Saura et al. Critical Care (2022) 26:292 https://doi.org/10.1186/s13054-022-04170-2 RESEARCH Open Access Relationship between corticosteroid use and incidence of ventilator‑associated pneumonia in COVID‑19 patients: a retrospective multicenter study Ouriel Saura1, Anahita Rouzé1,2, Ignacio Martin‑Loeches3,4,5, Pedro Povoa6,7,8, Louis Kreitmann30, Antoni Torres12, Matthieu Metzelard11, Damien Du Cheyron13, Fabien Lambiotte14, Fabienne Tamion15, Marie Labruyere16, Claire Boulle Geronimi17, Charles‑Edouard Luyt18, Martine Nyunga19, Olivier Pouly20, Arnaud W. Thille21, Bruno Megarbane22, Anastasia Saade23, Eleni Magira24, Jean‑François Llitjos25, Iliana Ioannidou26, Alexandre Pierre27, Jean Reignier28, Denis Garot29, Jean‑Luc Baudel31, Guillaume Voiriot32, Gaëtan Plantefeve33, Elise Morawiec34,35, Pierre Asfar36, Alexandre Boyer37, Armand Mekontso‑Dessap38,39,40, Fotini Bardaka41, Emili Diaz9,10, Christophe Vinsonneau42, Pierre‑Edouard Floch43, Nicolas Weiss44,45,46, Adrian Ceccato47, Antonio Artigas48, David Nora6, Alain Duhamel49,50, Julien Labreuche50, Saad Nseir1,2* and coVAPid Study Group Abstract Background: Ventilator-associated pneumonia (VAP) is common in patients with severe SARS-CoV-2 pneumonia. The aim of this ancillary analysis of the coVAPid multicenter observational retrospective study is to assess the relation‑ ship between adjuvant corticosteroid use and the incidence of VAP. Methods: Planned ancillary analysis of a multicenter retrospective European cohort in 36 ICUs. Adult patients receiv‑ ing invasive mechanical ventilation for more than 48 h for SARS-CoV-2 pneumonia were consecutively included between February and May 2020. VAP diagnosis required strict definition with clinical, radiological and quantitative microbiological confirmation. We assessed the association of VAP with corticosteroid treatment using univariate and multivariate cause-specific Cox’s proportional hazard models with adjustment on pre-specified confounders. Results: Among the 545 included patients, 191 (35%) received corticosteroids. The proportional hazard assump‑ tion for the effect of corticosteroids on the incidence of VAP could not be accepted, indicating that this effect varied during ICU stay. We found a non-significant lower risk of VAP for corticosteroid-treated patients during the first days in the ICU and an increased risk for longer ICU stay. By modeling the effect of corticosteroids with time-dependent coef‑ ficients, the association between corticosteroids and the incidence of VAP was not significant (overall effect p = 0.082), with time-dependent hazard ratios (95% confidence interval) of 0.47 (0.17–1.31) at day 2, 0.95 (0.63–1.42) at day 7, 1.48 (1.01–2.16) at day 14 and 1.94 (1.09–3.46) at day 21. *Correspondence: s-nseir@chru-lille.fr 1 Médecine Intensive-Réanimation, CHU de Lille, 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. Saura et al. Critical Care (2022) 26:292 Page 2 of 11 Conclusions: No significant association was found between adjuvant corticosteroid treatment and the incidence of VAP, although a time-varying effect of corticosteroids was identified along the 28-day follow-up. Keywords: SARS-CoV-2, COVID-19, Ventilator-associated lower respiratory tract infections, Corticosteroids Introduction and ICU length of stay, based on the occurrence of VAP. The novel severe acute respiratory syndrome coronavi- We also evaluated microbiology of VAP in both groups of rus 2 (SARS-CoV-2) can lead to a severe respiratory tract patients. infection (coronavirus disease 2019 (COVID-19)) and hit the world with multiple pandemic waves from Decem- Methods ber 2020. During the first surge of COVID-19, studies Study design and population reported that around 80% of patients admitted to hos- This is a planned ancillary analysis of the coVAPid study, pital for COVID-19 would require oxygen support [1, 2] which design was previously described [8]. Briefly, it was and a high rate of them an invasive mechanical ventila- a multicenter retrospective observational cohort con- tion (IMV) due to acute respiratory distress syndrome ducted in 36 ICUs in Europe (28 centers in France, 3 in (ARDS) leading to high mortality rates [3, 4]. IMV during Spain, 3 in Greece, 1 in Portugal and 1 in Ireland) aimed ARDS exposes patients to severe complications, such as to determine the relationship between SARS-CoV-2 ventilator-associated pneumonia (VAP). pneumonia as compared to influenza pneumonia or no Several studies have recently described the high inci- viral infection and the incidence of VA-LRTI. The pre- dence of ventilator-associated lower respiratory tract sent analysis was restricted to the population of SARS- infection (VA-LRTI) in COVID-19 patients ranging CoV-2 pneumonia. Patients were 18-year-old or above from 30 to 84% [4–7]. Previous studies demonstrated a and received IMV for more than 48 h. Patients were significantly higher incidence of VA-LRTI and notably excluded if data related to corticosteroid treatment were VAP in SARS-CoV-2 pneumonia patients versus non- not available. SARS-CoV-2 pneumonia patients [5, 8–10]. High rates Patients were consecutively included in each center of ARDS, alveolar inflammation, prolonged IMV, lung starting from the beginning of the COVID-19 pandemic microbiota alteration, COVID-19-related specific lesions, if they had a positive polymerase chain reaction (PCR) neuromuscular blocking and immunosuppressive agent test for the SARS-CoV-2 virus on nasopharyngeal swab use could explain this high rate of VAP in SARS-CoV-2 or respiratory secretions. pneumonia patients [11, 12]. The Ethics Committee and Institutional Review Boards The positive results of the randomized controlled approved the coVAPid study protocol (Comité de Pro- multicenter trial RECOVERY [13] and its further con- tection des Personnes Ouest VI; approved by April 14, firmation in large meta-analysis [14] have placed dexa- 2020; registration number RIPH:20.04.09.60039) as methasone as the first line agent for treating hospitalized minimal-risk research using data collected for routine COVID-19 patients with a significantly improved 28-day clinical practice. The requirement for informed consent survival, especially in the subgroup of patients invasively was waived, and patients or their relative received infor- ventilated. Yet, the impact of such treatment on the inci- mation about the study and were given the possibility to dence of VAP in COVID-19 patients is still a matter for refuse the use of their personal data. The coVAPid data- debate, as available data are scarce and conflicting [3, base was registered into the “Commission Nationale de 15–19]. l’Informatique et des Libertés” in accordance with the Hence, we sought to determine the relationship French law. The coVAPid study was registered at Clinical- between adjuvant corticosteroid treatment and the inci- Trials.gov, number NCT04359793. dence of VAP in a large cohort of COVID-19 patients Demographic characteristics, severity scores and invasively ventilated for more than 48 h, during the first comorbidities, past medical history and ongoing treat- surge of the SARS-CoV-2 pandemic. Our hypothesis was ments, prior hospitalization and exposition to antibiot- that VAP incidence would be higher in corticosteroid- ics (during the past three months) were collected for treated versus non-treated COVID-19 patients. each patient at baseline. During hospitalization, clini- The primary objective was to compare the incidence of cal, biological and radiological findings were recorded VAP in patients receiving or not adjuvant corticosteroid as well as the different treatments received during ICU treatment. Secondary objectives were to determine the stay (i.e., prone positioning, extra corporeal membrane relationship between adjuvant corticosteroid treatment oxygenation (ECMO)). Antibiotic and corticosteroid and 28-day mortality, duration of mechanical ventilation use was recorded as type, time of initiation, duration of Saura et al. Critical Care (2022) 26:292 Page 3 of 11 exposure before occurrence of VAP, maximum daily dose exposure were calculated as effect size. Hazard assump- expressed as prednisone equivalent dose (for corticoster- tion proportionality of corticosteroids during fol- oid treatment). low-up was assessed by using the scaled Schoenfeld residuals plots. Since the assumption was not satisfied, the corticosteroids effect was modeled using time- Objectives and outcomes dependent coefficient by including corticosteroids and Our primary objective was to determine the impact of corticosteroids*time interaction terms as covariates corticosteroid use on the incidence of VAP in SARS- into cause-specific Cox’s models and the overall cor- CoV-2 pneumonia patients. The primary outcome was ticosteroids effect was assessed by the likelihood ratio the occurrence of VAP [8, 20]. Briefly, new or progres- test. sive infiltrates on chest X-rays and two of the following Similarly, we investigated the association of corti- criteria were needed for the diagnosis of VAP: (1) leuco- costeroids with patient’s outcomes censored at day- cyte count greater than 12,000 cells per μL or less than 28 (overall survival, MV duration, length of ICU stay) 4000 cells per μL, (2) hyperthermia above 38.5 °C or by using a Cox’s regression model with cause-specific hypothermia under 36.5 °C, (3) purulent tracheal secre- hazard for MV duration (considering as event of inter- tions. Microbiological confirmation was required to con- est extubation alive and death under MV as compet- firm the diagnosis, with at least ­105 colony-forming units ing event) and for length of ICU stay (considering as (CFUs) per mL for endotracheal aspirates or 1 ­ 04 CFU per event of interest ICU discharge alive, and death in ICU mL for bronchoalveolar lavage. VAP episodes were pro- as competing event) [22]. Since there was no deviation spectively recorded and confirmed by two distinct physi- on proportionality assumption, the corticosteroid effect cians as well as the chest X-rays readings. Only first VAP was only modeled as a time-varying covariate without episodes were taken into account. time-dependent coefficients. The