PEEP-AKI-COVID ICU: Effect of Positive End-Expiratory Pressure on Acute Kidney Injury Development in Patients with COVID-19-Associated Acute Respiratory Distress Syndrome: An Ancillary Analysis of the COVID-ICU Study

PEEP-AKI-COVID ICU: Effect of Positive End-Expiratory Pressure on Acute Kidney Injury Development in Patients with COVID-19-Associated Acute Respiratory Distress Syndrome: An Ancillary Analysis of the COVID-ICU Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article PEEP-AKI-COVID ICU: Effect of Positive End-Expiratory Pressure on Acute Kidney Injury Development in Patients with COVID-19-Associated Acute Respiratory Distress Syndrome: An Ancillary Analysis of the COVID-ICU Study Léo Poirot, Lionel Tchatat Wangueu, Isaure Breteau, Matthieu Petit, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6880811/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Background Acute Kidney Injury (AKI) is common in patients admitted to intensive care unit (ICU) for severe SARS-CoV-2 pneumonia and is associated with a worse prognosis. Mechanical ventilation has been identified as a risk factor for renal damage in COVID-19. However, few studies have examined the specific ventilatory settings involved. We hypothesized that positive end-expiratory pressure (PEEP) may contribute to the onset of AKI. Our objective was to assess the association between higher PEEP levels and the occurrence of AKI. Methods We conducted an ancillary analysis of the international, prospective, multicenter COVID-ICU study, which included 4244 COVID-19 ICU patients across 149 intensive care units. For our study, only patients who underwent mechanical ventilation for at least 48 hours and had normal renal function before intubation were included. AKI was defined according to Kidney Disease Improving Global Outcome (KDIGO) criteria. A multivariate logistic regression model was used to evaluate the association between PEEP levels and the development of AKI. Results A total of 1,066 patients were included in the analysis. Among them, 510 (48%) developed AKI within five days of intubation. Mortality at 28 days was higher in patients with AKI (28% vs. 18%, p < 0.001) compared to those without. After adjusting for confounding factors, higher PEEP levels during the first three days of mechanical ventilation were independently associated with AKI (odds ratio [OR] 1.09; 95% confidence interval [95% CI 1.04–1.15]). A PEEP level exceeding 15 cmH₂O was strongly linked to an increased risk of AKI (OR 2.77; 95% CI [1.31–6.24]). Additionally, vasopressor use and elevated lactate levels were associated with renal impairment. AKI was significantly related to 28-day mortality, whereas PEEP levels were not. Conclusion Within five days of intubation in COVID-19 ARDS patients, higher PEEP levels were independently associated with an increased risk of AKI. While AKI was linked to higher mortality, PEEP level was not. acute kidney injury positive end-expiratory pressure mechanical ventilation COVID-19 acute respiratory distress syndrome Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Coronavirus disease 2019 (COVID-19) has significantly impacted ICU worldwide between 2020 and 2021, particularly through its severe form, which leads to acute respiratory distress syndrome (ARDS) 1 . It is now established that AKI is the most common organ failure associated with ARDS affecting 30 to 40% of patients 2,3 and more than 50% in the case of COVID-19 4 . The onset of renal dysfunction is a known risk factor for mortality in ARDS, whether linked to SARS-CoV-2 5 or not 2,3 . Moreover, AKI is linked to greater morbidity, as it prolongs the duration of mechanical ventilation 3 , extends ICU and hospital stays, and increases the risk of chronic kidney disease and end-stage renal disease 7,8 . However, the pathophysiology of renal damage in ARDS remains largely unknown 4 . Indeed, there are substantial gaps in our understanding of the heart-lung-kidney interactions, which are likely involved in this dual organ failure 9–11 . Several studies have identified mechanical ventilation as an independent risk factor for AKI in ARDS 2,12 , particularly in COVID-19 cases 13–15 . Hemodynamic changes, disruption of gas exchange, and systemic inflammation caused by this mechanical ventilation may explain the heightened risk of AKI in these patients 16 . However, the impact of specific ventilator settings on renal function has been insufficiently studied to date 10 . Specifically, PEEP may play a role in the development of renal dysfunction. Previous studies by Husain et al. 9 and Gabarre et al. 4 have suggested that PEEP, by increasing intrathoracic pressure, reduces preload and cardiac output 17 , potentially lowering renal blood flow (RBF). Furthermore, PEEP increases transpulmonary pressure, which can cause pulmonary capillary collapse in cases of alveolar overdistension. This leads to increased pulmonary vascular resistance, pulmonary arterial hypertension, and elevated right ventricular afterload 17–21 . Venous congestion and right ventricular dysfunction, which may result from these changes, are well-known causes of AKI due to reduced renal perfusion pressure 22–24 . Additionally, PEEP may disrupt renal physiology through neurohormonal changes 25,26 and the release of systemic inflammatory mediators 27,28 . Following international guidelines 29 and by analogy with non-COVID-19 ARDS 30 , PEEP is generally set at a high level in severe SARS-CoV-2 pneumonia. However, ARDS in COVID-19 patients appear to exhibit distinct characteristics compared to other causes of ARDS 31,32 , potentially amplifying the adverse effects of high PEEP 33 . Four observational clinical studies in COVID-19 patients have examined the relationship between PEEP and renal function. These studies, though valuable, involved small sample sizes, produced conflicting results, and lacked sufficient statistical power 34–37 . We hypothesized that higher PEEP levels may have a deleterious effect on renal function. The primary aim of this study was to determine whether PEEP levels influence the occurrence of AKI in COVID-19 patients. Secondary objectives included identifying other factors contributing to AKI and evaluating the impact of renal failure on mortality in COVID-19 patients. Methods Study design, data source and patients This study is an ancillary analysis of the COVID-ICU cohort 38 conducted between February 25, 2020 and May 4, 2020 during the first wave of the COVID-19 pandemic. The COVID-ICU cohort is a multicenter, prospective study conducted across 149 intensive care units (ICUs) in 138 hospitals across 3 countries (France, Switzerland and Belgium). It includes 4,244 patients aged over 16 years hospitalised in ICU with a positive laboratory-confirmed SARS-CoV-2 infection. In this analysis, Day 1 was defined as the first day of mechanical ventilation for each patient. Only those requiring invasive mechanical ventilation for at least 48 hours were included. Exclusion criteria comprised: patients who had received RRT or extracorporeal membrane oxygenation (ECMO) on Day 1 or earlier; those without daily PEEP values during the first three days of mechanical ventilation; patients mechanically ventilated for more than 24 hours before ICU admission; those without creatinine data on Day 1; patients with chronic kidney disease; and those with renal dysfunction as indicated by the Sequential Organ Failure Assessment (SOFA) score on Day 1. Case definition Renal function was assessed using the KDIGO classification 39 based solely on biological and RRT criteria, as daily urine output and prior creatinine values were not collected. Baseline creatinine was estimated, in accordance with guidelines 39 , by back-calculation 40 of the Modification of Diet in Renal Disease (MDRD) formula, assuming a baseline glomerular filtration rate (GFR) of 75 ml/min/1.73 m² for patients without chronic kidney disease (CKD). The maximum creatinine value and/or the use of RRT between Day 2 and Day 6 were used to classify patients into two groups, using the KDIGO criteria for AKI: those who developed AKI within 5 days of intubation, and those who retained normal renal function. Patients who died before day 6 and who did not meet the KDIGO criteria for AKI were classified as not having AKI. The severity of renal dysfunction was further categorized according to the KDIGO stages. The severity of ARDS was assessed using the PaO 2 /FiO 2 ratio and the Berlin criteria 1 . Ventilator-free days were calculated by taking into account the date of intubation and the date of successful extubation, excluding periods of temporary weaning. In the case of death within 28 days, the patient was considered to have no ventilator-free days. Data Collection All data were recorded daily at 10 a.m. by the study investigators using a standardized electronic form. Patient characteristics collected at ICU admission included age, sex, ethnicity, body mass index (BMI), active smoking status, Simplified Acute Physiology Score II (SAPS II), Sequential Organ Failure Assessment (SOFA) score, bacterial co-infection, and comorbidities, including chronic kidney disease. Ventilator settings (FiO 2 , tidal volume, total PEEP, plateau pressure, and PaO 2 /FiO 2 ratio); respiratory biomarkers (arterial blood gases, lactate levels); hemodynamic parameters (number of days on vasopressors, presence of right ventricular dysfunction) and rescue therapies (number of days in prone positioning and on inhaled nitric oxide) were collected and averaged over the first 72 hours. Prognostic data included ARDS severity on Day 1, renal function and/or use of renal replacement therapy within the first five days, 28-day mortality, ventilator-free days, and ICU length of stay. For each clinical or biological parameter, the worst value from the preceding 24 hours was recorded. Ethical approval The ethics committees of Switzerland (BASEC #: 2020-00704), the French Intensive Care Society (CE-SRLF 20-23), and Belgium (2020-294) approved the data collection protocol. Written informed consent was obtained from all participants before their inclusion in the study. Statistical Analysis Continuous variables are expressed as mean (standard deviation), while categorical variables are presented as numbers (percentages). Group comparisons were performed using the Student's t-test for continuous variables and the Chi-square test for categorical variables. To identify an independent association between the early PEEP level applied (average value from Day 1 to Day 3) and the development of AKI within 6 days following intubation, a logistic regression model was used. The risk factors for AKI in COVID-19 and ARDS, commonly identified in the literature 4,15,41,42 , were included in the adjusted model. Variables with p-value < 0.05 in univariate analysis were incorporated in the multivariate model. Subsequently, we sought to determine the PEEP threshold level significantly associated with the development of AKI. A second logistic regression analysis was conducted to assess whether early AKI in ICU patients was correlated with increased 28-day mortality. Adjustments were made for various mortality risk factors, as identified in the two largest cohorts from developed countries during the first wave of COVID-19 38,43 . All variables included in the models were predefined, with no additional variable selection. The goodness of fit for the logistic regression was evaluated using the Hosmer-Lemeshow test. The results of the multivariate analyses are presented as odds ratios (OR) with 95% confidence intervals (CI) and p-values. A two-tailed p-value < 0.05 was considered statistically significant. Missing data were imputed using the median in SPSS v28.0, and all analyses were performed using R v.4.3.0. Results Study Population Among 3583 patients who were mechanically ventilated for at least 48 hours, 1066 were included in our study after the application of the exclusion criteria. (Figure 1) The majority were overweight: BMI 29 ± 6; male (73%) with a mean age of 61 ± 12 years. The most common comorbidity was hypertension. (Table 1) Acute Kidney Injury: Incidence, Morbidity and Mortality Of the 1066 patients, 510 (48%) developed acute kidney injury within 5 days of intubation. Diabetes was more prevalent in the AKI group (26 vs 21% in the non-AKI group, p = 0 .032). (Table 1) The majority (61%) of AKI cases remained at KDIGO stage 1, while 19% progressed to stage 3, and 11% required RRT. Patients with AKI had higher 28-day mortality (28% vs. 18%, p < 0.001), a longer ICU stay (29 ± 18 vs. 23 ± 18 days, p < 0.001), and fewer ventilator-free days (7 ± 8 vs. 11 ± 9, p < 0.001) compared to those without AKI. (Table 2) Respiratory and Hemodynamic Parameters Compared to patients without AKI, PEEP was significantly higher in the AKI group (11.4 ± 2.7 vs 10.8 ± 2.6 cmH 2 O, p < 0.001). Static lung compliance was similar in both groups (36.4 ± 15.9 vs 36.8 ± 17.5 ml/cmH 2 O, p = 0.663) while pH was lower (7.39 ± 0.06 vs 7.40 ± 0.05, p < 0.001) and lactate was higher (1.6 ± 0.9 vs 1.4 ± 0.7 mmol/l p < 0.001) in the AKI group. From a hemodynamic perspective, patients with AKI required more days on vasopressors (1.8 ± 1.2 vs 1.6 ± 1.2 days, p < 0.029). (Table 3) Risk Factors Associated with Acute Kidney Injury After adjusting for confounding factors frequently identified or suspected in the literature (age, sex, BMI, ARDS severity as measured by the PaO 2 /FiO 2 ratio, tidal volume and cardiovascular comorbidities such as diabetes) and for factors identified in univariate analysis, PEEP was found to be statistically significantly associated with the development of AKI within 5 days of intubation (odds ratio [OR]1.09; 95% confidence interval [95% CI], 1.04-1.15). The number of days on vasopressors (OR 1.34; 95% CI, 1.01-1.77) and elevated lactate levels (OR 1.47; 95% CI, 1.19-1.87) were also significantly associated with renal impairment. (Figure 2). Subsequently, Patients with a 3-day mean PEEP strictly greater than 15 cmH 2 O (33 patients) had a significantly increased risk of developing AKI (OR 2.77; 95% CI, 1.31-6.24) (Figure 3). Analysis comparing patients with PEEP > 12 cmH 2 0 (306 patients) to the rest of the cohort did not show a significantly higher risk of AKI (OR 1.29; 95% CI, 0.98-1.70). Risk Factors Associated with Mortality at 28 days In a multivariate analysis adjusted for mortality risk factors, the level of PEEP was not associated with 28-day mortality (OR 1.01; 95% CI, 0.95-1.07). However, the occurrence of AKI within 5 days of initiating mechanical ventilation was associated with increased mortality at 28 days (OR 1.64; 95% CI, 1.21-2.24), as same as the age and the initial severity of ARDS. (Figure 4) Discussion In this ancillary study from a large international cohort of critically ill COVID-19 patients, 48% of mechanically ventilated patients developed de novo AKI within 5 days of intubation. Higher PEEP levels during the first 72 hours were independently associated with AKI onset (OR 1.09; 95% CI, 1.04-1.15), with PEEP >15 cmH₂O significantly increasing risk (OR 2.77; 95% CI, 1.31-6.24). Prolonged vasopressor use and elevated lactate levels also correlated with renal dysfunction. AKI was independently associated with higher 28-day mortality (OR 1.64; 95% CI, 1.21-2.24), but no significant link was found between PEEP levels and mortality (OR 1.00; 95% CI, 0.94-1.07). PEEP has traditionally been set at a high level in patients with ARDS. In our cohort of COVID-19-related ARDS, mean PEEP levels during the early days of mechanical ventilation were 11.4 ± 2.7 cmH 2 O, reflecting standard clinical practice. The rationale behind high PEEP settings is based on the "Baby Lung" concept, proposed by Gattinoni et al. 44 , which aims to counteract lung derecruitment induced by low tidal volume-protective ventilation 45 , reduce inflammation, atelectrauma 46 and improve oxygenation. While three major randomized trials have shown that high PEEP enhances oxygenation in ARDS patients 47–49 , none—including our study—have demonstrated a mortality benefit. This discrepancy may be due to the underexplored adverse effects of high PEEP on extrapulmonary organs. By analyzing a large cohort using logistic regression while accounting for numerous confounding factors associated with AKI in COVID-19, we demonstrated that each 1 cmH₂O increase in PEEP was associated with a 9% higher risk of acute kidney injury. Our findings reinforce and extend prior literature on COVID-19, such as a secondary analysis of a Dutch multicenter cohort involving 468 patients 37 and an Italian case-control study involving 101 patients 34 , both of which reported an association between PEEP and AKI with 1.5 to 5-fold higher AKI in the high PEEP groups, respectively. Observational studies, including before-and-after observational studies, 36,50 have also suggested a positive relationship between PEEP and renal impairment. Moreover, we identified a PEEP threshold that might elevate the risk of AKI: while the association with PEEP levels above 12 cmH 2 0 approached statistical significance (OR 1.29; 95%CI, 0.98-1.70), it was significant above 15 cmH 2 0 (OR 2.77; 95% CI, 1.31-6.24). We chose to analyze these two PEEP thresholds because, on average, the PEEP levels reported in randomized trials comparing “high” PEEP to “moderate” PEEP were 15 cmH 2 O and 9 cmH 2 O, respectively 47–49 . Therefore, 12 cmH 2 O can be considered the threshold beyond which PEEP can be classified as elevated, and 15 cmH 2 O as very high PEEP. In the context of ARDS unrelated to COVID-19, only a retrospective study involving 27,248 patients from the MIMIC-III cohort 51 has demonstrated a similar association between increased PEEP and AKI, with each 1 cmH 2 0 increase in PEEP associated with a roughly 1.2-fold increased risk of AKI. However, this result contrasts with other large-scale observational studies that failed