [23]. Second, no infor- mation was available on bronchoscopy macroscopic data, which may have also led to underestimating the Additional file 1. Further details on methods and results. incidence of IPA, because Aspergillus tracheobronchi- tis could not be diagnosed. Third, no information could Acknowledgements In addition to the authors, the coVAPid study group includes the follow‑ be provided on galactomannan in some study patients, ing collaborators (information to include for individual PubMed record): which might have also reduced the incidence of probable Mathilde Bouchereau, CHU de Lille, Centre de Réanimation, F-59000 Lille, IPA. Fourth, the evaluation of the two diseases was not France. Boualem Sendid, INSERM U1285, CNRS UMR 8576, Glycobiology in Fungal Pathogenesis and Clinical Applications, Université de Lille ; and Pôle de done simultaneously because of the absence of influenza Biologie-Pathologie-Génétique, Institut de Microbiologie, Service de Parasi‑ during COVID-19 pandemic. Fifth, this study was con- tologie Mycologie, CHU Lille, F-59000 Lille, France. Sean Boyd, Department of ducted in Europe, mostly in France, and the results may Intensive Care Medicine, Multidisciplinary Intensive Care Research Organiza‑ tion (MICRO), St. James’s Hospital, Dublin, Ireland. Luis Coelho, Polyvalent not be generalizable to other parts of the world. Finally, Intensive Care Unit, Hospital de São Francisco Xavier, CHLO, Lisbon, Portugal. we chose to use Blot definition for putative IPA, because NOVA Medical School, CHRC, New University of Lisbon, Portugal. Julien Maizel, this definition was validated using histological data in a Rouzé et al. Critical Care (2022) 26:11 Page 12 of 14 Service de médecine intensive réanimation, CHU Amiens Picardie, 80000 Availability of data and materials Amiens, France. Pierre Cuchet, Department of Medical Intensive Care, Caen All data needed to evaluate the conclusions in this article are present and University Hospital, F-14000 Caen, France. Wafa Zarrougui, Service de réanima‑ tabulated in the main text or the appendix. This article is the result of an origi‑ tion polyvalente, Centre hospitalier de Valenciennes, Valenciennes, France. nal retrospective cohort. For individual de-identified raw data that underlie Déborah Boyer, Medical Intensive Care Unit, Rouen University Hospital, 76000 the results reported in this article, please contact the corresponding author. Rouen, France. Jean-Pierre Quenot, Department of Intensive Care, François Mitterrand University Hospital, Dijon, France.​Mehdi Imouloudene, Service de réanimation et de soins intensifs, Centre hospitalier de Douai, Douai, France. Declarations Marc Pineton de Chambrun, Service de Médecine Intensive Réanimation, Insti‑ tut de Cardiologie, Groupe Hospitalier Pitié-Salpêtrière, Assistance Publique Ethics approval and consent to participate – Hôpitaux de Paris, Paris Cedex 13, France. Thierry Van Der Linden, Service The Ethics Committee and Institutional Review Boards approved the study de médecine intensive réanimation, Hôpital Saint Philibert GHICL, Université protocol (Comité de Protection des Personnes Ouest VI; approved by April 14, catholique, Lille, France. François Arrive, CHU de Poitiers, Médecine Intensive 2020; registration number RIPH:20.04.09.60039) as minimal-risk research using Réanimation, CIC 1402 ALIVE, Université de Poitiers, Poitiers, France. Sebastian data collected for routine clinical practice and waived the requirement for Voicu, Department of Medical and Toxicological Critical Care, Lariboisière Hos‑ informed consent. pital, INSERM