secondary objective was to determine the impact In addition, we investigated the effect of the occur- of adjuvant corticosteroid treatment on 28-day mortality, rence of VAP on the association between corticosteroid MV duration and ICU length of stay. use and these outcomes by including in the models the VAP covariate and the corticosteroids x VAP interac- tion (both treated as time-varying covariates). Statistical analysis All associations were further investigated after adjust- Categorical variables are reported as absolute num- ment for pre-specified confounders already known to ber and percentage, whereas continuous variables are be associated with VAP and patients’ outcomes (age, expressed as median with interquartile range (25th–75th gender, BMI, SAPS II, MacCabe classification, immuno- percentile). Patient characteristics at ICU admission and suppression, recent hospitalization, recent antibiotics, during ICU stay were described according to the use or shock, ARDS and cardiac arrest). To avoid case-dele- not of corticosteroids without statistical comparisons. tion in multivariate analyses due to presence of miss- The 28-day cumulative incidence of VAP, extubation alive ing data in covariates, multivariable Cox’s models were and ICU discharge alive were estimated using the Kalb- performed after handling missing data by using a multi- fleisch and Prentice method [21], considering extubation ple imputation procedure [23]. Specifically, imputation within 28-day (dead or alive), death under MV, or death of missing values was performed using a regression- during ICU as a competing events. The 28-day cumula- switching approach (chained equations with m = 20 tive incidence of all-cause mortality was estimated using obtained) under the “missing at random” assumption, the Kaplan–Meier method. using all baseline characteristics (see Table 1) and out- The association between corticosteroids and VAP comes, with a predictive mean matching method for was assessed using Cox regression with cause-specific quantitative variables and a logistic regression model hazard function considering initiation of corticosteroid (binary, ordinal or multinomial) for categorical vari- treatment as a time-varying covariate. In this model, ables. Estimates obtained in the different imputed data extubation within 28 days (dead or alive) without VAP sets were combined using Rubin’s rules [24]. Sensitiv- was considered as a competing event. The corticos- ity analysis on complete cases (patients without missing teroid time-varying variable was coded 0 during the data on covariates) was also performed. period before the start of the treatment and 1 from Statistical testing was performed with a two-tailed α the day of initiation of corticosteroids until the occur- level of 0.05. Data were analyzed using the SAS soft- rence of VAP or MV withdrawal or death within the ware package, release 9.4 (SAS Institute, Cary, NC). 28-day period of follow-up. The cause-specific hazard Statistical analysis is fully detailed in the online data ratios (cHR) for corticosteroid vs. non-corticosteroid supplement. Saura et al. Critical Care (2022) 26:292 Page 4 of 11 Table 1 Patient characteristics at ICU admission No corticosteroids (n = 354) Corticosteroids (n = 191) Age, years 64 (53–72) 65 (57–72) Men 256 (72.3) 134 (70.2) BMI (Kg/m)* 28.4 (25.4–33.0) 29.6 (26.9–34.3) Severity scores SAPS II† 41 (32–54) 43 (33–60) SOFA Score‡ 6 (3–8) 7 (3–9) Comorbidity scores MacCabe classification   Non-fatal 296/336 (88.1) 157/186 (85.3)   Fatal < 5 years 36/336 (10.7) 25/186 (13.6)   Fatal < 1 year 4/336 (1.2) 2/186 (1.1) Charlson comorbidity ­index§ 3 (1–4) 3 (2–4) Chronic diseases Diabetes mellitus 109/353 (30.9) 52/189 (27.5) Chronic renal failure 17/349 (4.9) 15/187 (8.0) Heart disease 70/351 (19.9) 30/187 (16.0) Chronic heart failure 13/350 (3.7) 8/186 (4.3) COPD 19/350 (5.4) 18/188 (9.6) Chronic respiratory failure 15/350 (4.3) 5/186 (2.7) Cirrhosis 4/350 (1.1) 4/187 (2.1) Immunosuppression 25/350 (7.1) 27/187 (14.4) Active smoking 17/350 (4.9) 11/188 (5.9) Alcohol abuse 23/349 (6.6) 10/187 (5.3) Location before ICU admission Home 163/354 (46.0) 95/191 (49.7) Hospital ward 136/354 (38.4) 70/191 (36.6) Another ICU 55/354 (15.5) 26/191 (13.6) Recent hospitalization (< 3 months) 24/354 (6.8) 18/189 (9.5) Recent antibiotics (< 3 months) 45/354 (12.7) 26/190 (13.7) Causes for ICU admission Shock 63/348 (18.1) 39/187 (20.9) Acute respiratory failure 327/354 (92.4) 172/190 (90.5) ARDS 244/352 (69.3) 125/188 (66.5) Neurological failure 14/344 (4.1) 12/182 (6.6) Cardiac arrest 2/343 (0.6) 1/182 (0.5) Acute renal failure 58/344(16.9) 37/182 (20.3) Values are as no./No.