to demonstrate this association in ARDS unrelated to COVID-19 3,41,52 . Several factors may explain this discrepancy in the literature between COVID-19 and non-COVID-19 ARDS. First, studies outside the context of COVID-19 often include a diverse range of ARDS etiologies and ARDS phenotypes 53 . Depending on the phenotype, patients respond differently to PEEP in terms of pulmonary recruitability 53–55 . The hemodynamic consequences of PEEP are inversely correlated with this recruitability 18,56 . Some patients with higher pulmonary recruitability experience little or no hemodynamic effects from PEEP. Consequently, the association between PEEP and AKI is less pronounced in studies involving heterogeneous populations. In the context of COVID-19, although different ARDS phenotypes have been described 57 , the study populations remain relatively homogeneous. Secondly, it has been noted that patients with COVID-19-related ARDS tend to have preserved pulmonary compliance 31,32 . This may amplify the hemodynamic effects of high PEEP in this population as suggested by Grasso et al. 33 potentially leading to impaired renal blood flow 58 and reduced oxygen delivery to renal tissues 59 . Again according to Grasso et Al. 33 high PEEP in the context of preserved compliance could generate greater alveolar overdistension, thus increasing the systemic release of inflammatory mediators, which also affect renal physiology 28 . However, our study did not find any significant difference in pulmonary compliance between patients with and without AKI. Furthermore, the average compliance (36.6 ml/cmH 2 0) was consistent with values observed in both non-COVID ARDS and other studies involving COVID-19-related ARDS 60,61 . From a pathophysiological standpoint, it is noteworthy that right ventricular dysfunction, a potential mechanism linking PEEP and AKI in COVID-19, was observed less frequently in our cohort (3.2%) compared to non-COVID-19-related ARDS 62 . This lower prevalence is likely attributable to the lack of systematic screening for acute cor pulmonale in our study. Our study also confirms that other clinical factors, such as the duration of vasopressor use and elevated blood lactate levels, are independent predictors of AKI. These factors reflect the overall severity of illness and have been identified as risk factors for renal impairment in other studies 3,63 . Consistent with previous reports in the literature 5,15,38,43 our analysis also underscores that AKI is a strong predictor of increased mortality in COVID-19 patients requiring mechanical ventilation. To our knowledge, this is the first study to establish an independent and temporal association between PEEP and AKI in COVID-19. We specifically observed the effect of PEEP during the first 72 hours, as most studies on the topic 47–49 . Additionally, to account for other confounding factors that might arise between the exposure period and the occurrence or non-occurrence of AKI, we limited the observation of AKI to the period between day 2 and day 6. This approach allowed us, on the one hand, to ensure a sufficient period of PEEP exposure for the potential development of AKI. On the other hand, it helped avoid incorrectly associating AKI after day 6, which is likely not physiologically related to PEEP applied between day 1 and day 3. Thus, our study introduces a critical temporal element, which is often missing in other observational studies. This finding reinforces the association, as highlighted in previous editorials 64,65 . Only Géri et al. in 2021 13 have conducted a similar analysis with comparable results, albeit with a much smaller sample of non-COVID-related ARDS. However, the positive association between PEEP and AKI must be interpreted with caution, as no significant relationship was found between PEEP levels and 28-day mortality, despite the strong association between AKI and mortality. Additionally, insufficient PEEP may lead to significant lung derecruitment and atelectasis, increasing pulmonary arterial pressure, as demonstrated in both animal models 66 and clinical studies 56 . Therefore, an individualized PEEP strategy is crucial to balance its beneficial effects on ventilation while minimizing the risk of renal impairment. Our study has several limitations that must be underlined. First, being an observational study causality cannot be conclusively established. Second, the large sample size and high clinical activity during the COVID-19 crisis led to missing data, which may have obscured additional confounding factors. Although data imputation methods were employed, these limitations should be considered. Third, the mortality rate in our cohort (23%) was lower than that reported in the original COVID-ICU study or in the large "Lung Safe" study 67 due in part to the exclusion of patients on ECMO or with pre-existing renal dysfunction to limit confounding factors. Fourth, the method of baseline creatinine imputation by the back-calculation of the MDRD formula, although validated 40 , remains controversial and may have overestimated the incidence of AKI by approximately 10% 68 . The non-use of the diuresis criterion in the KDIGO classification, although also validated 69 , may underestimate the incidence of AKI by approximately 15% 70 . A misclassification of AKI is therefore possible in our study, although the incidence appears to align with the findings reported in the existing literature on the subject 4 . Finally, only a single daily PEEP measurement was recorded at 10 am, whereas PEEP levels could fluctuate throughout the day for each patient, which could have introduced bias in the exposure assessment. Conclusion Our findings suggest that elevated levels of PEEP are independently associated with the development of AKI in patients with COVID-19-related ARDS. This highlights the need for clinicians to carefully consider the potential renal implications of high PEEP settings when managing these patients. Future prospective clinical trials are essential to confirm these findings, particularly in non-COVID-19-related ARDS, and to establish clear recommendations. Abbreviations 95% CI : 95% confidence interval AKI : Acute Kidney Injury ARDS :Acute Respiratory Distress Syndrome BMI : Body Mass Index CKD: Chronic Kidney Disease COPD : Chronic Obstructive Pulmonary Disease COVID-19 : Coronavirus disease 2019 ECMO : Extracorporeal Membrane Oxygenation GFR : Glomerular Filtration Rate ICU : Intensive Care Unit KDIGO : Kidney Disease ImprovalGlobal Outcomes MDRD : Modification of Diet in Renal Disease MV : mechanical ventilation NO: Nitric oxide OR : Odds Ratio PaCO 2 : Partial Pressure of Carbon Carbon Dioxide PaO 2 /FiO 2 : ratio between Partial Oxygen Pressure and Inspired Oxygen Fraction PEEP : Positive End-Expiratory Pressure PP: Prone Position Pplat :Plateau Pressure RBF: Renal Blood Flow RRT :Renal Replacement Therapy SOFA : sequential organ failure assessment score SAPS II : Simplified Acute Physiology Score II TIW : Theoretical Ideal Weight RV : Right Ventricle Vt : Volume tidal Declarations Ethics approval and consent to participate : The ethics committees of Switzerland (BASEC #: 2020-00704), the French Intensive Care Society (CE-SRLF 20-23) and Belgium (2020-294) approved the data collection protocol. Consent for publication : All patients or close relatives were informed that their data were included in the COVID-ICU cohort. Availability of data and material : Restrictions apply to the availability of these data and so are not publicly available. However, data are available from the authors upon reasonable request and with the permission of the institution. Competing interests : The authors declare that they have no conflict of interest. Funding: This study was funded by the Foundation AP-HP and the Direction de la Recherche Clinique et du Development and the French Ministry of Health. The REVA network received a 75 000 € research grant form Air Liquide Healthcare. The funder had no role in the design and conduct of the study, collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Authors' contributions : Florent Bavozet (FB), Lionel Tchatat-Wangueu (LTW), and Léo Poirot (LP) conceived and designed the study and were involved in drafting the manuscript. FB performed the data retrieval. LTW, Isaure Breteau (IB) performed the statistical analysis. All the authors were involved in the interpretation of the data, in drafting the manuscript, and made critical revisions to the discussion section. All authors read and approved the final version to be published. Acknowledgements : The authors are particularly grateful to all caregivers, COVID-ICU investigators and patients who have been involved in the study. References The ARDS Definition Task Force*. Acute Respiratory Distress Syndrome: The Berlin Definition. JAMA . 2012;307(23):2526–2533. doi: 10.1001/jama.2012.5669 Darmon M, Clec’h C, Adrie C, et al. Acute Respiratory Distress Syndrome and Risk of AKI among Critically Ill Patients. CJASN . 2014;9(8):1347–1353. doi: 10.2215/CJN.08300813 McNicholas BA, Rezoagli E, Pham T, et al. Impact of Early Acute Kidney Injury on Management and Outcome in Patients With Acute Respiratory Distress Syndrome: A Secondary Analysis of a Multicenter Observational Study*. Critical Care Medicine . 2019;47(9):1216–1225. doi: 10.1097/CCM.0000000000003832 Gabarre P, Dumas G, Zafrani L. Insuffisance rénale aiguë chez les patients COVID-19 en soins intensifs. Médecine Intensive Réanimation . 2021;30(Hors-série 1):43–52. doi: 10.37051/mir-00069 Alenezi FK, Almeshari MA, Mahida R, Bangash MN, Thickett DR, Patel JM. Incidence and risk factors of acute kidney injury in COVID-19 patients with and without acute respiratory distress syndrome (ARDS) during the first wave of COVID-19: a systematic review and Meta-Analysis. Renal Failure . 2021;43(1):1621–1633. doi: 10.1080/0886022X.2021.2011747 Hoste EAJ, Bagshaw SM, Bellomo R, et al. Epidemiology of acute kidney injury in critically ill patients: the multinational AKI-EPI study. Intensive Care Med . 2015;41(8):1411–1423. doi: 10.1007/s00134-015-3934-7 Coca SG, Singanamala S, Parikh CR. Chronic kidney disease after acute kidney injury: a systematic review and meta-analysis. Kidney International . 2012;81(5):442–448. doi: 10.1038/ki.2011.379 Gammelager H, Christiansen C, Johansen M, Tønnesen E, Jespersen B, Sørensen H. Five-year risk of end-stage renal disease among intensive care patients surviving dialysis-requiring acute kidney injury: a nationwide cohort study. Crit Care . 2013;17(4):R145. doi: 10.1186/cc12824 Husain-Syed F, Slutsky AS, Ronco C. Lung–Kidney Cross-Talk in the Critically Ill Patient. Am J Respir Crit Care Med . 2016;194(4):402–414. doi: 10.1164/rccm.201602-0420CP Darmon M, Legrand M, Terzi N. Understanding the kidney during acute respiratory failure. Intensive Care Med . 2017;43(8):1144–1147. doi: 10.1007/s00134-016-4532-z Joannidis M, Forni LG, Klein SJ, et al. Lung-kidney interactions in critically ill patients: consensus report of the Acute Disease Quality Initiative (ADQI) 21 Workgroup. Intensive Care Med . 2020;46(4):654–672. doi: 10.1007/s00134-019-05869-7 van den Akker JPC, Egal M, Groeneveld ABJ. Invasive mechanical ventilation as a risk factor for acute kidney injury in the critically ill: a systematic review and meta-analysis. Crit Care . 2013;17(3):R98. doi: 10.1186/cc12743 Geri G, Darmon M, Zafrani L, et al. Acute kidney injury in SARS-CoV2-related pneumonia ICU patients: a retrospective multicenter study. Ann Intensive Care . 2021;11(1):86. doi: 10.1186/s13613-021-00875-9 Lumlertgul N, Pirondini L, Cooney E, et al. Acute kidney injury prevalence, progression and long-term outcomes in critically ill patients with COVID-19: a cohort study. Ann Intensive Care . 2021;11(1):123. doi: 10.1186/s13613-021-00914-5 Hirsch JS, Ng JH, Ross DW, et al. Acute kidney injury in patients hospitalized with COVID-19. Kidney International . 2020;98(1):209–218. doi: 10.1016/j.kint.2020.05.006 Kuiper JW, Groeneveld ABJ, Slutsky AS, Plötz FB. Mechanical ventilation and acute renal failure. Crit Care Med . 2005;33(6):1408–1415. doi: 10.1097/01.ccm.0000165808.30416.ef Fougères E, Teboul JL, Richard C, Osman D, Chemla D, Monnet X. Hemodynamic impact of a positive end-expiratory pressure setting in acute respiratory distress syndrome: importance of the volume status. Crit Care Med . 2010;38(3):802–807. doi: 10.1097/CCM.0b013e3181c587fd Vieillard-Baron A, Matthay M, Teboul JL, et al. Experts’ opinion on management of hemodynamics in ARDS patients: focus on the effects of mechanical ventilation. Intensive Care Med . 2016;42(5):739–749. doi: 10.1007/s00134-016-4326-3 Vieillard-Baron A, Loubieres Y, Schmitt JM, Page B, Dubourg O, Jardin F. Cyclic changes in right ventricular output impedance during mechanical ventilation. J Appl Physiol (1985) . 1999;87(5):1644–1650. doi: 10.1152/jappl.1999.87.5.1644 Jardin F, Vieillard-Baron A. Right ventricular function and positive pressure ventilation in clinical practice: from hemodynamic subsets to respirator settings. Intensive Care Med . 2003;29(9):1426–1434. doi: 10.1007/s00134-003-1873-1 Mekontso Dessap A, Charron C, Devaquet J, et al. Impact of acute hypercapnia and augmented positive end-expiratory pressure on right ventricle function in severe acute respiratory distress syndrome. Intensive Care Med . 2009;35(11):1850–1858. doi: 10.1007/s00134-009-1569-2 Legrand M, Dupuis C, Simon C, et al. Association between systemic hemodynamics and septic acute kidney injury in critically ill patients: a retrospective observational study. Crit Care . 2013;17(6):R278. doi: 10.1186/cc13133 Ostermann M, Hall A, Crichton S. Low mean perfusion pressure is a risk factor for progression of acute kidney injury in critically ill patients – A retrospective analysis. BMC Nephrol . 2017;18:151. doi: 10.1186/s12882-017-0568-8 Chen C, Lee J, Johnson AE, Mark RG, Celi LA, Danziger J. Right Ventricular Function, Peripheral Edema, and Acute Kidney Injury in Critical Illness. Kidney International Reports . 2017;2(6):1059–1065. doi: 10.1016/j.ekir.2017.05.017 Annat G, Viale JP, Xuan BB, et al. Effect of PEEP Ventilation on Renal Function, Plasma Renin, Aldosterone, Neurophysins and Urinary ADH, and Prostaglandins. Anesthesiology . 1983;58(2):136–141. doi: 10.1097/00000542-198302000-00006 Farge D, De La Coussaye JE, Beloucif S, Fratacci MD, Payen DM. Interactions Between Hemodynamic and Hormonal Modifications During Peep-Induced Antidiuresis and Antinatriuresis. Chest . 1995;107(4):1095–1100. doi: 10.1378/chest.107.4.1095 Retamal J, Bugedo G, Larsson A, Bruhn A. High PEEP levels are associated with overdistension and tidal recruitment/derecruitment in ARDS patients. Acta Anaesthesiologica Scandinavica . 2015;59(9):1161–1169. doi: 10.1111/aas.12563 Ranieri VM, Giunta F, Suter PM, Slutsky AS. Mechanical ventilation as a mediator of multisystem organ failure in acute respiratory distress syndrome. JAMA . 2000;284(1):43–44. doi: 10.1001/jama.284.1.43 Evans L, Rhodes A, Alhazzani W, et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021. Intensive Care Med . 2021;47(11):1181–1247. doi: 10.1007/s00134-021-06506-y Papazian L, Aubron C, Brochard L, et al. Formal guidelines: management of acute respiratory distress syndrome. Annals of Intensive Care . 2019;9(1):69. doi: 10.1186/s13613-019-0540-9 Gattinoni L, Coppola S, Cressoni M, Busana M, Rossi S, Chiumello D. COVID-19 Does Not Lead to a “Typical” Acute Respiratory Distress Syndrome. Am J Respir Crit Care Med . 2020;201(10):1299–1300. doi: 10.1164/rccm.202003-0817LE Grasselli G, Zangrillo A, Zanella A, et al. Baseline Characteristics and Outcomes of 1591 Patients Infected With SARS-CoV-2 Admitted to ICUs of the Lombardy Region, Italy. JAMA . 2020;323(16):1574–1581. doi: 10.1001/jama.2020.5394 Grasso S, Mirabella L, Murgolo F, et al. Effects of Positive End-Expiratory Pressure in “High Compliance” Severe Acute Respiratory Syndrome Coronavirus 2 Acute Respiratory Distress Syndrome. Crit Care Med . 2020;48(12):e1332-e1336. doi: 10.1097/CCM.0000000000004640 Ottolina D, Zazzeron L, Trevisi L, et al. Acute kidney injury (AKI) in patients with Covid-19 infection is associated with ventilatory management with elevated positive end-expiratory pressure (PEEP). J Nephrol . 2022;35(1):99–111. doi: 10.1007/s40620-021-01100-3 Basse P, Morisson L, Barthélémy R, et al. Relationship between positive end-expiratory pressure levels, central venous pressure, systemic inflammation and acute renal failure in critically ill ventilated COVID-19 patients: a monocenter retrospective study in France. Acute Crit Care . 2023;38(2):172–181. doi: 10.4266/acc.2022.01494 Beurton A, Haudebourg L, Simon-Tillaux N, Demoule A, Dres M. Limiting positive end-expiratory pressure to protect renal function in SARS-CoV-2 critically ill patients. Journal of Critical Care . 2020;59:191–193. doi: 10.1016/j.jcrc.2020.07.008 Valk CMA, Tsonas AM, Botta M, et al. Association of early positive end-expiratory pressure settings with ventilator-free days in patients with coronavirus disease 2019 acute respiratory distress syndrome: A secondary analysis of the Practice of VENTilation in COVID-19 study. Eur J Anaesthesiol . 2021;38(12):1274–1283. doi: 10.1097/EJA.0000000000001565 COVID-ICU Group on behalf of the REVA Network and the COVID-ICU Investigators. Clinical characteristics and day-90 outcomes of 4244 critically ill adults with COVID-19: a prospective cohort study. Intensive Care Med . 2021;47(1):60–73. doi: 10.1007/s00134-020-06294-x Khwaja A. KDIGO Clinical Practice Guidelines for Acute Kidney Injury. Nephron Clin Pract . 2012;120(4):c179-c184. doi: 10.1159/000339789 Závada J, Hoste E, Cartin-Ceba R, et al. A comparison of three methods to estimate baseline creatinine for RIFLE classification. Nephrol Dial Transplant . 2010;25(12):3911–3918. doi: 10.1093/ndt/gfp766 Panitchote A, Mehkri O, Hastings A, et al. Factors associated with acute kidney injury in acute respiratory distress syndrome. Annals of Intensive Care . 