UMRS-1144, Paris University, Paris, France. Elie Azoulay, Service de médecine intensive réanimation, Hôpital Saint-Louis, 75010 Paris, France. Consent for publication Edgard Moglia, Critical Care Department, Hospital Universitari Parc Taulí, Not applicable. Sabadell, Spain Frédéric Pene, Medical Intensive Care Unit, Cochin Hospital, Assistance Publique – Hôpitaux de Paris, Paris, France. Catia Cilloniz, Depart‑ Competing interests ment of Pulmonology, Hospital Clinic of Barcelona, University of Barcelona, AR received personal fees from Maat Pharma, IML received personal fees from IDIBAPS, CIBERES, Barcelona, Spain. Didier Thevenin, Service de réanimation MSD, and Gilead. AA received personal fees from Lilly Foundation, and grants polyvalente, Centre Hospitalier de Lens, Lens, France. Charlotte Larrat, Service from Grifols and Fisher & Paykel. CEL received personal fees from Bayer, Merck, de Médecine Intensive Réanimation, CHU de Tours, Hôpital Bretonneau, 37044 Aerogen, Biomérieux, ThermoFisher Brahms, and Carmat. SN received personal Tours Cedex 9, France. Laurent Argaud, Service de Médecine Intensive—Réan‑ fees from MSD, Bio-Rad, BioMérieux, Gilead, Fisher and Paykel, and Pfizer. All imation, Hôpital Edouard Herriot, Hospices Civils de Lyon, 69437 Lyon Cedex other authors declare no competing interests. 03, France. Bertrand Guidet, Service de Médecine Intensive Réanimation, Hôpi‑ tal Saint-Antoine, Assistance Publique-Hôpitaux de Paris, 75012 Paris, France. Author details 1 Matthieu Turpin, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, CHU de Lille, Médecine Intensive-Réanimation, 59000 Lille, France. 2 INSERM Service de Médecine Intensive Réanimation, Hôpital Tenon, Paris, France. Dam‑ U1285, CNRS, UMR 8576 – UGSF – Unité de Glycobiologie Structurale et ien Contou, Service de réanimation polyvalente, CH Victor Dupouy, Argenteuil, Fonctionnelle, Université de Lille, 59000 Lille, France. 3 Department of Intensive France. Alexandra Beurton, Service de Médecine Intensive-Réanimation et Care Medicine, Multidisciplinary Intensive Care Research Organization Pneumologie, Assistance Publique-Hôpitaux de Paris, Hôpital Pitié Salpêtrière, (MICRO), St. James’s Hospital, Dublin, Ireland. 4 Department of Clinical France. Julien Demiselle, Département de Médecine Intensive Réanimation, medicine, School of Medicine, Trinity College Dublin, Dublin, Ireland. 5 Hospital CHU d’Angers, 49933 Angers Cedex 9, France. David Meguerditchian, Service Clinic, IDIBAPS, Universidad de Barcelona, Ciberes, Barcelona, Spain. 6 de médecine intensive réanimation, CHU de Bordeaux, F-33000 Bordeaux, Polyvalent Intensive Care Unit, Hospital de São Francisco Xavier, CHLO, Lisbon, France. Keyvan Razazi, Assistance Publique-Hôpitaux de Paris, Hôpitaux Uni‑ Portugal. 7 NOVA Medical School, CHRC, New University of Lisbon, Lisbon, versitaires Henri-Mondor, Service de Médecine Intensive Réanimation ; Uni‑ Portugal. 8 Center for Clinical Epidemiology and Research Unit of Clinical versité Paris Est Créteil, CARMAS ; INSERM U955, Institut Mondor de recherche Epidemiology, OUH Odense University Hospital, Odense, Denmark. 9 Critical Biomédicale ; F-94010 Créteil, France. Romain Arrestier, Assistance Publique- Care Department, Hospital Universitari Parc Tauli, Sabadell, Departament de Hôpitaux de Paris, Hôpitaux Universitaires Henri-Mondor, Service de Médecine Medicina, Universitat Autonoma de Barcelona, Barcelona, Spain. 10 Service de Intensive Réanimation ; Université Paris Est Créteil, CARMAS ; INSERM U955, médecine intensive réanimation, CHU Amiens Picardie, 80000 Amiens, France. 