(%) or median (interquartile range). * 31 missing values (n = 10 in corticosteroid group); † 42 missing values (n = 17 in corticosteroid group); ‡ 21 missing values (n = 8 in corticosteroid group); § 19 missing values (n = 8 in corticosteroid group) 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; Immunosuppression if hematological malignancy, allogeneic stem cell transplant, solid cancer, organ transplant, HIV or immunosuppressive drugs; 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 Results Patient characteristics at ICU admission From March 2020 through May 2020, 568 patients At ICU admission, the majority of patients were men receiving IMV > 48 h for SARS-CoV-2 pneumonia were with a median age of 64 year-old in corticosteroid and eligible for this study. Twenty-three patients (4%) were no-corticosteroid groups. Body mass index (BMI), SAPS excluded due to missing data. Among the 545 included II and SOFA scores, recent hospitalization (< 3 months) patients, 191 (35%) received corticosteroids (Fig. 1). and recent antibiotic use (< 3 months) were comparable Saura et al. Critical Care (2022) 26:292 Page 5 of 11 Fig. 1 Study flowchart between both groups. In the corticosteroid group, the Table 2 Patient characteristics during ICU stay percentage of patients with immunosuppression was No Corticosteroids (n = 191) higher than in patients who did not receive corticoster- corticosteroids oids. The main causes for ICU admission were acute res- (n = 354) piratory failure and ARDS in both groups (Table 1). Corticosteroids Hydrocortisone – 52/187 (27.8) Patient characteristics during ICU stay Dexamethasone – 46/187 (24.6) Patient characteristics during ICU stay are presented Methylprednisolone – 90/187 (48.1) in Table 2. Over 90% of patients in both groups had Highest daily dose, mg – 100 (50–133) an antibiotic treatment during their ICU stay with a Exposure period, days – 6 (3–8) slightly longer duration of treatment in the corticos- Antibiotic treatment 308/328 (93.9) 177/182 (97.3) teroid group. Prone positioning was more frequent in Duration, days 12 (7–18) 14 (9–20) patients who received corticosteroids than in those Prone positioning 228/353 (64.6) 143/191 (74.9) who did not. ECMO use was comparable in the two ECMO 39/354 (11.0) 22/190 (11.6) groups. 28-day mortality was higher in patients who 28-day outcomes received corticosteroids than in those who did not. MV duration, days 14 (8–22) 17 (10–25) Duration of MV and ICU length of stay were longer in 28-day mortality 93/354 (26.3) 70/191 (36.6) the corticosteroid group than in the no-corticosteroid ICU length of stay, days 17 (11–27) 20 (13–28) group. Values are as no./No.(%) or median (interquartile range) In the corticosteroid group, patients mainly Highest daily dose of corticosteroids is reported as prednisone equivalent. received methylprednisolone (48.1%) for a median Exposure period is defined from the day of initiation of corticosteroids until the time of 6 days (3–8 days) before occurrence of VAP. occurrence of VAP or MV withdrawal or death within the 28-day of follow-up ECMO extracorporeal membrane oxygenation, ICU intensive care unit, MV mechanical ventilation Saura et al. Critical Care (2022) 26:292 Page 6 of 11 The highest daily dose of prednisone equivalent was 8 (11%) in the corticosteroids group. A higher percent- 100 mg (50–133 mg). age of patients received antibiotic treatment at the day of VAP in the corticosteroid group versus no-corticosteroid group (Table 4). Incidence of VAP and corticosteroid use Gram-negative bacilli were the main bacteria respon- In the corticosteroid group, 74 (38.7%) patients developed sible for VAP in the 2 groups (60%). Pseudomonas aer- at least one episode of VAP versus 138 (38.9%) patients uginosa, Enterobacter spp. and Escherichia coli were the in the no-corticosteroid group. As shown in Additional most frequently identified bacteria. A Higher proportion file 1: e-Fig. 1, the proportional hazard assumption for of VAP due to multidrug-resistant bacteria (MDR) was the effect of corticosteroids on the incidence of VAP, found in the corticosteroid-treated group (Table 5). assessed by the scaled Schoenfeld residuals, revealed a time tendency indicating that this effect varied during Impact of corticosteroid use on patient outcomes ICU stay. By modeling the effect of corticosteroids with Twenty-eight-day mortality was significantly associated time-dependent coefficients, the association of corticos- with corticosteroid exposure in unadjusted analysis and teroids with incidence of VAP was not significant before after adjusting for pre-specified confounders in complete and after pre-specified adjustment (Table 3), with time- case analysis, and after multiple imputation analysis. dependent adjusted hazard ratios (95% confidence inter- In adjusted analysis, corticosteroid use was associated val) of 0.47 (0.17–1.31) at day 2, 0.95 (0.63–1.42) at day with prolonged duration of MV after multiple imputa- 7, 1.48 (1.01–2.16) at day 14 and 1.94 (1.09–3.46) at day tion analysis, but not with ICU length of stay (Table 3). 