2019;9(1):74. doi: 10.1186/s13613-019-0552-5 Gupta S, Coca SG, Chan L, et al. AKI Treated with Renal Replacement Therapy in Critically Ill Patients with COVID-19. JASN . 2021;32(1):161–176. doi: 10.1681/ASN.2020060897 Gupta S, Hayek SS, Wang W, et al. Factors Associated With Death in Critically Ill Patients With Coronavirus Disease 2019 in the US. JAMA Intern Med . 2020;180(11):1436–1447. doi: 10.1001/jamainternmed.2020.3596 Gattinoni L, Marini JJ, Pesenti A, Quintel M, Mancebo J, Brochard L. The “baby lung” became an adult. Intensive Care Med . 2016;42(5):663–673. doi: 10.1007/s00134-015-4200-8 ARDS Network. Ventilation with Lower Tidal Volumes as Compared with Traditional Tidal Volumes for Acute Lung Injury and the Acute Respiratory Distress Syndrome. N Engl J Med . 2000;342(18):1301–1308. doi: 10.1056/NEJM200005043421801 Slutsky AS, Ranieri VM. Ventilator-induced lung injury. N Engl J Med . 2013;369(22):2126–2136. doi: 10.1056/NEJMra1208707 Brower RG, Lanken PN, MacIntyre N, et al. Higher versus lower positive end-expiratory pressures in patients with the acute respiratory distress syndrome. N Engl J Med . 2004;351(4):327–336. doi: 10.1056/NEJMoa032193 Mercat A, Richard JCM, Vielle B, et al. Positive End-Expiratory Pressure Setting in Adults With Acute Lung Injury and Acute Respiratory Distress Syndrome: A Randomized Controlled Trial. JAMA . 2008;299(6):646–655. doi: 10.1001/jama.299.6.646 Meade MO, Cook DJ, Guyatt GH, et al. Ventilation Strategy Using Low Tidal Volumes, Recruitment Maneuvers, and High Positive End-Expiratory Pressure for Acute Lung Injury and Acute Respiratory Distress Syndrome: A Randomized Controlled Trial. JAMA . 2008;299(6):637–645. doi: 10.1001/jama.299.6.637 Lumlertgul N, Baker E, Pearson E, et al. Changing epidemiology of acute kidney injury in critically ill patients with COVID-19: a prospective cohort. Ann Intensive Care . 2022;12(1):118. doi: 10.1186/s13613-022-01094-6 Leite TT, Gomes CAM, Valdivia JMC, Libório AB. Respiratory parameters and acute kidney injury in acute respiratory distress syndrome: a causal inference study. Ann Transl Med . 2019;7(23):742. doi: 10.21037/atm.2019.11.92 Lombardi R, Nin N, Peñuelas O, et al. Acute Kidney Injury in Mechanically Ventilated Patients: The Risk Factor Profile Depends on the Timing of Aki Onset. Shock . 2017;48(4):411–417. doi: 10.1097/SHK.0000000000000871 Puybasset L, Cluzel P, Gusman P, Grenier P, Preteux F, Rouby JJ. Regional distribution of gas and tissue in acute respiratory distress syndrome. I. Consequences for lung morphology. CT Scan ARDS Study Group. Intensive Care Med . 2000;26(7):857–869. doi: 10.1007/s001340051274 Gattinoni L, Caironi P, Cressoni M, et al. Lung Recruitment in Patients with the Acute Respiratory Distress Syndrome. N Engl J Med . 2006;354(17):1775–1786. doi: 10.1056/NEJMoa052052 Calfee CS, Delucchi K, Parsons PE, et al. Subphenotypes in acute respiratory distress syndrome: latent class analysis of data from two randomised controlled trials. Lancet Respir Med . 2014;2(8):611–620. doi: 10.1016/S2213-2600(14)70097-9 Mekontso Dessap A, Charron C, Devaquet J, et al. Impact of acute hypercapnia and augmented positive end-expiratory pressure on right ventricle function in severe acute respiratory distress syndrome. Intensive Care Med . 2009;35(11):1850–1858. doi: 10.1007/s00134-009-1569-2 Gattinoni L, Chiumello D, Caironi P, et al. COVID-19 pneumonia: different respiratory treatments for different phenotypes? Intensive Care Med . 2020;46(6):1099–1102. doi: 10.1007/s00134-020-06033-2 Fogagnolo A, Grasso S, Dres M, et al. Focus on renal blood flow in mechanically ventilated patients with SARS-CoV-2: a prospective pilot study. J Clin Monit Comput . 2022;36(1):161–167. doi: 10.1007/s10877-020-00633-5 Barthélémy R, Beaucoté V, Bordier R, et al. Haemodynamic impact of positive end-expiratory pressure in SARS-CoV-2 acute respiratory distress syndrome: oxygenation versus oxygen delivery. Br J Anaesth . 2021;126(2):e70-e72. doi: 10.1016/j.bja.2020.10.026 Botta M, Tsonas AM, Pillay J, et al. Ventilation management and clinical outcomes in invasively ventilated patients with COVID-19 (PRoVENT-COVID): a national, multicentre, observational cohort study. Lancet Respir Med . 2021;9(2):139–148. doi: 10.1016/S2213-2600(20)30459-8 Haudebourg AF, Perier F, Tuffet S, et al. Respiratory Mechanics of COVID-19- versus Non-COVID-19-associated Acute Respiratory Distress Syndrome. Am J Respir Crit Care Med . 2020;202(2):287–290. doi: 10.1164/rccm.202004-1226LE Mekontso Dessap A, Boissier F, Charron C, et al. Acute cor pulmonale during protective ventilation for acute respiratory distress syndrome: prevalence, predictors, and clinical impact. Intensive Care Med . 2016;42(5):862–870. doi: 10.1007/s00134-015-4141-2 Salahuddin N, Sammani M, Hamdan A, et al. Fluid overload is an independent risk factor for acute kidney injury in critically Ill patients: results of a cohort study. BMC Nephrol . 2017;18(1):45. doi: 10.1186/s12882-017-0460-6 Rezoagli E, McNicholas B, Pham T, Bellani G, Laffey JG. Lung-kidney cross-talk in the critically ill: insights from the Lung Safe study. Intensive Care Med . 2020;46(5):1072–1073. doi: 10.1007/s00134-020-05962-2 Doig GS, McIlroy DR. Acute Kidney Injury in Patients With Acute Respiratory Distress Syndrome: The Chicken or the Egg? Crit Care Med . 2019;47(9):1273–1274. doi: 10.1097/CCM.0000000000003882 Duggan M, McCaul CL, McNamara PJ, Engelberts D, Ackerley C, Kavanagh BP. Atelectasis causes vascular leak and lethal right ventricular failure in uninjured rat lungs. Am J Respir Crit Care Med . 2003;167(12):1633–1640. doi: 10.1164/rccm.200210-1215OC Bellani G, Laffey JG, Pham T, et al. Epidemiology, Patterns of Care, and Mortality for Patients With Acute Respiratory Distress Syndrome in Intensive Care Units in 50 Countries. JAMA . 2016;315(8):788. doi: 10.1001/jama.2016.0291 Pickering JW, Endre ZH. Back-Calculating Baseline Creatinine with MDRD Misclassifies Acute Kidney Injury in the Intensive Care Unit. Clinical Journal of the American Society of Nephrology . 2010;5(7):1165–1173. doi: 10.2215/CJN.08531109 Lombardi R, Nin N, Lorente JA, et al. An Assessment of the Acute Kidney Injury Network Creatinine-Based Criteria in Patients Submitted to Mechanical Ventilation. Clinical Journal of the American Society of Nephrology . 2011;6(7):1547–1555. doi: 10.2215/CJN.09531010 Orieux A, Boyer A, Dewitte A, Combe C, Rubin S. Insuffisance rénale aiguë en soins intensifs-réanimation et ses conséquences: mise au point. Néphrologie & Thérapeutique . 2022;18(1):7–20. doi: 10.1016/j.nephro.2021.07.324 Collaborators COVID-ICU Group on behalf of the REVA Network and the COVID-ICU Investigators: Alain Mercat, Pierre Asfar, François Beloncle, Julien Demiselle, Tài Pham, Arthur Pavot, Xavier Monnet, Christian Richard, Alexandre Demoule, Martin Dres, Julien Mayaux, Alexandra Beurton, Cédric Daubin, Richard Descamps, Aurélie Joret, Damien Du Cheyron, Frédéric Pene, Jean-Daniel Chiche, Mathieu Jozwiak, Paul Jaubert, Guillaume Voiriot, Muriel Fartoukh, Marion Teulier, Clarisse Blayau, Erwen L'Her, Cécile Aubron, Laetitia Bodenes, Nicolas Ferriere, Johann Auchabie, Anthony Le Meur, Sylvain Pignal, Thierry Mazzoni, Jean-Pierre Quenot, Pascal Andreu, Jean-Baptiste Roudau, Marie Labruyère, Saad Nseir, Sébastien Preau, Julien Poissy, Daniel Mathieu, Sarah Benhamida, Rémi Paulet, Nicolas Roucaud, Martial Thyrault, Florence Daviet, Sami Hraiech, Gabriel Parzy, Aude Sylvestre, Sébastien Jochmans, Anne-Laure Bouilland, Mehran Monchi, Marc Danguy des Déserts, Quentin Mathais, Gwendoline Rager, Pierre Pasquier, Jean Reignier, Amélie Seguin, Charlotte Garret, Emmanuel Canet, Jean Dellamonica, Clément Saccheri, Romain Lombardi, Yanis Kouchit, Sophie Jacquier, Armelle Mathonnet, Mai-Ahn Nay, Isabelle Runge, Frédéric Martino, Laure Flurin, Amélie Rolle, Michel Carles, Rémi Coudroy, Arnaud W Thille, Jean-Pierre Frat, Maeva Rodriguez, Pascal Beuret, Audrey Tientcheu, Arthur Vincent, Florian Michelin, Fabienne Tamion, Dorothée Carpentier, Déborah Boyer, Christophe Girault, Valérie Gissot, Stéphan Ehrmann, Charlotte Salmon Gandonniere, Djlali Elaroussi, Agathe Delbove, Yannick Fedun, Julien Huntzinger, Eddy Lebas, Grâce Kisoka, Céline Grégoire, Stella Marchetta, Bernard Lambermont, Laurent Argaud, Thomas Baudry, Pierre-Jean Bertrand, Auguste Dargent, Christophe Guitton, Nicolas Chudeau, Mickaël Landais, Cédric Darreau, Alexis Ferré, Antoine Gros, Guillaume Lacave, Fabrice Bruneel, Mathilde Neuville, Jérôme Devaquet, Guillaume Tachon, Richard Gallot, Riad Chelha, Arnaud Galbois, Anne Jallot, Ludivine Chalumeau Lemoine, Khaldoun Kuteifan, Valentin Pointurier, Louise-Marie Jandeaux, Joy Mootien, Charles Damoisel, Benjamin Sztrymf, Matthieu Schmidt, Alain Combes, Juliette Chommeloux, Charles Edouard Luyt, Frédérique Schortgen, Leon Rusel, Camille Jung, Florent Gobert, Damien Vimpere, Lionel Lamhaut, Bertrand Sauneuf, Liliane Charrrier, Julien Calus, Isabelle Desmeules, Benoît Painvin, Jean-Marc Tadie, Vincent Castelain, Baptiste Michard, Jean-Etienne Herbrecht, Mathieu Baldacini, Nicolas Weiss, Sophie Demeret, Clémence Marois, Benjamin Rohaut, Pierre-Henri Moury, Anne-Charlotte Savida, Emmanuel Couadau, Mathieu Série, Nica Alexandru, Cédric Bruel, Candice Fontaine, Sonia Garrigou, Juliette Courtiade Mahler, Maxime Leclerc, Michel Ramakers, Pierre Garçon, Nicole Massou, Ly Van Vong, Juliane Sen, Nolwenn Lucas, Franck Chemouni, Annabelle Stoclin, Alexandre Avenel, Henri Faure, Angélie Gentilhomme, Sylvie Ricome, Paul Abraham, Céline Monard, Julien Textoris, Thomas Rimmele, Florent Montini, Gabriel Lejour, Thierry Lazard, Isabelle Etienney, Younes Kerroumi, Claire Dupuis, Marine Bereiziat, Elisabeth Coupez, François Thouy, Clément Hofmann, Nicolas Donat, Anne Chrisment, Rose-Marie Blot, Antoine Kimmoun, Audrey Jacquot, Matthieu Mattei, Bruno Levy, Ramin Ravan, Loïc Dopeux, Jean-Mathias Liteaudon, Delphine Roux, Brice Rey, Radu Anghel, Deborah Schenesse, Vincent Gevrey, Jermy Castanera, Philippe Petua, Benjamin Madeux, Otto Hartman, Michael Piagnerelli, Anne Joosten, Cinderella Noel, Patrick Biston, Thibaut Noel, Gurvan L E Bouar, Messabi Boukhanza, Elsa Demarest, Marie-France Bajolet, Nathanaël Charrier, Audrey Quenet, Cécile Zylberfajn, Nicolas Dufour, Bruno Mégarbane, Sébastian Voicu, Nicolas Deye, Isabelle Malissin, François Legay, Matthieu Debarre, Nicolas Barbarot, Pierre Fillatre, Bertrand Delord, Thomas Laterrade, Tahar Saghi, Wilfried Pujol, Pierre Julien Cungi, Pierre Esnault, Mickael Cardinale, Vivien Hong Tuan Ha, Grégory Fleury, Marie-Ange Brou, Daniel Zafmahazo, David Tran-Van, Patrick Avargues, Lisa Carenco, Nicolas Robin, Alexandre Ouali, Lucie Houdou, Christophe Le Terrier, Noémie Suh, Steve Primmaz, Jérome Pugin, Emmanuel Weiss, Tobias Gauss, Jean-Denis Moyer, Catherine Paugam Burtz, Béatrice La Combe, Rolland Smonig, Jade Violleau, Pauline Cailliez, Jonathan Chelly, Antoine Marchalot, Cécile Saladin, Christelle Bigot, Pierre-Marie Fayolle, Jules Fatséas, Amr Ibrahim, Dabor Resiere, Rabih Hage, Clémentine Cholet, Marie Cantier, Pierre Trouiler, Philippe Montravers, Brice Lortat-Jacob, Sebastien Tanaka, Alexy Tran Dinh, Jacques Duranteau, Anatole Harrois, Guillaume Dubreuil, Marie Werner, Anne Godier, Sophie Hamada, Diane Zlotnik, Hélène Nougue, Armand Mekontso-Dessap, Guillaume Carteaux, Keyvan Razazi, Nicolas de Prost, Nicolas Mongardon, Nicolas Mongardon, Meriam Lamraoui, Claire Alessandri, Quentin de Roux, Charles de Roquetaillade, Benjamin G Chousterman, Alexandre Mebazaa, Etienne Gayat, Marc Garnier, Emmanuel Pardo, Lea Satre-Buisson, Christophe Gutton, Elise Yvin, Clémence Marcault, Elie Azoulay, Michael Darmon, Hafid Ait Oufella, Geofroy Hariri, Tomas Urbina, Sandie Mazerand, Nicholas Heming, Francesca Santi, Pierre Moine, Djillali Annane, Adrien Bouglé, Edris Omar, Aymeric Lancelot, Emmanuelle Begot, Gaétan Plantefeve, Damien Contou, Hervé Mentec, Olivier Pajot, Stanislas Faguer, Olivier Cointault, Laurence Lavayssiere, Marie-Béatrice Nogier, Matthieu Jamme, Claire Pichereau, Jan Hayon, Hervé Outin, François Dépret, Maxime Coutrot, Maité Chaussard, Lucie Guillemet, Pierre Gofn, Romain Thouny, Julien Guntz, Laurent Jadot, Romain Persichini, Vanessa Jean-Michel, Hugues Georges, Thomas Caulier, Gaël Pradel, Marie-Hélène Hausermann, Thi My Hue Nguyen-Valat, Michel Boudinaud, Emmanuel Vivier, Sylvène Rosseli, Gaël Bourdin, Christian Pommier, Marc Vinclair, Simon Poignant, Sandrine Mons, Wulfran Bougouin, Franklin Bruna, Quentin Maestraggi, Christian Roth, Laurent Bitker, François Dhelft, Justine Bonnet-Chateau, Mathilde Filippelli, Tristan Morichau-Beauchant, Stéphane Thierry, Charlotte Le Roy, Mélanie Saint Jouan, Bruno Goncalves, Aurélien Mazeraud, Matthieu Daniel, Tarek Sharshar, Cyril Cadoz, Rostane Gaci, Sébastien Gette, Guillaune Louis, Sophie-Caroline Sacleux, Marie-Amélie Ordan, Aurélie Cravoisy, Marie Conrad, Guilhem Courte, Sébastien Gibot, Younès Benzidi, Claudia Casella, Laurent Serpin, Jean-Lou Setti, Marie-Catherine Besse, Anna Bourreau, Jérôme Pillot, Caroline Rivera, Camille Vinclair, Marie-Aline Robaux, Chloé Achino, Marie-Charlotte Delignette, Tessa Mazard, Frédéric Aubrun, Bruno Bouchet, Aurélien Frérou, Laura Muller, Charlotte Quentin, Samuel Degoul, Xavier Stihle, Claude Sumian, Nicoletta Bergero, Bernard Lanaspre, Hervé Quintard, Eve Marie Maiziere, Pierre-Yves Egreteau, Guillaume Leloup, Florin Berteau, Marjolaine Cottrel, Marie Bouteloup, Matthieu Jeannot, Quentin Blanc, Julien Saison, Isabelle Geneau, Romaric Grenot, Abdel Ouchike, Pascal Hazera, Anne-Lyse Masse, Suela Demiri, Corinne Vezinet, Elodie Baron, Deborah Benchetrit, Antoine Monsel, Grégoire Trebbia, Emmanuelle Schaack, Raphaël Lepecq, Mathieu Bobet, Christophe Vinsonneau, Thibault Dekeyser, Quentin Delforge, Imen Rahmani, Bérengère Vivet, Jonathan Paillot, Lucie Hierle, Claire Chaignat, Sarah Valette, Benoït Her, Jennifer Brunet, Mathieu Page, Fabienne Boiste, Anthony Collin, Florent Bavozet, Aude Garin, Mohamed Dlala, Kais Mhamdi, Bassem Beilouny, Alexandra Lavalard, Severine Perez, Benoit Veber, Pierre-Gildas Guitard, Philippe Gouin, Anna Lamacz, Fabienne Plouvier, Bertrand P Delaborde, Aïssa Kherchache, Amina Chaalal, Jean-Damien Ricard, Marc Amouretti, Santiago Freita-Ramos, Damien Roux, Jean-Michel Constantin, Mona Assef, Marine Lecore, Agathe Selves, Florian Prevost, Christian Lamer, Ruiying Shi, Lyes Knani, Sébastien Pili Floury, Lucie Vettoretti, Michael Levy, Lucile Marsac, Stéphane Dauger, Sophie Guilmin-Crépon, Hadrien Winiszewski, Gael Piton, Thibaud Soumagne, Gilles Capellier, Jean-Baptiste Putegnat, Frédérique Bayle, Maya Perrou, Ghyslaine Thao, Guillaume Géri, Cyril Charron, Xavier Repessé, Antoine Vieillard-Baron, Mathieu Guilbart, Pierre-Alexandre Roger, Sébastien Hinard, Pierre-Yves Macq, Kevin Chaulier, Sylvie Goutte, Patrick Chillet, Anaïs Pitta, Barbara Darjent, Amandine Bruneau, Sigismond Lasocki, Maxime Leger, Soizic Gergaud, Pierre Lemarie, Nicolas Terzi, Carole Schwebel, Anaïs Dartevel, Louis-Marie Galerneau, Jean-Luc Diehl, Caroline Hauw-Berlemont, Nicolas Péron, Emmanuel Guérot, Abolfazl Mohebbi Amoli, Michel Benhamou, Jean-Pierre Deyme, Olivier Andremont, Diane Lena, Julien Cady, Arnaud Causeret, Arnaud De La Chapelle, Christophe Cracco, Stéphane Rouleau, David Schnell, Camille Foucault, Cécile Lory, Thibault Chapelle, Vincent Bruckert, Julie Garcia, Abdlazize Sahraoui, Nathalie Abbosh, Caroline Bornstain, Pierre Pernet, Florent Poirson, Ahmed Pasem, Philippe Karoubi, Virginie Poupinel, Caroline Gauthier, François Bouniol, Philippe Feuchere, Florent Bavozet, Anne Heron, Serge Carreira, Malo Emery, Anne Sophie Le Floch, Luana Giovannangeli, Nicolas Herzog, Christophe Giacardi, Thibaut Baudic, Chloé Thill, Said Lebbah, Jessica Palmyre, Florence Tubach, David Hajage, Nicolas Bonnet, Nathan Ebstein, Stéphane Gaudry, Yves Cohen, Julie Noublanche, Olivier Lesieur, Arnaud Sément, Isabel Roca-Cerezo, Michel Pascal, Nesrine Sma, Gwenhaël Colin, Jean-Claude Lacherade, Gauthier Bionz, Natacha Maquigneau, Pierre Bouzat, Michel Durand, Marie-Christine Hérault, Jean-Francois Payen Tables Table 1 : Characteristics at admission Total population With AKI (n = 510) Without AKI (n = 556) p value Age 61 ± 12 62 ± 12 61 ± 12 0.307 Male sex 778 (73) 367 (73) 411 (74) 0.623 BMI 29 ± 6 29 ± 6 29 ± 6 0.827 SAPS II 40 ± 15 41 ± 15 39 ± 14 0.030 No antecedents 215 (20) 92 (18) 123 (22) 0.114 Active smoking 28 (3) 14 (3) 14 (3) 0.969 Respiratory history 201 (19) 106 (21) 95 (17) 0.151 COPD 53 (5) 27 (5) 26 (5) 0.747 Asthma 76 (7) 40 (8) 36 (6) 0.454 Cardiovascular history 586 (55) 288 (56) 298 (54) 0.379 Hypertension 454 (43) 230 (45) 224 (40) 0.120 Ischemic heart disease 94 (9) 42 (8) 52 (9) 0.587 Congestive heart failure 22 (2) 14 (3) 8 (1) 0.203 Diabetes 248 (23) 134 (26) 114 (21) 0.032 Immunodepression (a) 91 (9) 49 (9) 42 (8) 0.276 Bacterial co-infection 62 (6) 28 (5.5) 34 (6) 0.761 The data are presented in numbers and percentages (%) or as mean ± standard deviation. a includes: long-term immunosuppressive medications and/or corticosteroids, HIV infection, solid organ transplantation, active solid or hematological cancer AKI acute kidney injury failure, BMI body mass index, COPD chronic obstructive pulmonary disease, SAPS II simplified acute physiology score II Table 2: Prognosis and severity of acute kidney injury Total population With AKI (n = 510) Without AKI (n = 556) p value Initial severity of ARDS at day 1 a 0.063 Mild 294 (29) 135 (27) 159 (30) - Moderate 460 (45) 211 (43) 249 (47) - Severe 277 (27) 150 (30) 127 (24) - Kidney function: Basal creatinine b 54 ± 15 53 ± 17 55 ± 14 0.105 Severity of AKI from day 2 to 6 KDIGO 1 314 (29) 314 (61) - - KDIGO 2 98 (9) 98 (19) - - KDIGO 3 98 (9) 98 (19) - - RRT from day 2 to 6 54 (5) 54 (11) - - Prognosis: Mortality at 28 day c 237 (23) 140 (28) 97 (18) <0.001 Ventilator-free