11 Institut Mondor de recherche Biomédicale ; F-94010 Créteil, France. Vassiliki Department of Pulmonology, Hospital Clinic of Barcelona, IDIBAPS, CIBERES, Tsolaki, Intensive Care Unit, University Hospital of Larissa, University of Thessaly, University of Barcelona, Barcelona, Spain. 12 Department of Medical Intensive Biopolis Larissa, 41110 Greece. Mehdi Marzouk, Intensive Care Unit, Hôpital de Care, Caen University Hospital, 14000 Caen, France. 13 Service de réanimation Béthune, 62408 Béthune, France. Guillaume Brunin, Service de réanimation, polyvalente, Centre hospitalier de Valenciennes, Valenciennes, France. 14 Hôpital Duchenne, 62200 Boulogne-sur-Mer, France. Nicolas Weiss, Sorbonne Medical Intensive Care Unit, UNIROUEN, Inserm U1096, FHU‑ REMOD‑VHF, Université, Assistance Publique-Hôpitaux de Paris, Sorbonne Université, Rouen University Hospital, 76000 Rouen, France. 15 Department of Intensive Hôpital de la Pitié-Salpêtrière, Département de Neurologie, Unité de Médecine Care, François Mitterrand University Hospital, Dijon, France. 16 Service de Intensive Réanimation Neurologique, Paris, France. Luis Morales, Intensive Care réanimation et de soins intensifs, Centre hospitalier de Douai, Douai, France. 17 Unit, Hospital Universitari Sagrat Cor, Barcelona, Spain. Service de Médecine Intensive Réanimation, Institut de Cardiologie, Groupe Hospitalier Pitié‑Salpêtrière, Assistance Publique – Hôpitaux de Paris, Paris Authors’ contributions Cedex 13, France. 18 Service de réanimation, Centre hospitalier de Roubaix, AR, EL, IML, PP, AD, JL, and SN conceptualized and designed the study. All Roubaix, France. 19 Service de médecine intensive réanimation, Hôpital Saint authors acquired the data, drafted or critically revised the manuscript for Philibert GHICL, Université catholique, Lille, France. 20 CHU de Poitiers, important intellectual content, and gave final approval of the submitted Médecine Intensive Réanimation, CIC 1402 ALIVE, Université de Poitiers, version. AR, EL, IML, PP, RN, AT, AD, JL, and SN analyzed and interpreted the Poitiers, France. 21 Department of Medical and Toxicological Critical Care, data. SN was guarantor of the paper. All authors read and approved the final Lariboisière Hospital, INSERM UMRS‑1144, Paris University, Paris, France. 22 manuscript. Service de médecine intensive réanimation, Hôpital Saint-Louis, 75010 Paris, France. 23 First Department of Critical Care Medicine, Medical School, Funding Evangelismos Hospital, National and Kapodistrian University of Athens, Athens, This study was supported in part by a grant from the French government Greece. 24 Medical Intensive Care Unit, Cochin Hospital, Assistance Publique through the « Programme Investissement d’Avenir» (I-SITE ULNE) managed by – Hôpitaux de Paris, Paris, France. 25 First Department of Pulmonary Medicine the Agence Nationale de la Recherche (coVAPid project). Prof. Ignacio Martin- and Intensive Care Unit, Sotiria Chest Hospital, National and Kapodistrian Loeches has been supported by SFI (Science Foundation Ireland), Grant Num‑ University of Athens, Athens, Greece. 26 Service de réanimation polyvalente, ber 20/COV/0038. The funders of the study had no role in the study design, Centre Hospitalier de Lens, Lens, France. 27 Service de Médecine Intensive data collection, analysis, or interpretation, writing of the report, or decision to Réanimation, CHU de Nantes, Nantes, France. 