21. Similar results were found in sensitivity complete Associations between different corticosteroids and VAP, case analysis. Additional file 1: e-Table 1 depicts the asso- 28-day mortality, MV duration and ICU length of stay are ciation of different corticosteroids with VAP in all study presented in e-Table 1 patients. VAP occurrence did not significantly modify the rela- tionship between corticosteroids and mortality, duration Patient characteristics at the day of VAP of MV, or length of ICU stay (Table 6). However, a sig- and microbiological data nificant association was found between corticosteroids VAP episodes were mainly diagnosed with endotracheal exposure and ICU mortality in the absence of exposure aspirates in both groups. SOFA score, modified CPIS and to VAP. Twenty-eight-day cumulative incidence of VAP, PaO2/FiO2 ratio did not differ at the day of VAP between all-cause mortality, extubation alive and ICU discharge the two groups. Thirty-five (25%) patients had at least one alive are presented in Additional file 1: e-Fig. 2. VAP recurrence in the no-corticosteroids group versus Table 3 Association between corticosteroid treatment use and outcomes in all study patients Unadjusted analysis Adjusted ­analysisb Multiple imputation ­analysisc Complete case-analysis cHR (95%CI) P Value cHR (95%CI) P Value cHR (95%CI) P Value VAP Overall effect 0.13a 0.082a 0.056a At day 2 0.43 (0.15–1.17) 0.47 (0.17–1.31) 0.43 (0.14–1.24) At day 7 0.86 (0.58–1.28) 0.95 (0.63–1.42) 0.95 (0.63–1.44) At day 14 1.34 (0.92–1.94) 1.48 (1.01–2.16) 1.59 (1.05–2.38) At day 21 1.75 (0.99–3.08) 1.94 (1.09–3.46) 2.16 (1.16–4.02) 28-day mortality 2.01 (1.46–2.75) < 0.0001 1.67 (1.20–2.33) 0.002 1.47 (1.02–2.10) 0.034 MV duration 1.14 (0.89–1.45) 0.30 1.25 (1.01–1.54) 0.036 1.18 (0.88–1.56) 0.25 Length of ICU stay 0.71 (0.54–0.95) 0.017 1.00 (0.80–1.24) 0.99 0.77 (0.56–1.07) 0.12 ARDS acute respiratory distress syndrome, BMI body mass index, cHR cause-specific hazard ratio, CI confidence interval, ICU intensive care unit, SAPS II Simplified Acute Physiology Score II, VAP ventilator-associated pneumonia a P Value for the effect of corticosteroids assessed by including corticosteroids and time*corticosteroids terms into Cox’s regression model to account the violation of proportional hazard assumption b Adjusted for age, sex, BMI, SAPS II, MacCabe classification, immunosuppression, recent hospitalization, recent antibiotics, shock, ARDS, cardiac arrest (cafter handling missing values by multiple imputation (m = 20) Saura et al. Critical Care (2022) 26:292 Page 7 of 11 Table 4 Description of patients at the day of VAP diagnosis Table 5 Microorganisms responsible for VAP No Corticosteroids (n = 74) No corticosteroids Corticosteroids corticosteroids (n = 138) (n = 74) (n = 138) Gram-positive cocci 22 (15.9) 13 (17.6) Total number of VAP MSSA 12 (8.8) 7 (9.5) 1 103/138 (74.6) 66/74 (89.2) MRSA 5 (3.6) 0 (0.0) 2 29/138 (21.0) 6/74 (8.1) Enterococcus spp. 3 (2.2) 4 (5.4) 3 5/138 (3.6) 1/74 (1.4) Streptococcus pneumoniae 2 (1.5) 2 (2.7) 4 1/138 (0.7) 1/74 (1.4) Gram-negative bacilli 83 (60) 44 (59.5) 5 0/138 (0.0) 1/74 (1.4) Pseudomonas aeruginosa 24 (17.5) 17 (23) SOFA ­scorea 8 (5–11) 8 (5–11) Enterobacter spp. 20 (14.6) 14 (18.9) Diagnostic procedure Klebsiella pneumoniae 6 (4.4) 5 (6.8) Endotracheal aspirates 83/137 (60.6) 47/73 (64.4) Escherichia coli 12 (8.8) 2 (2.7) Bronchoalveolar lavage 54/137 (39.4) 26/73 (35.6) Acinetobacter baumannii 9 (6.6) 2 (2.7) Modified ­CPISa 6 (5–7) 6 (4–7) Stenotrophomonas malt- 2 (1.5) 0 (0.0) PaO2/FiO2b 130 (91–180) 139 (95–188) ophilia Antibiotic treatment 122/138 (88.4) 71/74 (95.9) Serratia marcescens 2 (1.5) 2 (2.7) Appropriate antibiotic 94/133 (70.7) 48/73 (65.8) Citrobacter freundii 4 (2.9) 0 (0.0) treatment Proteus mirabilis 1 (0.7) 1 (1.4) Values are as no./No.(%) or median (interquartile range) Haemophilus influenza 2 (1.5) 0 (0.0) VAP ventilator-associated pneumonia, SOFA Sequential Organ Failure Morganella morganii 1 (0.7) 1 (1.4) Assessment, CPIS clinical pulmonary infection score a Other* 17 (12.3) 9 (12.1) 8 missing values (1 in corticosteroids group) b Polymicrobial 15 (10.9) 8 (10.8) 13 missing values (3 in corticosteroids group) Multidrug-resistant isolates 26 (19.0) 21 (28.4) VAP Ventilator-associated pneumonia Values are as no. (%) Discussion Missing values n = 1 (in the no-corticosteroid group) In this ancillary study of the coVAPid study, we found no MRSA, methicillin-resistant Staphylococcus aureus; MSSA, methicillin-sensitive significant association between adjuvant corticosteroid Staphylococcus aureus treatment and the incidence of VAP in a population of * Contains other Streptococcus Spp., other Klebsiella Spp., other Citrobacter Spp. SARS-CoV-2 patients invasively ventilated for over 48 h. and other bacteria However, we found a time-varying effect of corticoster- oid adjuvant therapy on the incidence of VAP over the association between VAP and mortality in this popula- 28-day period. tion [25, 26]. To date, there is no prospective interven- The incidence of VAP in the SARS-CoV-2 population tional study that evaluated the impact of corticosteroid was high, nearly half of the patients presenting at least use on the incidence of VAP, as the RECOVERY study one VAP episode during ICU stay, irrespective of corti- itself did not include it as an outcome. However, there costeroid use. This result is in line with several previous is a growing body of evidence in the