days d 9 ± 9 7 ± 8 11 ± 9 <0.001 ICU length of stay 26 ± 18 29 ± 18 23 ± 18 <0.001 Data are presented in numbers and percentages (%) or mean ± standard deviation. a according to Berlin criteria b calculated using the formula : c 31 lost to follow-up not included in this table d time between date of intubation and last successful extubation AKI acute kidney injury, ARDS acute respiratory distress syndrome, ICU Intensive Care Unit, MV mechanical ventilation, RRT renal replacement therapy Table 3: Mean respiratory and hemodynamic parameters between day 1 - day 3 With AKI Without AKI p value Respiratory parameters PEEP, cmH 2 0 11.4 ± 2.7 10.8 ± 2.6 < 0.001 Tidal volume, ml/kg of IBW 6.4 ± 1.2 6.3 ± 0.9 0.311 Plateau pressure, cmH 2 0 24.4 ± 4.0 23.9 ± 3.9 0.036 Driving pressure, cmH 2 0 a 13.0 ± 3.8 12.6 ± 3.4 0.131 Static compliance, ml/cmH 2 0 b 36.4 ± 15.9 36.8 ± 17.5 0.663 Blood gases PaO 2 / FiO 2 175 ± 65 180 ± 66 0.235 pH 7.39 ± 0.06 7.40 ± 0.05 <0.001 PaCO 2 , mmHg 45.0 ± 10.0 44.2 ± 8.2 0.151 Bicarbonates, mmol/l 26.3 ± 3.6 26.9 ± 3.2 0.003 c Lactate, mmol/l 1.6 ± 0.9 1.4 ± 0.7 <0.001 Rescue therapy Number of days in PP 0.8 ± 0.9 0.7 ± 0.9 0.386 Number of days NO 0.1 ± 0.5 0.1 ± 0.4 0.740 Hemodynamic parameters Number of days vasopressors c 1.8 ± 1.2 1.6 ± 1.2 0.003 RV dysfunction over 3 days, N (%) d 22 (4) 13 (2) 0.102 Data are presented as mean ± standard deviation or numbers and percentages (%). a calculated with driving pressure = plateau pressure - total PEEP b calculated with static compliance = tidal volume / driving pressure c a Student's t test has been performed here d if trans-thoracic ultrasound was performed AKI acute kidney injury, PEEP positive expiratory pressure, IBW ideal body weight, PaO 2 /FiO 2 arterial partial pressure of oxygen on fraction inspired in oxygen, PaCO 2 arterial partial pressure of carbon dioxide, PP prone position, NO inhaled nitric oxide, RV right ventricle Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 23 Jun, 2025 Reviews received at journal 23 Jun, 2025 Reviews received at journal 20 Jun, 2025 Reviewers agreed at journal 19 Jun, 2025 Reviews received at journal 18 Jun, 2025 Reviewers agreed at journal 17 Jun, 2025 Reviewers agreed at journal 17 Jun, 2025 Reviewers agreed at journal 16 Jun, 2025 Reviewers invited by journal 15 Jun, 2025 Editor assigned by journal 13 Jun, 2025 Submission checks completed at journal 13 Jun, 2025 First submitted to journal 12 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6880811","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":472213089,"identity":"134a7416-a564-4f4e-a278-b7ef5dce7107","order_by":0,"name":"Léo Poirot","email":"","orcid":"","institution":"CH Victor Jousselin","correspondingAuthor":false,"prefix":"","firstName":"Léo","middleName":"","lastName":"Poirot","suffix":""},{"id":472213090,"identity":"2440e12b-3912-46c2-9531-0446d657c698","order_by":1,"name":"Lionel Tchatat Wangueu","email":"","orcid":"","institution":"CHU de Rouen, Unité Inserm 1096 - ENVI, UFR Santé Université de Rouen Normandie","correspondingAuthor":false,"prefix":"","firstName":"Lionel","middleName":"Tchatat","lastName":"Wangueu","suffix":""},{"id":472213091,"identity":"0f27e409-dfad-4258-9873-2a7f30cb085a","order_by":2,"name":"Isaure Breteau","email":"","orcid":"","institution":"CHRU de Tours, Unité Inserm 1327 - ISCHEMIA, UFR de Médecine de Tours","correspondingAuthor":false,"prefix":"","firstName":"Isaure","middleName":"","lastName":"Breteau","suffix":""},{"id":472213092,"identity":"d7a00117-8237-4c2b-a250-da3e5c094c07","order_by":3,"name":"Matthieu Petit","email":"","orcid":"","institution":"Hôpital Ambroise Paré, APHP, Université Versailles Saint Quentin – Université Paris Saclay","correspondingAuthor":false,"prefix":"","firstName":"Matthieu","middleName":"","lastName":"Petit","suffix":""},{"id":472213093,"identity":"50c3ba6b-34b8-40c2-9737-80b002736b46","order_by":4,"name":"Matthieu Schmidt","email":"","orcid":"","institution":"Institut de Cardiologie, Hôpital Pitié-Salpêtrière","correspondingAuthor":false,"prefix":"","firstName":"Matthieu","middleName":"","lastName":"Schmidt","suffix":""},{"id":472213094,"identity":"bec7e066-58cc-48d2-ae03-1133bc815f18","order_by":5,"name":"Florent Bavozet","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIie3OvQrCMBDA8ZSALgddr1jfIRKoi+irtBR0EcEXEKGgo2sEH6IP4HBQ0KXujorgpFBwVPAbFyXVzSF/DnLLjwtjJtMfVlTPxWbAbnPNWmkJLB8vOv0X4eI7IuhrUoq2mJ1qPTlfENtPa0FMvJBpiTvzHAVN9NKOb022zWDc51zpSAN9KQET9JZQPQIlwYjZif5j2DpIEGeUCgQHOgcDxnkOaVc24BMKvBO6XskjbtpdKwodlbaFNaFQjqM8UhrGlJ3qtj1MBdtRvRzPIz350M/AZDKZTG9dAOKAQQK2aP+AAAAAAElFTkSuQmCC","orcid":"","institution":"CH Victor Jousselin","correspondingAuthor":true,"prefix":"","firstName":"Florent","middleName":"","lastName":"Bavozet","suffix":""}],"badges":[],"createdAt":"2025-06-12 13:23:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6880811/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6880811/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84873339,"identity":"a42a7d02-ae8c-4066-ab0d-89d306105f6c","added_by":"auto","created_at":"2025-06-18 09:21:30","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":69388,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Slide1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6880811/v1/eac96343275291a14904a50c.jpg"},{"id":84873338,"identity":"0a7b910f-5d72-4234-85f7-d3c376255706","added_by":"auto","created_at":"2025-06-18 09:21:30","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":63992,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Slide2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6880811/v1/16f9415ee48b487e3913f9ba.jpg"},{"id":84873342,"identity":"61f0d567-02dc-44e6-bfe6-5fb2dc410954","added_by":"auto","created_at":"2025-06-18 09:21:30","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":62488,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Slide3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6880811/v1/75cc71a9184edb3760f43b00.jpg"},{"id":84873340,"identity":"427f1dc9-f863-4fa9-b6a5-73b8ebd62d40","added_by":"auto","created_at":"2025-06-18 09:21:30","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":57749,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Slide4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6880811/v1/5340c48c603fb14109ab91ea.jpg"},{"id":84874936,"identity":"b1e95851-14b3-47e3-a63f-c516f5faf037","added_by":"auto","created_at":"2025-06-18 09:37:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1337273,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6880811/v1/2307067a-a2bc-4148-a329-3e858d8b92be.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"PEEP-AKI-COVID ICU: Effect of Positive End-Expiratory Pressure on Acute Kidney Injury Development in Patients with COVID-19-Associated Acute Respiratory Distress Syndrome: An Ancillary Analysis of the COVID-ICU Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCoronavirus disease 2019 (COVID-19) has significantly impacted ICU worldwide between 2020 and 2021, particularly through its severe form, which leads to acute respiratory distress syndrome (ARDS)\u003csup\u003e1\u003c/sup\u003e. It is now established that AKI is the most common organ failure associated with ARDS affecting 30 to 40% of patients\u003csup\u003e2,3\u003c/sup\u003e and more than 50% in the case of COVID-19\u003csup\u003e4\u003c/sup\u003e. The onset of renal dysfunction is a known risk factor for mortality in ARDS, whether linked to SARS-CoV-2\u003csup\u003e5\u003c/sup\u003e or not\u003csup\u003e2,3\u003c/sup\u003e. Moreover, AKI is linked to greater morbidity, as it prolongs the duration of mechanical ventilation\u003csup\u003e3\u003c/sup\u003e, extends ICU and hospital stays, and increases the risk of chronic kidney disease and end-stage renal disease\u003csup\u003e7,8\u003c/sup\u003e.\u003c/p\u003e\n\u003cp id=\"_Toc148050711\"\u003eHowever, the pathophysiology of renal damage in ARDS remains largely unknown\u003csup\u003e4\u003c/sup\u003e. Indeed, there are substantial gaps in our understanding of the heart-lung-kidney interactions, which are likely involved in this dual organ failure\u003csup\u003e9–11\u003c/sup\u003e. Several studies have identified mechanical ventilation as an independent risk factor for AKI in ARDS\u003csup\u003e2,12\u003c/sup\u003e, particularly in COVID-19 cases\u003csup\u003e13–15\u003c/sup\u003e. Hemodynamic changes, disruption of gas exchange, and systemic inflammation caused by this mechanical ventilation may explain the heightened risk of AKI in these patients\u003csup\u003e16\u003c/sup\u003e. However, the impact of specific ventilator settings on renal function has been insufficiently studied to date\u003csup\u003e10\u003c/sup\u003e.\u0026nbsp;\u003cbr\u003e\u0026nbsp;Specifically, PEEP may play a role in the development of renal dysfunction.\u0026nbsp;Previous studies by Husain et al.\u003csup\u003e9\u003c/sup\u003e and Gabarre et al.\u003csup\u003e4\u003c/sup\u003e have suggested that PEEP, by increasing intrathoracic pressure, reduces preload and cardiac output\u003csup\u003e17\u003c/sup\u003e, potentially lowering renal blood flow (RBF). Furthermore, PEEP increases transpulmonary pressure, which can cause pulmonary capillary collapse in cases of alveolar overdistension.\u0026nbsp;This leads to increased pulmonary vascular resistance, pulmonary arterial hypertension, and elevated right ventricular afterload\u003csup\u003e17–21\u003c/sup\u003e. Venous congestion and right ventricular dysfunction, which may result from these changes, are well-known causes of AKI due to reduced renal perfusion pressure\u003csup\u003e22–24\u003c/sup\u003e. Additionally, PEEP may disrupt renal physiology through neurohormonal changes\u003csup\u003e25,26\u003c/sup\u003e\u0026nbsp; and the release of systemic inflammatory mediators\u003csup\u003e27,28\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eFollowing international guidelines\u003csup\u003e29\u003c/sup\u003e and by analogy with non-COVID-19 ARDS\u003csup\u003e30\u003c/sup\u003e, PEEP is generally set at a high level in severe SARS-CoV-2 pneumonia. However, ARDS in COVID-19 \u0026nbsp;patients appear to exhibit distinct characteristics compared to other causes of ARDS\u003csup\u003e31,32\u003c/sup\u003e, potentially amplifying the adverse effects of high PEEP\u003csup\u003e33\u003c/sup\u003e.\u0026nbsp;Four observational clinical studies in COVID-19 patients have examined the relationship between PEEP and renal function.\u0026nbsp;These studies, though valuable, involved small sample sizes, produced conflicting results, and lacked sufficient statistical power\u003csup\u003e34–37\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eWe hypothesized that higher PEEP levels may have a deleterious effect on renal function. The primary aim of this study was to determine whether PEEP levels influence the occurrence of AKI in COVID-19 patients. Secondary objectives included identifying other factors contributing to AKI and evaluating the impact of renal failure on mortality in COVID-19 patients.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy design, data source\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;and patients\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp id=\"_Toc148050714\"\u003eThis study is an ancillary analysis of the COVID-ICU cohort\u003csup\u003e38\u003c/sup\u003e conducted between February 25, 2020 and May 4, 2020 during the first wave of the COVID-19 pandemic. The COVID-ICU cohort is a multicenter, prospective study conducted across 149 intensive care units (ICUs) in 138 hospitals across 3 countries (France, Switzerland and Belgium). It includes 4,244 patients aged over 16 years hospitalised in ICU with a positive laboratory-confirmed SARS-CoV-2 infection.\u003c/p\u003e\n\u003cp\u003eIn this analysis, Day 1 was defined as the first day of mechanical ventilation for each patient. Only those requiring invasive mechanical ventilation for at least 48 hours were included. Exclusion criteria comprised: patients who had received RRT or extracorporeal membrane oxygenation (ECMO) on Day 1 or earlier; those without daily PEEP values during the first three days of mechanical ventilation; patients mechanically ventilated for more than 24 hours before ICU admission; those without creatinine data on Day 1; patients with chronic kidney disease; and those with renal dysfunction as indicated by the Sequential Organ Failure Assessment (SOFA) score on Day 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCase definition\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRenal function was assessed using the KDIGO classification\u003csup\u003e39\u003c/sup\u003e based solely on biological and RRT criteria, as daily urine output and prior creatinine values were not collected. Baseline creatinine was estimated, in accordance with guidelines\u003csup\u003e39\u003c/sup\u003e, by back-calculation\u003csup\u003e40\u003c/sup\u003e of the Modification of Diet in Renal Disease (MDRD) formula, assuming a baseline glomerular filtration rate (GFR) of 75 ml/min/1.73 m² for patients without chronic kidney disease (CKD). The maximum creatinine value and/or the use of RRT between Day 2 and Day 6 were used to classify patients into two groups, using the KDIGO criteria for AKI: those who developed AKI within 5 days of intubation, and those who retained normal renal function. Patients who died before day 6 and who did not meet the KDIGO criteria for AKI were classified as not having AKI. The severity of renal dysfunction was further categorized according to the KDIGO stages. The severity of ARDS was assessed using the PaO\u003csub\u003e2\u003c/sub\u003e/FiO\u003csub\u003e2\u003c/sub\u003e ratio and the Berlin criteria\u003csup\u003e1\u003c/sup\u003e. Ventilator-free days were calculated by taking into account the date of intubation and the date of successful extubation, excluding periods of temporary weaning. In the case of death within 28 days, the patient was considered to have no ventilator-free days.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Collection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data were recorded daily at 10 a.m. by the study investigators using a standardized electronic form. Patient characteristics collected at ICU admission included age, sex, ethnicity, body mass index (BMI), active smoking status, Simplified Acute Physiology Score II (SAPS II), Sequential Organ Failure Assessment (SOFA) score, bacterial co-infection, and comorbidities, including chronic kidney disease. Ventilator settings (FiO\u003csup\u003e2\u003c/sup\u003e, tidal volume, total PEEP, plateau pressure, and PaO\u003csub\u003e2\u003c/sub\u003e/FiO\u003csub\u003e2\u003c/sub\u003e ratio); respiratory biomarkers (arterial blood gases, lactate levels); hemodynamic parameters (number of days on vasopressors, presence of right ventricular dysfunction) and rescue therapies (number of days in prone positioning and on inhaled nitric oxide) were collected and averaged over the first 72 hours. Prognostic data included ARDS severity on Day 1, renal function and/or use of renal replacement therapy within the first five days, 28-day mortality, ventilator-free days, and ICU length of stay. For each clinical or biological parameter, the worst value from the preceding 24 hours was recorded.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthical approval\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ethics committees of Switzerland (BASEC #: 2020-00704), the French Intensive Care Society (CE-SRLF 20-23), and Belgium (2020-294) approved the data collection protocol. Written informed consent was obtained from all participants before their inclusion in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStatistical Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eContinuous variables are expressed as mean (standard deviation), while categorical variables are presented as numbers (percentages). Group comparisons were performed using the Student's t-test for continuous variables and the Chi-square test for categorical variables.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo identify an independent association between the early PEEP level applied (average value from Day 1 to Day 3) and the development of AKI within 6 days following intubation, a logistic regression model was used. The risk factors for AKI in COVID-19 and ARDS, commonly identified in the literature\u003csup\u003e4,15,41,42\u003c/sup\u003e, were included in the adjusted model. Variables with p-value \u0026lt; 0.05 in univariate analysis were incorporated in the multivariate model. Subsequently, we sought to determine the PEEP threshold level significantly associated with the development of AKI.\u003c/p\u003e\n\u003cp\u003eA second logistic regression analysis was conducted to assess whether early AKI in ICU patients was correlated with increased 28-day mortality. Adjustments were made for various mortality risk factors, as identified in the two largest cohorts from developed countries during the first wave of COVID-19\u003csup\u003e38,43\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAll variables included in the models were predefined, with no additional variable selection. The goodness of fit for the logistic regression was evaluated using the Hosmer-Lemeshow test. The results of the multivariate analyses are presented as odds ratios (OR) with 95% confidence intervals (CI) and p-values. A two-tailed p-value \u0026lt; 0.05 was considered statistically significant. Missing data were imputed using the median in SPSS v28.0, and all analyses were performed using R v.4.3.0.