28 Service de Médecine Intensive submit for publication. Réanimation, CHU de Tours, Hôpital Bretonneau, 37044 Tours Cedex 9, France. Rouzé et al. Critical Care (2022) 26:11 Page 13 of 14 29 Service de Médecine Intensive ‑ Réanimation, Hôpital Edouard Herriot, polyvalente, CH Victor Dupouy, Argenteuil, France. 74 Service de Médecine Hospices Civils de Lyon, 69437 Lyon Cedex 03, France. 30 Service de Médecine Intensive‑Réanimation et Pneumologie, Assistance Publique‑Hôpitaux de Intensive Réanimation, Hôpital Saint‑Antoine, Assistance Publique-Hôpitaux Paris, Hôpital Pitié Salpêtrière, Paris, France. 75 Département de Médecine de Paris, 75012 Paris, France. 31 Assistance Publique‑Hôpitaux de Paris, Service Intensive Réanimation, CHU d’Angers, 49933 Angers Cedex 9, France. 76 Service de Médecine Intensive Réanimation, Hôpital Tenon, Sorbonne Université, Paris, de médecine intensive réanimation, CHU de Bordeaux, 33000 Bordeaux, France. 32 Service de réanimation polyvalente, CH Victor Dupouy, Argenteuil, France. 77 Assistance Publique‑Hôpitaux de Paris, Hôpitaux Universitaires France. 33 Service de Médecine Intensive‑Réanimation et Pneumologie, Hôpital Henri‑Mondor, Service de Médecine Intensive Réanimation , CARMAS ; INSERM Pitié Salpêtrière, Assistance Publique-Hôpitaux de Paris, Paris, France. 34 Inserm U955, Institut Mondor de recherche Biomédicale, Université Paris Est Créteil, UMRS Neurophysiologie respiratoire expérimentale et clinique, Assistance 94010 Créteil, France. 78 Assistance Publique‑Hôpitaux de Paris, Hôpitaux Publique‑Hôpitaux de Paris, Hôpital Pitié Salpêtrière, Sorbonne Université, Universitaires Henri‑Mondor, Service de Médecine Intensive Réanimation, Paris, France. 35 Département de Médecine Intensive Réanimation, CHU CARMAS ; INSERM U955, Institut Mondor de recherche Biomédicale, Université d’Angers, 49933 Angers Cedex 9, France. 36 Service de médecine intensive Paris Est Créteil, 94010 Créteil, France. 79 Intensive Care Unit, University Hospital réanimation, CHU de Bordeaux, 33000Bordeaux, France. 37 Assistance of Larissa, University of Thessaly, 41110 Biopolis Larissa, Greece. 80 Intensive Publique‑Hôpitaux de Paris, Hôpitaux Universitaires Henri‑Mondor, Service de Care Unit, Hôpital de Béthune, 62408 Béthune, France. 81 Service de Médecine Intensive Réanimation, CARMAS ; INSERM U955, Institut Mondor de réanimation, Hôpital Duchenne, 62200 Boulogne‑sur‑Mer, France. 82 Assistance recherche Biomédicale, Université Paris Est Créteil, 94010 Créteil, France. Publique‑Hôpitaux de Paris, Sorbonne Université, Hôpital de la Pitié‑Sal‑ 38 Intensive Care Unit, University Hospital of Larissa, University of Thessaly, pêtrière, Département de Neurologie, Unité de Médecine Intensive 41110 Biopolis Larissa, Greece. 39 Intensive Care Unit, Hôpital de Béthune, Réanimation Neurologique, Sorbonne Université, Paris, France. 83 Intensive 62408 Béthune, France. 40 Service de réanimation, Hôpital Duchenne, Care Unit, Hospital Universitari Sagrat Cor, Barcelona, Spain. 62200 Boulogne‑sur‑Mer, France. 41 Assistance Publique‑Hôpitaux de Paris, Sorbonne Université, Hôpital de la Pitié‑Salpêtrière, Département de Received: 22 October 2021 Accepted: 17 December 2021 Neurologie, Unité de Médecine Intensive Réanimation Neurologique, Sorbonne Université, Paris, France. 42 Brain Liver Pitié‑Salpêtrière (BLIPS) Study Group, INSERM UMR_S 938, Centre de recherche Saint‑Antoine, Maladies métaboliques, biliaires et fibro‑inflammatoire du foie, Institute of Cardiome‑ tabolism and Nutrition (ICAN), Sorbonne Université, Paris, France. 43 Intensive References Care Unit, IDIBAPS, CIBERES, Hospital Universitari Sagrat Cor, Barcelona, Spain. 1. 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