literature pointing studies that reported high incidence of VAP in critically out the increased risk of developing VAP in COVID-19 ill COVID-19 patients [3, 8–10, 17]. patients treated with corticosteroids [16–19, 27, 28]. Following the RECOVERY trial, corticosteroid adju- A recent study by Mesland et al. [17]. reported, among vant use dramatically increased in critically ill COVID- 322 COVID-19 patients invasively ventilated, a signifi- 19 patients, although only 15% patients were invasively cantly higher incidence for VA-LRTI in patients receiv- ventilated in this trial. In invasively ventilated COVID- ing corticosteroid adjuvant therapy compared with those 19 patients, high rates of ARDS, prolonged ICU stay and who did not. Corticosteroids were found to be an inde- IMV duration along with immunologic disorders and pendent factor associated with VA-LRTI in a multivari- neuromuscular blocking agent use expose these patients able adjusted analysis. Another recent study found the to higher risk of developing VAP and one could question same association between corticosteroid use and VA- the impact of wide use of corticosteroids on the incidence LRTI [18]. However, other studies suggested no associa- of hospital-acquired infections (HAI) and VAP in this tion between corticosteroid exposure and the incidence population, already at higher risk for these infections. of VA-LRTI in COVID-19 [15, 29]. In COVID-19 patients, VAP is a serious complica- In our study, we did not find a significant association tion, as our group and others demonstrated a significant between corticosteroid exposure and VAP incidence Saura et al. Critical Care (2022) 26:292 Page 8 of 11 Table 6 Association between corticosteroid use and mortality, MV duration and ICU length of stay according to VAP Unadjusted analysis Adjusted ­analysisa Multiple imputation ­analysisb Complete case-analysis cHR (95%CI) P Value P Het cHR (95%CI) P Value P Het cHR (95%CI) P Value P Het All-cause 28-day mortality No VAP 2.36 (1.60–3.46) < 0.0001 0.18 1.95 (1.31–2.90) 0.001 0.15 1.61 (1.03–2.51) 0.034 0.44 VAP 1.50 (0.87–2.59) 0.14 1.18 (0.66–2.10) 0.56 1.21 (0.67–2.17) 0.51 MV duration No VAP 1.20 (0.90–1.61) 0.27 0.40 1.29 (0.96–1.73) 0.086 0.19 1.46 (1.03–2.05) 0.03 0.050 VAP 0.96 (0.62–1.50) 0.68 0.90 (0.57–1.42) 0.66 0.81 (0.49–1.31) 0.39 Length of ICU stay No VAP 0.68 (0.48–0.96) 0.027 0.82 0.76 (0.53–1.07) 0.11 0.78 0.84 (0.56–1.26) 0.40 0.46 VAP 0.73 (0.44–1.19) 0.21 0.69 (0.42–1.14) 0.15 0.65 (0.38–1.12) 0.12 ARDS acute respiratory distress syndrome, BMI body mass index, cHR cause-specific hazard ratio, CI confidence interval, ICU intensive care unit SAPS II Simplified Acute Physiology Score II, VAP ventilator-associated pneumonia a Adjusted for age, gender, BMI, SAPS II, McCabe classification, immunosuppression, recent hospitalization, recent antibiotics, shock, ARDS, cardiac arrest b After handling missing values by multiple imputation (m = 20) P Het: P Value for the heterogeneity test of effects according to occurrence of VAP during the 28-day period of follow-up. However, our corticosteroid-treated patients. Several other observa- results suggest a trend toward a time-varying effect of tional studies also failed to demonstrate this benefit from corticosteroid exposure on the incidence of VAP. This corticosteroids [17, 36]. time-varying effect increased all along the 28-day follow- Microorganisms responsible for VAP in our study did up, and the association between corticosteroid use and not differ between the corticosteroid treated and non- VAP became statistically significant after the 14th day treated patients. In line with previous results, Gram-neg- of mechanical ventilation. Several explanations could be ative bacilli were the main bacteria found in respiratory provided for this time-varying effect. First, corticoster- tract samples with a high rate of Enterobacteriaceae and oid-immunosuppressive effect is a time-dependent but Pseudomonas aeruginosa. Methicillin-sensitive Staphylo- also a cumulative-dose-dependent mechanism [30] that coccus aureus was the main Gram-positive cocci, and the may explain the late occurrence of hospital-acquired rate of multidrug-resistant bacteria was also high [3, 15, infections in treated patients. Second, sepsis-associated 17]. immunosuppression is a time-dependent process occur- To our knowledge, our study is the largest multicenter ring in the late course of ICU stay, resulting in immu- study to examine the impact of corticosteroid adjuvant noparalysis and ICU-acquired infection [31, 32]. Finally, therapy on the incidence of VAP in COVID-19 patients, SARS-CoV-2-mediated immune dysfunction is associ- and the first to show a varying association between cor- ated with a progressive lymphopenia [33, 34], and a mul- ticosteroid use and the incidence of VAP. Additional tifactorial immunosuppression culminating after day 14 strengths of our study are the large number of patients, [35] that exposes patients to late-onset ICU-acquired the multicenter design and the strict definition of VAP infection. with quantitative