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy Population\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong 3583 patients who were mechanically ventilated for at least 48 hours, 1066\u0026nbsp;were included in our study after the application of the exclusion criteria. (Figure 1)\u003cbr\u003e\u0026nbsp;The majority\u0026nbsp;were overweight: BMI 29 ±\u0026nbsp;6; male (73%) with a mean age of 61\u0026nbsp;±\u0026nbsp;12 years. The most common comorbidity was hypertension. (Table 1)\u003c/p\u003e\n\u003cp id=\"_Toc148050721\"\u003e\u003cstrong\u003e\u003cem\u003eAcute Kidney Injury: Incidence, Morbidity and Mortality\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOf the 1066 patients, 510 (48%) developed acute kidney injury within 5 days of intubation. Diabetes was more prevalent in the AKI group (26 vs 21% in the non-AKI group, \u003cem\u003ep = 0\u003c/em\u003e.032). (Table 1)\u0026nbsp;The majority (61%) of AKI cases remained at KDIGO stage 1, while 19% progressed to stage 3, and 11% required RRT. Patients with AKI had higher 28-day mortality (28% vs. 18%, p \u0026lt; 0.001), a longer ICU stay (29 ± 18 vs. 23 ± 18 days, p \u0026lt; 0.001), and fewer ventilator-free days (7 ± 8 vs. 11 ± 9, p \u0026lt; 0.001) compared to those without AKI.\u0026nbsp;(Table 2)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eRespiratory and Hemodynamic Parameters\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompared to patients without AKI, PEEP was significantly higher in the AKI group (11.4 ± 2.7 vs 10.8 ± 2.6 cmH\u003csub\u003e2\u003c/sub\u003eO, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). Static lung compliance was similar in both groups (36.4 ± 15.9 vs 36.8 ± 17.5 ml/cmH\u003csub\u003e2\u003c/sub\u003eO, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.663) while pH was lower (7.39 ± 0.06 vs 7.40 ± 0.05, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) and lactate was higher (1.6 ± 0.9 vs 1.4 ± 0.7 mmol/l \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001) in the AKI group. From a hemodynamic perspective, patients with AKI required more days on vasopressors (1.8 ± 1.2 vs 1.6 ± 1.2 days, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.029). (Table 3)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eRisk Factors Associated with Acute Kidney Injury\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter adjusting for confounding factors frequently identified or suspected in the literature (age, sex, BMI, ARDS severity as measured by the PaO\u003csub\u003e2\u003c/sub\u003e/FiO\u003csub\u003e2\u003c/sub\u003e ratio, tidal volume and cardiovascular comorbidities such as diabetes) and for factors identified in univariate analysis, PEEP was found to be statistically significantly associated with the development of AKI within 5 days of intubation (odds ratio [OR]1.09; 95% confidence interval [95% CI], 1.04-1.15). The number of days on vasopressors (OR 1.34; 95% CI, 1.01-1.77) and elevated lactate levels (OR 1.47; 95% CI, 1.19-1.87) were also significantly associated with renal impairment. (Figure 2). Subsequently, Patients with a 3-day mean PEEP strictly greater than 15 cmH\u003csub\u003e2\u003c/sub\u003eO (33 patients) had a significantly increased risk of developing AKI (OR 2.77; 95% CI, 1.31-6.24) (Figure 3). Analysis comparing patients with PEEP \u0026gt; 12 cmH\u003csub\u003e2\u003c/sub\u003e0 (306 patients) to the rest of the cohort did not show a significantly higher risk of AKI (OR 1.29; 95% CI, 0.98-1.70).\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc148050724\"\u003e\u003cstrong\u003e\u003cem\u003eRisk Factors Associated with Mortality at 28 days\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn a multivariate analysis adjusted for mortality risk factors, the level of PEEP was not associated with 28-day mortality (OR 1.01; 95% CI, 0.95-1.07). However, the occurrence of AKI within 5 days of initiating mechanical ventilation was associated with increased mortality at 28 days (OR 1.64; 95% CI, 1.21-2.24), as same as the age and the initial severity of ARDS. (Figure 4)\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this ancillary study from a large international cohort of critically ill COVID-19 patients, 48% of mechanically ventilated patients developed de novo AKI within 5 days of intubation. Higher PEEP levels during the first 72 hours were independently associated with AKI onset (OR 1.09; 95% CI, 1.04-1.15), with PEEP \u0026gt;15 cmH₂O significantly increasing risk (OR 2.77; 95% CI, 1.31-6.24). Prolonged vasopressor use and elevated lactate levels also correlated with renal dysfunction. AKI was independently associated with higher 28-day mortality (OR 1.64; 95% CI, 1.21-2.24), but no significant link was found between PEEP levels and mortality (OR 1.00; 95% CI, 0.94-1.07).\u003c/p\u003e\n\u003cp\u003ePEEP has traditionally been set at a high level in patients with ARDS. In our cohort of COVID-19-related ARDS, mean PEEP levels during the early days of mechanical ventilation were 11.4 ± 2.7 cmH\u003csub\u003e2\u003c/sub\u003eO, reflecting standard clinical practice. The rationale behind high PEEP settings is based on the \"Baby Lung\" concept, proposed by Gattinoni et al.\u003csup\u003e44\u003c/sup\u003e, which aims to counteract lung derecruitment induced by low tidal volume-protective ventilation \u003csup\u003e45\u003c/sup\u003e, reduce inflammation, atelectrauma\u003csup\u003e46\u003c/sup\u003e and improve oxygenation. While three major randomized trials have shown that high PEEP enhances oxygenation in ARDS patients\u003csup\u003e47–49\u003c/sup\u003e, none—including our study—have demonstrated a mortality benefit. This discrepancy may be due to the underexplored adverse effects of high PEEP on extrapulmonary organs.\u003c/p\u003e\n\u003cp\u003eBy analyzing a large cohort using logistic regression while accounting for numerous confounding factors associated with AKI in COVID-19, we demonstrated that each 1 cmH₂O increase in PEEP was associated with a 9% higher risk of acute kidney injury. Our findings reinforce and extend prior literature on COVID-19, such as a secondary analysis of a Dutch multicenter cohort involving 468 patients\u003csup\u003e37\u003c/sup\u003e and an Italian case-control study involving 101 patients\u003csup\u003e34\u003c/sup\u003e, both of which reported an association between PEEP and AKI with 1.5 to 5-fold higher AKI in the high PEEP groups, respectively. Observational studies, including before-and-after observational studies,\u003csup\u003e36,50\u003c/sup\u003e have also suggested a positive relationship between PEEP and renal impairment. Moreover, we identified a PEEP threshold that might elevate the risk of AKI: while the association with PEEP levels above 12 cmH\u003csub\u003e2\u003c/sub\u003e0 approached statistical significance (OR 1.29; 95%CI, 0.98-1.70), it was significant above 15 cmH\u003csub\u003e2\u003c/sub\u003e0 (OR 2.77; 95% CI, 1.31-6.24). We chose to analyze these two PEEP thresholds because, on average, the PEEP levels reported in randomized trials comparing “high” PEEP to “moderate” PEEP were 15 cmH\u003csub\u003e2\u003c/sub\u003eO and 9 cmH\u003csub\u003e2\u003c/sub\u003eO, respectively\u003csup\u003e47–49\u003c/sup\u003e. Therefore, 12 cmH\u003csub\u003e2\u003c/sub\u003eO can be considered the threshold beyond which PEEP can be classified as elevated, and 15 cmH\u003csub\u003e2\u003c/sub\u003eO as very high PEEP. In the context of ARDS unrelated to COVID-19, only a retrospective study involving 27,248 patients from the MIMIC-III cohort\u003csup\u003e51\u003c/sup\u003e has demonstrated a similar association between increased PEEP and AKI, with each 1 cmH\u003csub\u003e2\u003c/sub\u003e0 increase in PEEP associated with a roughly 1.2-fold increased risk of AKI. \u0026nbsp;However, this result contrasts with other large-scale observational studies that failed to demonstrate this association in ARDS unrelated to COVID-19\u003csup\u003e3,41,52\u003c/sup\u003e. Several factors may explain this discrepancy in the literature between COVID-19 and non-COVID-19 ARDS. First, studies outside the context of COVID-19 often include a diverse range of ARDS etiologies and ARDS phenotypes\u003csup\u003e53\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDepending on the phenotype, patients respond differently to PEEP in terms of pulmonary recruitability\u003csup\u003e53–55\u003c/sup\u003e.\u0026nbsp;The hemodynamic consequences of PEEP are inversely correlated with this recruitability\u003csup\u003e18,56\u003c/sup\u003e. Some patients with higher pulmonary recruitability experience little or no hemodynamic effects from PEEP. Consequently, the association between PEEP and AKI is less pronounced in studies involving heterogeneous populations. In the context of COVID-19, although different ARDS phenotypes have been described\u003csup\u003e57\u003c/sup\u003e, the study populations remain relatively homogeneous. Secondly, it has been noted that patients with COVID-19-related ARDS tend to have preserved pulmonary compliance\u003csup\u003e31,32\u003c/sup\u003e. This may amplify the hemodynamic effects of high PEEP in this population as suggested by Grasso et al.\u003csup\u003e33\u003c/sup\u003e potentially leading to impaired renal blood flow\u003csup\u003e58\u003c/sup\u003e and reduced oxygen delivery to renal tissues\u003csup\u003e59\u003c/sup\u003e. Again according to Grasso et Al.\u003csup\u003e33\u003c/sup\u003e high PEEP in the context of preserved compliance could generate greater alveolar overdistension, thus increasing the systemic release of inflammatory mediators, which also affect renal physiology\u003csup\u003e28\u003c/sup\u003e. However, our study did not find any significant difference in pulmonary compliance between patients with and without AKI. Furthermore, the average compliance (36.6 ml/cmH\u003csub\u003e2\u003c/sub\u003e0) was consistent with values observed in both non-COVID ARDS and other studies involving COVID-19-related ARDS\u003csup\u003e60,61\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eFrom a pathophysiological standpoint, it is noteworthy that right ventricular dysfunction, a potential mechanism linking PEEP and AKI in COVID-19, was observed less frequently in our cohort (3.2%) compared to non-COVID-19-related ARDS\u003csup\u003e62\u003c/sup\u003e. This lower prevalence is likely attributable to the lack of systematic screening for acute cor pulmonale in our study.\u003c/p\u003e\n\u003cp\u003eOur study also confirms that other clinical factors, such as the duration of vasopressor use and elevated blood lactate levels, are independent predictors of AKI. These factors reflect the overall severity of illness and have been identified as risk factors for renal impairment in other studies\u003csup\u003e3,63\u003c/sup\u003e. Consistent with previous reports in the literature\u003csup\u003e5,15,38,43\u003c/sup\u003e our analysis also underscores that AKI is a strong predictor of increased mortality in COVID-19 patients requiring mechanical ventilation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo our knowledge, this is the first study to establish an independent and temporal association between PEEP and AKI in COVID-19. We specifically observed the effect of PEEP during the first 72 hours, as most studies on the topic\u003csup\u003e47–49\u003c/sup\u003e. Additionally, to account for other confounding factors that might arise between the exposure period and the occurrence or non-occurrence of AKI, we limited the observation of AKI to the period between day 2 and day 6. This approach allowed us, on the one hand, to ensure a sufficient period of PEEP exposure for the potential development of AKI. On the other hand, it helped avoid incorrectly associating AKI after day 6, which is likely not physiologically related to PEEP applied between day 1 and day 3. Thus, our study introduces a critical temporal element, which is often missing in other observational studies. This finding reinforces the association, as highlighted in previous editorials\u003csup\u003e64,65\u003c/sup\u003e. Only Géri \u003cem\u003eet al.\u003c/em\u003e in 2021\u003csup\u003e13\u003c/sup\u003e have conducted a similar analysis with comparable results, albeit with a much smaller sample of non-COVID-related ARDS.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, the positive association between PEEP and AKI must be interpreted with caution, as no significant relationship was found between PEEP levels and 28-day mortality, despite the strong association between AKI and mortality.\u0026nbsp;Additionally, insufficient PEEP may lead to significant lung derecruitment and atelectasis, increasing pulmonary arterial pressure, as demonstrated in both animal models\u003csup\u003e66\u003c/sup\u003e and clinical studies\u003csup\u003e56\u003c/sup\u003e.\u0026nbsp;Therefore, an individualized PEEP strategy is crucial to balance its beneficial effects on ventilation while minimizing the risk of renal impairment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur study has several limitations that must be underlined. First, being an observational study causality cannot be conclusively established. Second, the large sample size and high clinical activity during the COVID-19 crisis led to missing data, which may have obscured additional confounding factors. Although data imputation methods were employed, these limitations should be considered. Third, the mortality rate in our cohort (23%) was lower than that reported in the original COVID-ICU study or in the large \"Lung Safe\" study\u003csup\u003e67\u003c/sup\u003e due in part to the exclusion of patients on ECMO or with pre-existing renal dysfunction to limit confounding factors. Fourth, the method of baseline creatinine imputation by the back-calculation of the MDRD formula, although validated\u003csup\u003e40\u003c/sup\u003e, remains controversial and may have overestimated the incidence of AKI by approximately 10%\u003csup\u003e68\u003c/sup\u003e. The non-use of the diuresis criterion in the KDIGO classification, although also validated\u003csup\u003e69\u003c/sup\u003e, may underestimate the incidence of AKI by approximately 15%\u003csup\u003e70\u003c/sup\u003e. A misclassification of AKI is therefore possible in our study, although the incidence appears to align with the findings reported in the existing literature on the subject\u003csup\u003e4\u003c/sup\u003e. Finally, only a single daily PEEP measurement was recorded at 10 am, whereas PEEP levels could fluctuate throughout the day for each patient, which could have introduced bias in the exposure assessment.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur findings suggest that elevated levels of PEEP are independently associated with the development of AKI in patients with COVID-19-related ARDS. This highlights the need for clinicians to carefully consider the potential renal implications of high PEEP settings when managing these patients. Future prospective clinical trials are essential to confirm these findings, particularly in non-COVID-19-related ARDS, and to establish clear recommendations.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e: 95% confidence interval\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAKI\u003c/strong\u003e: Acute Kidney Injury\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eARDS\u003c/strong\u003e:Acute Respiratory Distress Syndrome\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e: Body Mass Index\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCKD:\u0026nbsp;\u003c/strong\u003eChronic Kidney Disease\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCOPD\u003c/strong\u003e: Chronic Obstructive Pulmonary Disease\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCOVID-19\u003c/strong\u003e: Coronavirus disease 2019\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eECMO\u003c/strong\u003e: Extracorporeal Membrane Oxygenation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGFR\u003c/strong\u003e: Glomerular Filtration Rate\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eICU\u003c/strong\u003e: Intensive Care Unit\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKDIGO\u003c/strong\u003e: Kidney Disease\u0026nbsp;ImprovalGlobal Outcomes\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMDRD\u003c/strong\u003e: Modification of Diet in Renal Disease\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMV\u003c/strong\u003e: mechanical ventilation\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNO:\u0026nbsp;\u003c/strong\u003eNitric oxide\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e: Odds Ratio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePaCO\u003csub\u003e2\u003c/sub\u003e\u003c/strong\u003e: Partial Pressure of Carbon Carbon Dioxide\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePaO\u003csub\u003e2\u003c/sub\u003e/FiO\u003csub\u003e2\u003c/sub\u003e\u003c/strong\u003e: ratio between Partial Oxygen Pressure and Inspired Oxygen Fraction\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePEEP\u003c/strong\u003e: Positive End-Expiratory Pressure\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePP:\u0026nbsp;\u003c/strong\u003eProne Position\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePplat\u003c/strong\u003e:Plateau Pressure\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRBF:\u0026nbsp;\u003c/strong\u003eRenal Blood Flow\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRRT\u003c/strong\u003e:Renal Replacement Therapy\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSOFA\u003c/strong\u003e: sequential organ failure assessment score\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSAPS II\u003c/strong\u003e: Simplified Acute Physiology Score II\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTIW\u003c/strong\u003e: Theoretical Ideal Weight\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRV\u003c/strong\u003e: Right Ventricle\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVt\u003c/strong\u003e: Volume tidal\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e: The ethics committees of Switzerland (BASEC #: 2020-00704), the French Intensive Care Society\u0026nbsp;(CE-SRLF 20-23) and Belgium (2020-294) approved the data collection protocol.