microbiological documentation for Our study reports higher 28-day mortality and longer each event. However, some limitations should be men- MV duration in the group of patients who received adju- tioned. First, the observational retrospective design of vant corticosteroid treatment, as compared to those who our study taking place before the RECOVERY era is did not. The main reason for this discrepancy with results responsible for possible selection bias with disparate of randomized controlled trials [13, 36] might be the use of corticosteroids among centers that intentionally observational design of this study taking place before the selected the sickest patients to receive corticosteroids, RECOVERY era when corticosteroid prescriptions were leading to poorer outcomes. Second, a small propor- at the discretion of attending physicians who selected tion of included patients (30%) received corticosteroids, the sickest patients to receive these treatments. Septic which could also introduce a selection bias. Third, in our shock, non-resolving ARDS and intense systemic inflam- study we collected all steroid prescriptions irrespective of mation were the main reasons for corticosteroid adjuvant variations in molecule, duration and dosage. The impact therapy, and this led de facto to a poorer prognosis in the Saura et al. Critical Care (2022) 26:292 Page 9 of 11 of this discrepancy on patient outcomes might be real, (Medical Intensive Care Unit, Cochin Hospital, Assistance Publique – Hôpitaux de Paris, Paris, France), Catia Cilloniz (Department of Pulmonology, Hospital yet no data support this in the literature. Clinic of Barcelona, University of Barcelona, IDIBAPS, CIBERES, Barcelona, Spain), Didier Thevenin (Service de réanimation polyvalente, Centre Hospi‑ talier de Lens, Lens, France), Charlotte Larrat (Service de Médecine Intensive Conclusions Réanimation CHU de Tours, Hôpital Bretonneau, 37044 Tours Cedex 9, France), We found no significant association between corticos- Laurent Argaud (Service de Médecine Intensive - Réanimation, Hôpital teroid adjuvant therapy and the incidence of VAP in the Edouard Herriot, Hospices Civils de Lyon, 69437 Lyon Cedex 03, France), Bertrand Guidet (Service de Médecine Intensive Réanimation, Hôpital Saint- population of invasively ventilated patients for a SARS- Antoine, Assistance Publique-Hôpitaux de Paris, 75012 Paris, France), Damien CoV-2 pneumonia. However, we found a time-varying Contou (Service de réanimation polyvalente, CH Victor Dupouy, Argenteuil, effect of corticosteroid adjuvant therapy on the cause- France), Alexandra Beurton (Service de Médecine Intensive-Réanimation et Pneumologie, Assistance Publique-Hôpitaux de Paris, Hôpital Pitié Salpêtrière, specific estimated risk of developing VAP throughout France), David Meguerditchian (Service de médecine intensive réanimation, patient course in ICU. Further studies are needed to clar- CHU de Bordeaux, F-33000 Bordeaux, France), Keyvan Razazi (Assistance ify the role and effects of adjuvant corticosteroid treat- Publique-Hôpitaux de Paris, Hôpitaux Universitaires Henri-Mondor, Service de Médecine Intensive Réanimation; Université Paris Est Créteil, CARMAS; INSERM ment in the sickest COVID-19 patients. Future research U955, Institut Mondor de recherche Biomédicale; F-94010 Créteil, France), should also investigate the interest of a corticosteroid-use Vassiliki Tsolaki (Intensive Care Unit, University Hospital of Larissa, University of strategy based on patient inflammatory phenotypes. Thessaly, Biopolis Larissa, 41110 Greece), Mehdi Marzouk (Intensive Care Unit, Hôpital de Béthune, 62408 Béthune, France), Guillaume Brunin (Service de réanimation, Hôpital Duchenne, 62200 Boulogne-sur-Mer, France), Clémence Marois (Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Sorbonne Abbreviations Université Hôpital de la Pitié-Salpêtrière, Département de Neurologie, Unité ARDS: Acute respiratory distress syndrome; BMI: Body mass index; BSI: de Médecine Intensive Réanimation Neurologique, Paris, France), Luis Morales Bloodstream infection; CFU: Colony-forming unit; CPIS: Clinical pulmonary (Intensive Care Unit, Hospital Unive rsitari Sagrat Cor, Barcelona, Spain) infection score; COVID-19: Coronavirus disease 2019; ECMO: Extra corporeal membrane oxygenation; HAI: Hospital-acquired infection; ICU: Intensive care Author contributions unit; IMV: Invasive mechanical ventilation; PCR: Polymerase chain reaction; OS, AR, IML, PP, AD, JL and SN contributed to conception and design of the SAPS II: Simplified Acute Physiology Score II; SARS-CoV-2: Severe acute respira‑ study. All authors were involved in data acquisition. OS, AR, IML, PP, AT, LK, AD, tory syndrome coronavirus 2019; SOFA: Sequential Organ Failure Assessment; JL and SN contributed to data analysis and interpretation. All authors were VA-LRTI: Ventilator-associated lower respiratory tract infection; VAP: Ventilator- involved in manuscript drafting or critical revision for important intellectual associated pneumonia; VAT: Ventilator-associated tracheobronchitis. content. All authors contributed to final approval of the submitted version. SN was guarantor of the paper. Supplementary Information Funding The online version contains supplementary material available at https://​doi.