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eAll patients or close relatives were informed that their data were included in the COVID-ICU cohort.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and material\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Restrictions apply to the availability of these data and so are not publicly available. However, data are available from the authors upon reasonable request and with the permission of the institution.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e The authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding:\u003c/em\u003e\u003c/strong\u003eThis study was funded by the Foundation AP-HP and the Direction de la Recherche Clinique et du Development and the French Ministry of Health. The REVA network received a 75 000 \u0026euro; research grant form Air Liquide Healthcare. The funder had no role in the design and conduct of the study, collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors\u0026apos; contributions\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Florent Bavozet (FB), Lionel Tchatat-Wangueu (LTW), and L\u0026eacute;o Poirot (LP) conceived and designed the study and were involved in drafting the manuscript. FB performed the data retrieval. LTW, Isaure Breteau (IB) performed the statistical analysis. All the authors were involved in the interpretation of the data, in drafting the manuscript, and made critical revisions to the discussion section. All authors read and approved the final version to be published.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e: The authors are particularly grateful to all caregivers, COVID-ICU investigators and patients who have been involved in the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eThe ARDS Definition Task Force*. Acute Respiratory Distress Syndrome: The Berlin Definition. \u003cem\u003eJAMA\u003c/em\u003e. 2012;307(23):2526\u0026ndash;2533. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jama.2012.5669\u003c/span\u003e\u003cspan address=\"10.1001/jama.2012.5669\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDarmon M, Clec\u0026rsquo;h C, Adrie C, et al. Acute Respiratory Distress Syndrome and Risk of AKI among Critically Ill Patients. \u003cem\u003eCJASN\u003c/em\u003e. 2014;9(8):1347\u0026ndash;1353. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2215/CJN.08300813\u003c/span\u003e\u003cspan address=\"10.2215/CJN.08300813\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcNicholas BA, Rezoagli E, Pham T, et al. Impact of Early Acute Kidney Injury on Management and Outcome in Patients With Acute Respiratory Distress Syndrome: A Secondary Analysis of a Multicenter Observational Study*. \u003cem\u003eCritical Care Medicine\u003c/em\u003e. 2019;47(9):1216\u0026ndash;1225. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/CCM.0000000000003832\u003c/span\u003e\u003cspan address=\"10.1097/CCM.0000000000003832\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGabarre P, Dumas G, Zafrani L. Insuffisance r\u0026eacute;nale aigu\u0026euml; chez les patients COVID-19 en soins intensifs. \u003cem\u003eM\u0026eacute;decine Intensive R\u0026eacute;animation\u003c/em\u003e. 2021;30(Hors-s\u0026eacute;rie 1):43\u0026ndash;52. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.37051/mir-00069\u003c/span\u003e\u003cspan address=\"10.37051/mir-00069\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlenezi FK, Almeshari MA, Mahida R, Bangash MN, Thickett DR, Patel JM. Incidence and risk factors of acute kidney injury in COVID-19 patients with and without acute respiratory distress syndrome (ARDS) during the first wave of COVID-19: a systematic review and Meta-Analysis. \u003cem\u003eRenal Failure\u003c/em\u003e. 2021;43(1):1621\u0026ndash;1633. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/0886022X.2021.2011747\u003c/span\u003e\u003cspan address=\"10.1080/0886022X.2021.2011747\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoste EAJ, Bagshaw SM, Bellomo R, et al. Epidemiology of acute kidney injury in critically ill patients: the multinational AKI-EPI study. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2015;41(8):1411\u0026ndash;1423. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-015-3934-7\u003c/span\u003e\u003cspan address=\"10.1007/s00134-015-3934-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoca SG, Singanamala S, Parikh CR. Chronic kidney disease after acute kidney injury: a systematic review and meta-analysis. \u003cem\u003eKidney International\u003c/em\u003e. 2012;81(5):442\u0026ndash;448. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/ki.2011.379\u003c/span\u003e\u003cspan address=\"10.1038/ki.2011.379\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGammelager H, Christiansen C, Johansen M, T\u0026oslash;nnesen E, Jespersen B, S\u0026oslash;rensen H. Five-year risk of end-stage renal disease among intensive care patients surviving dialysis-requiring acute kidney injury: a nationwide cohort study. \u003cem\u003eCrit Care\u003c/em\u003e. 2013;17(4):R145. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/cc12824\u003c/span\u003e\u003cspan address=\"10.1186/cc12824\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHusain-Syed F, Slutsky AS, Ronco C. Lung\u0026ndash;Kidney Cross-Talk in the Critically Ill Patient. \u003cem\u003eAm J Respir Crit Care Med\u003c/em\u003e. 2016;194(4):402\u0026ndash;414. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1164/rccm.201602-0420CP\u003c/span\u003e\u003cspan address=\"10.1164/rccm.201602-0420CP\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDarmon M, Legrand M, Terzi N. Understanding the kidney during acute respiratory failure. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2017;43(8):1144\u0026ndash;1147. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-016-4532-z\u003c/span\u003e\u003cspan address=\"10.1007/s00134-016-4532-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoannidis M, Forni LG, Klein SJ, et al. Lung-kidney interactions in critically ill patients: consensus report of the Acute Disease Quality Initiative (ADQI) 21 Workgroup. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2020;46(4):654\u0026ndash;672. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-019-05869-7\u003c/span\u003e\u003cspan address=\"10.1007/s00134-019-05869-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan den Akker JPC, Egal M, Groeneveld ABJ. Invasive mechanical ventilation as a risk factor for acute kidney injury in the critically ill: a systematic review and meta-analysis. \u003cem\u003eCrit Care\u003c/em\u003e. 2013;17(3):R98. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/cc12743\u003c/span\u003e\u003cspan address=\"10.1186/cc12743\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGeri G, Darmon M, Zafrani L, et al. Acute kidney injury in SARS-CoV2-related pneumonia ICU patients: a retrospective multicenter study. \u003cem\u003eAnn Intensive Care\u003c/em\u003e. 2021;11(1):86. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13613-021-00875-9\u003c/span\u003e\u003cspan address=\"10.1186/s13613-021-00875-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLumlertgul N, Pirondini L, Cooney E, et al. Acute kidney injury prevalence, progression and long-term outcomes in critically ill patients with COVID-19: a cohort study. \u003cem\u003eAnn Intensive Care\u003c/em\u003e. 2021;11(1):123. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13613-021-00914-5\u003c/span\u003e\u003cspan address=\"10.1186/s13613-021-00914-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHirsch JS, Ng JH, Ross DW, et al. Acute kidney injury in patients hospitalized with COVID-19. \u003cem\u003eKidney International\u003c/em\u003e. 2020;98(1):209\u0026ndash;218. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.kint.2020.05.006\u003c/span\u003e\u003cspan address=\"10.1016/j.kint.2020.05.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKuiper JW, Groeneveld ABJ, Slutsky AS, Pl\u0026ouml;tz FB. Mechanical ventilation and acute renal failure. \u003cem\u003eCrit Care Med\u003c/em\u003e. 2005;33(6):1408\u0026ndash;1415. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/01.ccm.0000165808.30416.ef\u003c/span\u003e\u003cspan address=\"10.1097/01.ccm.0000165808.30416.ef\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFoug\u0026egrave;res E, Teboul JL, Richard C, Osman D, Chemla D, Monnet X. Hemodynamic impact of a positive end-expiratory pressure setting in acute respiratory distress syndrome: importance of the volume status. \u003cem\u003eCrit Care Med\u003c/em\u003e. 2010;38(3):802\u0026ndash;807. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/CCM.0b013e3181c587fd\u003c/span\u003e\u003cspan address=\"10.1097/CCM.0b013e3181c587fd\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVieillard-Baron A, Matthay M, Teboul JL, et al. Experts\u0026rsquo; opinion on management of hemodynamics in ARDS patients: focus on the effects of mechanical ventilation. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2016;42(5):739\u0026ndash;749. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-016-4326-3\u003c/span\u003e\u003cspan address=\"10.1007/s00134-016-4326-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVieillard-Baron A, Loubieres Y, Schmitt JM, Page B, Dubourg O, Jardin F. Cyclic changes in right ventricular output impedance during mechanical ventilation. \u003cem\u003eJ Appl Physiol (1985)\u003c/em\u003e. 1999;87(5):1644\u0026ndash;1650. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1152/jappl.1999.87.5.1644\u003c/span\u003e\u003cspan address=\"10.1152/jappl.1999.87.5.1644\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJardin F, Vieillard-Baron A. Right ventricular function and positive pressure ventilation in clinical practice: from hemodynamic subsets to respirator settings. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2003;29(9):1426\u0026ndash;1434. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-003-1873-1\u003c/span\u003e\u003cspan address=\"10.1007/s00134-003-1873-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMekontso Dessap A, Charron C, Devaquet J, et al. Impact of acute hypercapnia and augmented positive end-expiratory pressure on right ventricle function in severe acute respiratory distress syndrome. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2009;35(11):1850\u0026ndash;1858. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-009-1569-2\u003c/span\u003e\u003cspan address=\"10.1007/s00134-009-1569-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLegrand M, Dupuis C, Simon C, et al. Association between systemic hemodynamics and septic acute kidney injury in critically ill patients: a retrospective observational study. \u003cem\u003eCrit Care\u003c/em\u003e. 2013;17(6):R278. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/cc13133\u003c/span\u003e\u003cspan address=\"10.1186/cc13133\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOstermann M, Hall A, Crichton S. Low mean perfusion pressure is a risk factor for progression of acute kidney injury in critically ill patients \u0026ndash; A retrospective analysis. \u003cem\u003eBMC Nephrol\u003c/em\u003e. 2017;18:151. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12882-017-0568-8\u003c/span\u003e\u003cspan address=\"10.1186/s12882-017-0568-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen C, Lee J, Johnson AE, Mark RG, Celi LA, Danziger J. Right Ventricular Function, Peripheral Edema, and Acute Kidney Injury in Critical Illness. \u003cem\u003eKidney International Reports\u003c/em\u003e. 2017;2(6):1059\u0026ndash;1065. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ekir.2017.05.017\u003c/span\u003e\u003cspan address=\"10.1016/j.ekir.2017.05.017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnnat G, Viale JP, Xuan BB, et al. Effect of PEEP Ventilation on Renal Function, Plasma Renin, Aldosterone, Neurophysins and Urinary ADH, and Prostaglandins. \u003cem\u003eAnesthesiology\u003c/em\u003e. 1983;58(2):136\u0026ndash;141. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/00000542-198302000-00006\u003c/span\u003e\u003cspan address=\"10.1097/00000542-198302000-00006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFarge D, De La Coussaye JE, Beloucif S, Fratacci MD, Payen DM. Interactions Between Hemodynamic and Hormonal Modifications During Peep-Induced Antidiuresis and Antinatriuresis. \u003cem\u003eChest\u003c/em\u003e. 1995;107(4):1095\u0026ndash;1100. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1378/chest.107.4.1095\u003c/span\u003e\u003cspan address=\"10.1378/chest.107.4.1095\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRetamal J, Bugedo G, Larsson A, Bruhn A. High PEEP levels are associated with overdistension and tidal recruitment/derecruitment in ARDS patients. \u003cem\u003eActa Anaesthesiologica Scandinavica\u003c/em\u003e. 2015;59(9):1161\u0026ndash;1169. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/aas.12563\u003c/span\u003e\u003cspan address=\"10.1111/aas.12563\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRanieri VM, Giunta F, Suter PM, Slutsky AS. Mechanical ventilation as a mediator of multisystem organ failure in acute respiratory distress syndrome. \u003cem\u003eJAMA\u003c/em\u003e. 2000;284(1):43\u0026ndash;44. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jama.284.1.43\u003c/span\u003e\u003cspan address=\"10.1001/jama.284.1.43\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEvans L, Rhodes A, Alhazzani W, et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2021;47(11):1181\u0026ndash;1247. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-021-06506-y\u003c/span\u003e\u003cspan address=\"10.1007/s00134-021-06506-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePapazian L, Aubron C, Brochard L, et al. Formal guidelines: management of acute respiratory distress syndrome. \u003cem\u003eAnnals of Intensive Care\u003c/em\u003e. 2019;9(1):69. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13613-019-0540-9\u003c/span\u003e\u003cspan address=\"10.1186/s13613-019-0540-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGattinoni L, Coppola S, Cressoni M, Busana M, Rossi S, Chiumello D. COVID-19 Does Not Lead to a \u0026ldquo;Typical\u0026rdquo; Acute Respiratory Distress Syndrome. \u003cem\u003eAm J Respir Crit Care Med\u003c/em\u003e. 2020;201(10):1299\u0026ndash;1300. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1164/rccm.202003-0817LE\u003c/span\u003e\u003cspan address=\"10.1164/rccm.202003-0817LE\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrasselli G, Zangrillo A, Zanella A, et al. Baseline Characteristics and Outcomes of 1591 Patients Infected With SARS-CoV-2 Admitted to ICUs of the Lombardy Region, Italy. \u003cem\u003eJAMA\u003c/em\u003e. 2020;323(16):1574\u0026ndash;1581. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jama.2020.5394\u003c/span\u003e\u003cspan address=\"10.1001/jama.2020.5394\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrasso S, Mirabella L, Murgolo F, et al. Effects of Positive End-Expiratory Pressure in \u0026ldquo;High Compliance\u0026rdquo; Severe Acute Respiratory Syndrome Coronavirus 2 Acute Respiratory Distress Syndrome. \u003cem\u003eCrit Care Med\u003c/em\u003e. 2020;48(12):e1332-e1336. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/CCM.0000000000004640\u003c/span\u003e\u003cspan address=\"10.1097/CCM.0000000000004640\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOttolina D, Zazzeron L, Trevisi L, et al. Acute kidney injury (AKI) in patients with Covid-19 infection is associated with ventilatory management with elevated positive end-expiratory pressure (PEEP). \u003cem\u003eJ Nephrol\u003c/em\u003e. 2022;35(1):99\u0026ndash;111. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s40620-021-01100-3\u003c/span\u003e\u003cspan address=\"10.1007/s40620-021-01100-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBasse P, Morisson L, Barth\u0026eacute;l\u0026eacute;my R, et al. Relationship between positive end-expiratory pressure levels, central venous pressure, systemic inflammation and acute renal failure in critically ill ventilated COVID-19 patients: a monocenter retrospective study in France. \u003cem\u003eAcute Crit Care\u003c/em\u003e. 2023;38(2):172\u0026ndash;181. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4266/acc.2022.01494\u003c/span\u003e\u003cspan address=\"10.4266/acc.2022.01494\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeurton A, Haudebourg L, Simon-Tillaux N, Demoule A, Dres M. Limiting positive end-expiratory pressure to protect renal function in SARS-CoV-2 critically ill patients. \u003cem\u003eJournal of Critical Care\u003c/em\u003e. 2020;59:191\u0026ndash;193. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jcrc.2020.07.008\u003c/span\u003e\u003cspan address=\"10.1016/j.jcrc.2020.07.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eValk CMA, Tsonas AM, Botta M, et al. Association of early positive end-expiratory pressure settings with ventilator-free days in patients with coronavirus disease 2019 acute respiratory distress syndrome: A secondary analysis of the Practice of VENTilation in COVID-19 study. \u003cem\u003eEur J Anaesthesiol\u003c/em\u003e. 2021;38(12):1274\u0026ndash;1283. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/EJA.0000000000001565\u003c/span\u003e\u003cspan address=\"10.1097/EJA.0000000000001565\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCOVID-ICU Group on behalf of the REVA Network and the COVID-ICU Investigators. Clinical characteristics and day-90 outcomes of 4244 critically ill adults with COVID-19: a prospective cohort study. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2021;47(1):60\u0026ndash;73. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-020-06294-x\u003c/span\u003e\u003cspan address=\"10.1007/s00134-020-06294-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhwaja A. KDIGO Clinical Practice Guidelines for Acute Kidney Injury. \u003cem\u003eNephron Clin Pract\u003c/em\u003e. 2012;120(4):c179-c184. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1159/000339789\u003c/span\u003e\u003cspan address=\"10.1159/000339789\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZ\u0026aacute;vada J, Hoste E, Cartin-Ceba R, et al. A comparison of three methods to estimate baseline creatinine for RIFLE classification. \u003cem\u003eNephrol Dial Transplant\u003c/em\u003e. 2010;25(12):3911\u0026ndash;3918. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ndt/gfp766\u003c/span\u003e\u003cspan address=\"10.1093/ndt/gfp766\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePanitchote A, Mehkri O, Hastings A, et al. Factors associated with acute kidney injury in acute respiratory distress syndrome. \u003cem\u003eAnnals of Intensive Care\u003c/em\u003e. 2019;9(1):74. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13613-019-0552-5\u003c/span\u003e\u003cspan address=\"10.1186/s13613-019-0552-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGupta S, Coca SG, Chan L, et al. AKI Treated with Renal Replacement Therapy in Critically Ill Patients with COVID-19. \u003cem\u003eJASN\u003c/em\u003e. 2021;32(1):161\u0026ndash;176. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1681/ASN.2020060897\u003c/span\u003e\u003cspan address=\"10.1681/ASN.2020060897\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGupta S, Hayek SS, Wang W, et al. Factors Associated With Death in Critically Ill Patients With Coronavirus Disease 2019 in the US. \u003cem\u003eJAMA Intern Med\u003c/em\u003e. 2020;180(11):1436\u0026ndash;1447. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jamainternmed.2020.3596\u003c/span\u003e\u003cspan address=\"10.1001/jamainternmed.2020.3596\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGattinoni L, Marini JJ, Pesenti A, Quintel M, Mancebo J, Brochard L. The \u0026ldquo;baby lung\u0026rdquo; became an adult. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2016;42(5):663\u0026ndash;673. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-015-4200-8\u003c/span\u003e\u003cspan address=\"10.1007/s00134-015-4200-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eARDS Network. Ventilation with Lower Tidal Volumes as Compared with Traditional Tidal Volumes for Acute Lung Injury and the Acute Respiratory Distress Syndrome. \u003cem\u003eN Engl J Med\u003c/em\u003e. 2000;342(18):1301\u0026ndash;1308. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1056/NEJM200005043421801\u003c/span\u003e\u003cspan address=\"10.1056/NEJM200005043421801\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSlutsky AS, Ranieri VM. Ventilator-induced lung injury. \u003cem\u003eN Engl J Med\u003c/em\u003e. 2013;369(22):2126\u0026ndash;2136. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1056/NEJMra1208707\u003c/span\u003e\u003cspan address=\"10.1056/NEJMra1208707\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrower RG, Lanken PN, MacIntyre N, et al. Higher versus lower positive end-expiratory pressures in patients with the acute respiratory distress syndrome. \u003cem\u003eN Engl J Med\u003c/em\u003e. 2004;351(4):327\u0026ndash;336. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1056/NEJMoa032193\u003c/span\u003e\u003cspan address=\"10.1056/NEJMoa032193\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMercat A, Richard JCM, Vielle B, et al. Positive End-Expiratory Pressure Setting in Adults With Acute Lung Injury and Acute Respiratory Distress Syndrome: A Randomized Controlled Trial. \u003cem\u003eJAMA\u003c/em\u003e. 2008;299(6):646\u0026ndash;655. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jama.299.6.646\u003c/span\u003e\u003cspan address=\"10.1001/jama.299.6.646\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeade MO, Cook DJ, Guyatt GH, et al. Ventilation Strategy Using Low Tidal Volumes, Recruitment Maneuvers, and High Positive End-Expiratory Pressure for Acute Lung Injury and Acute Respiratory Distress Syndrome: A Randomized Controlled Trial. \u003cem\u003eJAMA\u003c/em\u003e. 2008;299(6):637\u0026ndash;645. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jama.299.6.637\u003c/span\u003e\u003cspan address=\"10.1001/jama.299.6.637\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLumlertgul N, Baker E, Pearson E, et al. Changing epidemiology of acute kidney injury in critically ill patients with COVID-19: a prospective cohort. \u003cem\u003eAnn Intensive Care\u003c/em\u003e. 2022;12(1):118. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13613-022-01094-6\u003c/span\u003e\u003cspan address=\"10.1186/s13613-022-01094-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeite TT, Gomes CAM, Valdivia JMC, Lib\u0026oacute;rio AB. Respiratory parameters and acute kidney injury in acute respiratory distress syndrome: a causal inference study. \u003cem\u003eAnn Transl Med\u003c/em\u003e. 2019;7(23):742. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.21037/atm.2019.11.92\u003c/span\u003e\u003cspan address=\"10.21037/atm.2019.11.92\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLombardi R, Nin N, Pe\u0026ntilde;uelas O, et al. Acute Kidney Injury in Mechanically Ventilated Patients: The Risk Factor Profile Depends on the Timing of Aki Onset. \u003cem\u003eShock\u003c/em\u003e. 2017;48(4):411\u0026ndash;417. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/SHK.0000000000000871\u003c/span\u003e\u003cspan address=\"10.1097/SHK.0000000000000871\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePuybasset L, Cluzel P, Gusman P, Grenier P, Preteux F, Rouby JJ. Regional distribution of gas and tissue in acute respiratory distress syndrome. I. Consequences for lung morphology. CT Scan ARDS Study Group. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2000;26(7):857\u0026ndash;869. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s001340051274\u003c/span\u003e\u003cspan address=\"10.1007/s001340051274\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGattinoni L, Caironi P, Cressoni M, et al. Lung Recruitment in Patients with the Acute Respiratory Distress Syndrome. \u003cem\u003eN Engl J Med\u003c/em\u003e. 2006;354(17):1775\u0026ndash;1786. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1056/NEJMoa052052\u003c/span\u003e\u003cspan address=\"10.1056/NEJMoa052052\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCalfee CS, Delucchi K, Parsons PE, et al. Subphenotypes in acute respiratory distress syndrome: latent class analysis of data from two randomised controlled trials. \u003cem\u003eLancet Respir Med\u003c/em\u003e. 2014;2(8):611\u0026ndash;620. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S2213-2600(14)70097-9\u003c/span\u003e\u003cspan address=\"10.1016/S2213-2600(14)70097-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMekontso Dessap A, Charron C, Devaquet J, et al. Impact of acute hypercapnia and augmented positive end-expiratory pressure on right ventricle function in severe acute respiratory distress syndrome. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2009;35(11):1850\u0026ndash;1858. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-009-1569-2\u003c/span\u003e\u003cspan address=\"10.1007/s00134-009-1569-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGattinoni L, Chiumello D, Caironi P, et al. COVID-19 pneumonia: different respiratory treatments for different phenotypes? \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2020;46(6):1099\u0026ndash;1102. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-020-06033-2\u003c/span\u003e\u003cspan address=\"10.1007/s00134-020-06033-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFogagnolo A, Grasso S, Dres M, et al. Focus on renal blood flow in mechanically ventilated patients with SARS-CoV-2: a prospective pilot study. \u003cem\u003eJ Clin Monit Comput\u003c/em\u003e. 2022;36(1):161\u0026ndash;167. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10877-020-00633-5\u003c/span\u003e\u003cspan address=\"10.1007/s10877-020-00633-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarth\u0026eacute;l\u0026eacute;my R, Beaucot\u0026eacute; V, Bordier R, et al. Haemodynamic impact of positive end-expiratory pressure in SARS-CoV-2 acute respiratory distress syndrome: oxygenation versus oxygen delivery. \u003cem\u003eBr J Anaesth\u003c/em\u003e. 2021;126(2):e70-e72. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.bja.2020.10.026\u003c/span\u003e\u003cspan address=\"10.1016/j.bja.2020.10.026\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBotta M, Tsonas AM, Pillay J, et al. Ventilation management and clinical outcomes in invasively ventilated patients with COVID-19 (PRoVENT-COVID): a national, multicentre, observational cohort study. \u003cem\u003eLancet Respir Med\u003c/em\u003e. 2021;9(2):139\u0026ndash;148. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S2213-2600(20)30459-8\u003c/span\u003e\u003cspan address=\"10.1016/S2213-2600(20)30459-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaudebourg AF, Perier F, Tuffet S, et al. Respiratory Mechanics of COVID-19- versus Non-COVID-19-associated Acute Respiratory Distress Syndrome. \u003cem\u003eAm J Respir Crit Care Med\u003c/em\u003e. 2020;202(2):287\u0026ndash;290. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1164/rccm.202004-1226LE\u003c/span\u003e\u003cspan address=\"10.1164/rccm.202004-1226LE\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMekontso Dessap A, Boissier F, Charron C, et al. Acute cor pulmonale during protective ventilation for acute respiratory distress syndrome: prevalence, predictors, and clinical impact. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2016;42(5):862\u0026ndash;870. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-015-4141-2\u003c/span\u003e\u003cspan address=\"10.1007/s00134-015-4141-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalahuddin N, Sammani M, Hamdan A, et al. Fluid overload is an independent risk factor for acute kidney injury in critically Ill patients: results of a cohort study. \u003cem\u003eBMC Nephrol\u003c/em\u003e. 2017;18(1):45. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12882-017-0460-6\u003c/span\u003e\u003cspan address=\"10.1186/s12882-017-0460-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRezoagli E, McNicholas B, Pham T, Bellani G, Laffey JG. Lung-kidney cross-talk in the critically ill: insights from the Lung Safe study. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2020;46(5):1072\u0026ndash;1073. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00134-020-05962-2\u003c/span\u003e\u003cspan address=\"10.1007/s00134-020-05962-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDoig GS, McIlroy DR. Acute Kidney Injury in Patients With Acute Respiratory Distress Syndrome: The Chicken or the Egg? \u003cem\u003eCrit Care Med\u003c/em\u003e. 2019;47(9):1273\u0026ndash;1274. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/CCM.0000000000003882\u003c/span\u003e\u003cspan address=\"10.1097/CCM.0000000000003882\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuggan M, McCaul CL, McNamara PJ, Engelberts D, Ackerley C, Kavanagh BP. Atelectasis causes vascular leak and lethal right ventricular failure in uninjured rat lungs. \u003cem\u003eAm J Respir Crit Care Med\u003c/em\u003e. 2003;167(12):1633\u0026ndash;1640. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1164/rccm.200210-1215OC\u003c/span\u003e\u003cspan address=\"10.1164/rccm.200210-1215OC\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBellani G, Laffey JG, Pham T, et al. Epidemiology, Patterns of Care, and Mortality for Patients With Acute Respiratory Distress Syndrome in Intensive Care Units in 50 Countries. \u003cem\u003eJAMA\u003c/em\u003e. 2016;315(8):788. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jama.2016.0291\u003c/span\u003e\u003cspan address=\"10.1001/jama.2016.0291\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePickering JW, Endre ZH. Back-Calculating Baseline Creatinine with MDRD Misclassifies Acute Kidney Injury in the Intensive Care Unit. \u003cem\u003eClinical Journal of the American Society of Nephrology\u003c/em\u003e. 2010;5(7):1165\u0026ndash;1173. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2215/CJN.08531109\u003c/span\u003e\u003cspan address=\"10.2215/CJN.08531109\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLombardi R, Nin N, Lorente JA, et al. An Assessment of the Acute Kidney Injury Network Creatinine-Based Criteria in Patients Submitted to Mechanical Ventilation. \u003cem\u003eClinical Journal of the American Society of Nephrology\u003c/em\u003e. 2011;6(7):1547\u0026ndash;1555. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2215/CJN.09531010\u003c/span\u003e\u003cspan address=\"10.2215/CJN.09531010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOrieux A, Boyer A, Dewitte A, Combe C, Rubin S. Insuffisance r\u0026eacute;nale aigu\u0026euml; en soins intensifs-r\u0026eacute;animation et ses cons\u0026eacute;quences: mise au point. \u003cem\u003eN\u0026eacute;phrologie \u0026amp; Th\u0026eacute;rapeutique\u003c/em\u003e. 2022;18(1):7\u0026ndash;20. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.nephro.2021.07.324\u003c/span\u003e\u003cspan address=\"10.1016/j.nephro.2021.07.324\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCollaborators\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCOVID-ICU Group on behalf of the REVA Network and the COVID-ICU Investigators:\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlain Mercat, Pierre Asfar, Fran\u0026ccedil;ois Beloncle, Julien Demiselle, T\u0026agrave;i Pham, Arthur Pavot, Xavier Monnet, Christian Richard, Alexandre Demoule, Martin Dres, Julien Mayaux, Alexandra Beurton, C\u0026eacute;dric Daubin, Richard Descamps, Aur\u0026eacute;lie Joret, Damien Du Cheyron, Fr\u0026eacute;d\u0026eacute;ric Pene, Jean-Daniel Chiche, Mathieu Jozwiak, Paul Jaubert, Guillaume Voiriot, Muriel Fartoukh, Marion Teulier, Clarisse Blayau, Erwen L'Her, C\u0026eacute;cile Aubron, Laetitia Bodenes, Nicolas Ferriere, Johann Auchabie, Anthony Le Meur, Sylvain Pignal, Thierry Mazzoni, Jean-Pierre Quenot, Pascal Andreu, Jean-Baptiste Roudau, Marie Labruy\u0026egrave;re, Saad Nseir, S\u0026eacute;bastien Preau, Julien Poissy, Daniel Mathieu, Sarah Benhamida, R\u0026eacute;mi Paulet, Nicolas Roucaud, Martial Thyrault, Florence Daviet, Sami Hraiech, Gabriel Parzy, Aude Sylvestre, S\u0026eacute;bastien Jochmans, Anne-Laure Bouilland, Mehran Monchi, Marc Danguy des D\u0026eacute;serts, Quentin Mathais, Gwendoline Rager, Pierre Pasquier, Jean Reignier, Am\u0026eacute;lie Seguin, Charlotte Garret, Emmanuel Canet, Jean Dellamonica, Cl\u0026eacute;ment Saccheri, Romain Lombardi, Yanis Kouchit, Sophie Jacquier, Armelle Mathonnet, Mai-Ahn Nay, Isabelle Runge, Fr\u0026eacute;d\u0026eacute;ric Martino, Laure Flurin, Am\u0026eacute;lie Rolle, Michel Carles, R\u0026eacute;mi Coudroy, Arnaud W Thille, Jean-Pierre Frat, Maeva Rodriguez, Pascal Beuret, Audrey Tientcheu, Arthur Vincent, Florian Michelin, Fabienne Tamion, Doroth\u0026eacute;e Carpentier, D\u0026eacute;borah Boyer, Christophe Girault, Val\u0026eacute;rie Gissot, St\u0026eacute;phan Ehrmann, Charlotte Salmon Gandonniere, Djlali Elaroussi, Agathe Delbove, Yannick Fedun, Julien Huntzinger, Eddy Lebas, Gr\u0026acirc;ce Kisoka, C\u0026eacute;line Gr\u0026eacute;goire, Stella Marchetta, Bernard Lambermont, Laurent Argaud, Thomas Baudry, Pierre-Jean Bertrand, Auguste Dargent, Christophe Guitton, Nicolas Chudeau, Micka\u0026euml;l Landais, C\u0026eacute;dric Darreau, Alexis Ferr\u0026eacute;, Antoine Gros, Guillaume Lacave, Fabrice Bruneel, Mathilde Neuville, J\u0026eacute;r\u0026ocirc;me Devaquet, Guillaume Tachon, Richard Gallot, Riad Chelha, Arnaud Galbois, Anne Jallot, Ludivine Chalumeau Lemoine, Khaldoun Kuteifan, Valentin Pointurier, Louise-Marie Jandeaux, Joy Mootien, Charles Damoisel, Benjamin Sztrymf, Matthieu Schmidt, Alain Combes, Juliette Chommeloux, Charles Edouard Luyt, Fr\u0026eacute;d\u0026eacute;rique Schortgen, Leon Rusel, Camille Jung, Florent Gobert, Damien Vimpere, Lionel Lamhaut, Bertrand Sauneuf, Liliane Charrrier, Julien Calus, Isabelle Desmeules, Beno\u0026icirc;t Painvin, Jean-Marc Tadie, Vincent Castelain, Baptiste Michard, Jean-Etienne Herbrecht, Mathieu Baldacini, Nicolas Weiss, Sophie Demeret, Cl\u0026eacute;mence Marois, Benjamin Rohaut, Pierre-Henri Moury, Anne-Charlotte Savida, Emmanuel Couadau, Mathieu S\u0026eacute;rie, Nica Alexandru, C\u0026eacute;dric Bruel, Candice Fontaine, Sonia Garrigou, Juliette Courtiade Mahler, Maxime Leclerc, Michel Ramakers, Pierre Gar\u0026ccedil;on, Nicole Massou, Ly Van Vong, Juliane Sen, Nolwenn Lucas, Franck Chemouni, Annabelle Stoclin, Alexandre Avenel, Henri Faure, Ang\u0026eacute;lie Gentilhomme, Sylvie Ricome, Paul Abraham, C\u0026eacute;line Monard, Julien Textoris, Thomas Rimmele, Florent Montini, Gabriel Lejour, Thierry Lazard, Isabelle Etienney, Younes Kerroumi, Claire Dupuis, Marine Bereiziat, Elisabeth Coupez, Fran\u0026ccedil;ois Thouy, Cl\u0026eacute;ment Hofmann, Nicolas Donat, Anne Chrisment, Rose-Marie Blot, Antoine Kimmoun, Audrey Jacquot, Matthieu Mattei, Bruno Levy, Ramin Ravan, Lo\u0026iuml;c Dopeux, Jean-Mathias Liteaudon, Delphine Roux, Brice Rey, Radu Anghel, Deborah Schenesse, Vincent Gevrey, Jermy Castanera, Philippe Petua, Benjamin Madeux, Otto Hartman, Michael Piagnerelli, Anne Joosten, Cinderella Noel, Patrick Biston, Thibaut Noel, Gurvan L E Bouar, Messabi Boukhanza, Elsa Demarest, Marie-France Bajolet, Nathana\u0026euml;l Charrier, Audrey Quenet, C\u0026eacute;cile Zylberfajn, Nicolas Dufour, Bruno M\u0026eacute;garbane, S\u0026eacute;bastian Voicu, Nicolas Deye, Isabelle Malissin, Fran\u0026ccedil;ois Legay, Matthieu Debarre, Nicolas Barbarot, Pierre Fillatre, Bertrand Delord, Thomas Laterrade, Tahar Saghi, Wilfried Pujol, Pierre Julien