​ This study was supported in part by a grant from the French government org/​10.​1186/​s13054-​022-​04170-2. through the « Programme Investissement d’Avenir» (I-SITE ULNE) managed by the Agence Nationale de la Recherche (coVAPid project). Prof. Ignacio Additional file 1. Supplementary e-figures and e-tables. Martin-Loeches has been supported by SFI (Science Foundation Ireland), Grant number 20/COV/0038. The funders of the study had no role in the study design, data collection, analysis or interpretation, writing of the report or deci‑ Acknowledgments sion to submit for publication. coVAPid Study Group Availability of data and materials Mathilde Bouchereau (CHU de Lille, Centre de Réanimation, F-59000 Lille, All data needed to evaluate the conclusions in this article are present and France), Sean Boyd (Department of Intensive Care Medicine, Multidisciplinary tabulated in the main text or the appendix. This article is the result of an origi‑ Intensive Care Research Organization (MICRO), St.’James’s Hospital, Dublin, nal retrospective cohort. For individual de-identified raw data that underlie Ireland), Luis Coelho (Polyvalent Intensive Care Unit, Hospital de São Francisco the results reported in this article, please contact the corresponding authors. Xavier, CHLO, Lisbon, Portugal and NOVA Medical School, CHRC, New Univer‑ sity of Lisbon, Portugal), Julien Maizel (Service de médecine intensive réanima‑ tion, CHU Amiens Picardie, 80000 Amiens, France), Pierre Cuchet (Department Declarations of Medical Intensive Care, Caen University Hospital, F-14000 Caen, France), Wafa Zarrougui (Service de réanimation polyvalente, Centre hospitalier de Ethics approval and consent to participate Valenciennes, Valenciennes, France), Déborah Boyer (Medical Intensive Care The Ethics Committee and Institutional Review Boards approved the study Unit, Rouen University Hospital, 76000 Rouen, France), Jean-Pierre Quenot protocol (Comité de Protection des Personnes Ouest VI; approved by April 14, (Department of Intensive Care, François Mitterrand University Hospital, Dijon, 2020; registration number RIPH:20.04.09.60039) as minimal-risk research using France), Mehdi Imouloudene (Service de réanimation et de soins intensifs, data collected for routine clinical practice and waived the requirement for Centre hospitalier de Douai, France), Marc Pineton de Chambrun (Service de informed consent. Médecine Intensive Réanimation, Institut de Cardiologie, Groupe Hospitalier Pitié-Salpêtrière, Assistance Publique – Hôpitaux de Paris Cedex 13, France), Competing interests Thierry Van der Linden (Service de médecine intensive réanimation, Hôpital AR received personal fees from Maat Pharma, and IML received personal fees Saint Philibert GHICL, université catholique, Lille, France), François Arrive (CHU from MSD and Gilead. AA received personal fees from Lilly Foundation and de Poitiers, Médecine Intensive Réanimation, CIC 1402 ALIVE France université grants from Grifols and Fisher & Paykel. CEL received personal fees from Bayer, de Poitiers, Poitiers, France), Sebastian Voicu (Department of Medical and Merck, Aerogen, bioMérieux, ThermoFisher Brahms and Carmat. SN received Toxicological Critical Care, Lariboisière Hospital, INSERM UMRS-1144, Paris personal fees from MSD, Bio Rad, bioMérieux, Gilead, Fisher & Paykel and Pfizer. University, Paris, France), Elie Azoulay (Service de médecine intensive réanima‑ All other authors declare no competing interests. tion, Hôpital Saint-Louis, 75010 Paris, France), Edgard Moglia (Critical Care Department, Hospital Universitari Parc Taulí, Sabadell, Spain), Frédéric Pene Consent for publication Not applicable. Saura et al. Critical Care (2022) 26:292 Page 10 of 11 49 Author details Univ. Lille, ULR 2694-METRICS: Evaluation des Technologies de Santé et des 1 Médecine Intensive-Réanimation, CHU de Lille, 59000 Lille, France. 2 INSERM Pratiques Médicales, 59000 Lille, France. 50 Biostatistics Department, CHU de U1285, Université de Lille, CNRS, UMR 8576 – UGSF – Unité de Glycobiologie Lille, 59000 Lille, France. Structurale et Fonctionnelle, 59000 Lille, France. 3 Department of Intensive Care Medicine, Multidisciplinary Intensive Care Research Organization (MICRO), St. Received: 13 July 2022 Accepted: 12 September 2022 James’s Hospital, Dublin, Ireland. 4 Department of Clinical Medicine, School of Medicine, Trinity College Dublin, Dublin, Ireland. 5 Hospital Clinic, IDIBAPS, Universidad de Barcelona, Ciberes, Barcelona, Spain. 6 Polyvalent Intensive Care Unit, Hospital de São Francisco Xavier, CHLO, Lisbon, Portugal. 7 NOVA Medical School, CHRC, New University of Lisbon, Lisbon, Portugal. 8 Center for Clini‑ References cal Epidemiology and Research Unit of Clinical Epidemiology, OUH Odense 1. Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, et al. 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