Cungi, Pierre Esnault, Mickael Cardinale, Vivien Hong Tuan Ha, Gr\u0026eacute;gory Fleury, Marie-Ange Brou, Daniel Zafmahazo, David Tran-Van, Patrick Avargues, Lisa Carenco, Nicolas Robin, Alexandre Ouali, Lucie Houdou, Christophe Le Terrier, No\u0026eacute;mie Suh, Steve Primmaz, J\u0026eacute;rome Pugin, Emmanuel Weiss, Tobias Gauss, Jean-Denis Moyer, Catherine Paugam Burtz, B\u0026eacute;atrice La Combe, Rolland Smonig, Jade Violleau, Pauline Cailliez, Jonathan Chelly, Antoine Marchalot, C\u0026eacute;cile Saladin, Christelle Bigot, Pierre-Marie Fayolle, Jules Fats\u0026eacute;as, Amr Ibrahim, Dabor Resiere, Rabih Hage, Cl\u0026eacute;mentine Cholet, Marie Cantier, Pierre Trouiler, Philippe Montravers, Brice Lortat-Jacob, Sebastien Tanaka, Alexy Tran Dinh, Jacques Duranteau, Anatole Harrois, Guillaume Dubreuil, Marie Werner, Anne Godier, Sophie Hamada, Diane Zlotnik, H\u0026eacute;l\u0026egrave;ne Nougue, Armand Mekontso-Dessap, Guillaume Carteaux, Keyvan Razazi, Nicolas de Prost, Nicolas Mongardon, Nicolas Mongardon, Meriam Lamraoui, Claire Alessandri, Quentin de Roux, Charles de Roquetaillade, Benjamin G Chousterman, Alexandre Mebazaa, Etienne Gayat, Marc Garnier, Emmanuel Pardo, Lea Satre-Buisson, Christophe Gutton, Elise Yvin, Cl\u0026eacute;mence Marcault, Elie Azoulay, Michael Darmon, Hafid Ait Oufella, Geofroy Hariri, Tomas Urbina, Sandie Mazerand, Nicholas Heming, Francesca Santi, Pierre Moine, Djillali Annane, Adrien Bougl\u0026eacute;, Edris Omar, Aymeric Lancelot, Emmanuelle Begot, Ga\u0026eacute;tan Plantefeve, Damien Contou, Herv\u0026eacute; Mentec, Olivier Pajot, Stanislas Faguer, Olivier Cointault, Laurence Lavayssiere, Marie-B\u0026eacute;atrice Nogier, Matthieu Jamme, Claire Pichereau, Jan Hayon, Herv\u0026eacute; Outin, Fran\u0026ccedil;ois D\u0026eacute;pret, Maxime Coutrot, Mait\u0026eacute; Chaussard, Lucie Guillemet, Pierre Gofn, Romain Thouny, Julien Guntz, Laurent Jadot, Romain Persichini, Vanessa Jean-Michel, Hugues Georges, Thomas Caulier, Ga\u0026euml;l Pradel, Marie-H\u0026eacute;l\u0026egrave;ne Hausermann, Thi My Hue Nguyen-Valat, Michel Boudinaud, Emmanuel Vivier, Sylv\u0026egrave;ne Rosseli, Ga\u0026euml;l Bourdin, Christian Pommier, Marc Vinclair, Simon Poignant, Sandrine Mons, Wulfran Bougouin, Franklin Bruna, Quentin Maestraggi, Christian Roth, Laurent Bitker, Fran\u0026ccedil;ois Dhelft, Justine Bonnet-Chateau, Mathilde Filippelli, Tristan Morichau-Beauchant, St\u0026eacute;phane Thierry, Charlotte Le Roy, M\u0026eacute;lanie Saint Jouan, Bruno Goncalves, Aur\u0026eacute;lien Mazeraud, Matthieu Daniel, Tarek Sharshar, Cyril Cadoz, Rostane Gaci, S\u0026eacute;bastien Gette, Guillaune Louis, Sophie-Caroline Sacleux, Marie-Am\u0026eacute;lie Ordan, Aur\u0026eacute;lie Cravoisy, Marie Conrad, Guilhem Courte, S\u0026eacute;bastien Gibot, Youn\u0026egrave;s Benzidi, Claudia Casella, Laurent Serpin, Jean-Lou Setti, Marie-Catherine Besse, Anna Bourreau, J\u0026eacute;r\u0026ocirc;me Pillot, Caroline Rivera, Camille Vinclair, Marie-Aline Robaux, Chlo\u0026eacute; Achino, Marie-Charlotte Delignette, Tessa Mazard, Fr\u0026eacute;d\u0026eacute;ric Aubrun, Bruno Bouchet, Aur\u0026eacute;lien Fr\u0026eacute;rou, Laura Muller, Charlotte Quentin, Samuel Degoul, Xavier Stihle, Claude Sumian, Nicoletta Bergero, Bernard Lanaspre, Herv\u0026eacute; Quintard, Eve Marie Maiziere, Pierre-Yves Egreteau, Guillaume Leloup, Florin Berteau, Marjolaine Cottrel, Marie Bouteloup, Matthieu Jeannot, Quentin Blanc, Julien Saison, Isabelle Geneau, Romaric Grenot, Abdel Ouchike, Pascal Hazera, Anne-Lyse Masse, Suela Demiri, Corinne Vezinet, Elodie Baron, Deborah Benchetrit, Antoine Monsel, Gr\u0026eacute;goire Trebbia, Emmanuelle Schaack, Rapha\u0026euml;l Lepecq, Mathieu Bobet, Christophe Vinsonneau, Thibault Dekeyser, Quentin Delforge, Imen Rahmani, B\u0026eacute;reng\u0026egrave;re Vivet, Jonathan Paillot, Lucie Hierle, Claire Chaignat, Sarah Valette, Beno\u0026iuml;t Her, Jennifer Brunet, Mathieu Page, Fabienne Boiste, Anthony Collin, Florent Bavozet, Aude Garin, Mohamed Dlala, Kais Mhamdi, Bassem Beilouny, Alexandra Lavalard, Severine Perez, Benoit Veber, Pierre-Gildas Guitard, Philippe Gouin, Anna Lamacz, Fabienne Plouvier, Bertrand P Delaborde, A\u0026iuml;ssa Kherchache, Amina Chaalal, Jean-Damien Ricard, Marc Amouretti, Santiago Freita-Ramos, Damien Roux, Jean-Michel Constantin, Mona Assef, Marine Lecore, Agathe Selves, Florian Prevost, Christian Lamer, Ruiying Shi, Lyes Knani, S\u0026eacute;bastien Pili Floury, Lucie Vettoretti, Michael Levy, Lucile Marsac, St\u0026eacute;phane Dauger, Sophie Guilmin-Cr\u0026eacute;pon, Hadrien Winiszewski, Gael Piton, Thibaud Soumagne, Gilles Capellier, Jean-Baptiste Putegnat, Fr\u0026eacute;d\u0026eacute;rique Bayle, Maya Perrou, Ghyslaine Thao, Guillaume G\u0026eacute;ri, Cyril Charron, Xavier Repess\u0026eacute;, Antoine Vieillard-Baron, Mathieu Guilbart, Pierre-Alexandre Roger, S\u0026eacute;bastien Hinard, Pierre-Yves Macq, Kevin Chaulier, Sylvie Goutte, Patrick Chillet, Ana\u0026iuml;s Pitta, Barbara Darjent, Amandine Bruneau, Sigismond Lasocki, Maxime Leger, Soizic Gergaud, Pierre Lemarie, Nicolas Terzi, Carole Schwebel, Ana\u0026iuml;s Dartevel, Louis-Marie Galerneau, Jean-Luc Diehl, Caroline Hauw-Berlemont, Nicolas P\u0026eacute;ron, Emmanuel Gu\u0026eacute;rot, Abolfazl Mohebbi Amoli, Michel Benhamou, Jean-Pierre Deyme, Olivier Andremont, Diane Lena, Julien Cady, Arnaud Causeret, Arnaud De La Chapelle, Christophe Cracco, St\u0026eacute;phane Rouleau, David Schnell, Camille Foucault, C\u0026eacute;cile Lory, Thibault Chapelle, Vincent Bruckert, Julie Garcia, Abdlazize Sahraoui, Nathalie Abbosh, Caroline Bornstain, Pierre Pernet, Florent Poirson, Ahmed Pasem, Philippe Karoubi, Virginie Poupinel, Caroline Gauthier, Fran\u0026ccedil;ois Bouniol, Philippe Feuchere, Florent Bavozet, Anne Heron, Serge Carreira, Malo Emery, Anne Sophie Le Floch, Luana Giovannangeli, Nicolas Herzog, Christophe Giacardi, Thibaut Baudic, Chlo\u0026eacute; Thill, Said Lebbah, Jessica Palmyre, Florence Tubach, David Hajage, Nicolas Bonnet, Nathan Ebstein, St\u0026eacute;phane Gaudry, Yves Cohen, Julie Noublanche, Olivier Lesieur, Arnaud S\u0026eacute;ment, Isabel Roca-Cerezo, Michel Pascal, Nesrine Sma, Gwenha\u0026euml;l Colin, Jean-Claude Lacherade, Gauthier Bionz, Natacha Maquigneau, Pierre Bouzat, Michel Durand, Marie-Christine H\u0026eacute;rault, Jean-Francois Payen\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e: Characteristics at admission\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"710\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal population\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWith AKI\u0026nbsp;\u003cbr\u003e\u0026nbsp;(n = 510)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWithout AKI\u0026nbsp;\u003cbr\u003e\u0026nbsp;(n = 556)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e61 \u0026plusmn; 12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e62 \u0026plusmn; 12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e61 \u0026plusmn; 12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.307\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003eMale sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e778 (73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e367 (73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e411 (74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.623\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e29 \u0026plusmn; 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e29 \u0026plusmn; 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e29 \u0026plusmn; 6\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.827\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003eSAPS II\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e40 \u0026plusmn; 15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e41 \u0026plusmn; 15\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e39 \u0026plusmn; 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003eNo antecedents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e215 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e92 (18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e123 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003eActive smoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e28 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e14 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e14 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.969\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003eRespiratory history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e201 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e106 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e95 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;COPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e53 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e27 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e26 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Asthma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e76 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e40 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e36 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.454\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003eCardiovascular history\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e586 (55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e288 (56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e298 (54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.379\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e454 (43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e230 (45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e224 (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.120\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Ischemic heart disease\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e94 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e42 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e52 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.587\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Congestive heart failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e22 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e14 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e8 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.203\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e248 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e134 (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e114 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003eImmunodepression \u003csup\u003e(a)\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e91 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e49 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e42 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.276\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003eBacterial co-infection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e62 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e28 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e34 (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.761\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 710px;\"\u003e\n \u003cp\u003eThe data are presented in numbers and percentages (%) or as mean \u0026plusmn; standard deviation.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e includes: long-term immunosuppressive medications and/or corticosteroids, HIV infection, solid organ transplantation, active solid or hematological cancer\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eAKI\u003c/em\u003e acute kidney injury failure, \u003cem\u003eBMI\u003c/em\u003e body mass index, \u003cem\u003eCOPD\u003c/em\u003e chronic obstructive pulmonary disease, \u003cem\u003eSAPS II\u003c/em\u003e simplified acute physiology score II\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Prognosis and severity of acute kidney injury\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"716\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal population\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWith AKI\u0026nbsp;\u003cbr\u003e\u0026nbsp;(n = 510)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWithout AKI\u0026nbsp;\u003cbr\u003e\u0026nbsp;(n = 556)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eInitial severity of ARDS at day 1\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Mild\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e294 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e135 (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e159 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e460 (45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e211 (43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e249 (47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Severe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e277 (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e150 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e127 (24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cem\u003eKidney function:\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eBasal creatinine\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e54 \u0026plusmn; 15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e53 \u0026plusmn; 17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e55 \u0026plusmn; 14\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eSeverity of AKI from day 2 to 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;KDIGO 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e314 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e314 (61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;KDIGO 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e98 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e98 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;KDIGO 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e98 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e98 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eRRT from day 2 to 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e54 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e54 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cem\u003ePrognosis:\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eMortality at 28 day\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e237 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e140 (28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e97 (18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eVentilator-free days\u003cem\u003e\u003csup\u003ed\u003c/sup\u003e\u003c/em\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e9 \u0026plusmn; 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e7 \u0026plusmn; 8\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e11 \u0026plusmn; 9\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 245px;\"\u003e\n \u003cp\u003eICU length of stay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e26 \u0026plusmn; 18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e29 \u0026plusmn; 18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e23 \u0026plusmn; 18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 716px;\"\u003e\n \u003cp\u003eData are presented in numbers and percentages (%) or mean \u0026plusmn; standard deviation.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cbr\u003e\u0026nbsp;a\u003c/sup\u003e according to Berlin criteria\u003cbr\u003e\u003csup\u003eb\u003c/sup\u003e calculated using the formula : \u0026nbsp;\u003cbr\u003e\u003csup\u003ec\u003c/sup\u003e 31 lost to follow-up not included in this table\u003cbr\u003e\u003csup\u003ed\u003c/sup\u003e time between date of intubation and last successful extubation\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eAKI\u003c/em\u003e acute kidney injury, \u003cem\u003eARDS\u003c/em\u003e acute respiratory distress syndrome, \u003cem\u003eICU\u003c/em\u003e Intensive Care Unit,\u003cem\u003e\u0026nbsp;MV\u003c/em\u003e mechanical ventilation,\u003cem\u003e\u0026nbsp;RRT\u003c/em\u003e renal replacement therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Mean respiratory and hemodynamic parameters between day 1 - day 3\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"109%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWith AKI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWithout AKI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cem\u003eRespiratory parameters\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003ePEEP, cmH\u003csub\u003e2\u003c/sub\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e11.4 \u0026plusmn; 2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e10.8 \u0026plusmn; 2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003eTidal volume, ml/kg of IBW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e6.4 \u0026plusmn; 1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e6.3 \u0026plusmn; 0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003ePlateau pressure, cmH\u003csub\u003e2\u003c/sub\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e24.4 \u0026plusmn; 4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e23.9 \u0026plusmn; 3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003eDriving pressure, cmH\u003csub\u003e2\u003c/sub\u003e0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e13.0 \u0026plusmn; 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e12.6 \u0026plusmn; 3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003eStatic compliance, ml/cmH\u003csub\u003e2\u003c/sub\u003e0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e36.4 \u0026plusmn; 15.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e36.8 \u0026plusmn; 17.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.663\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cem\u003eBlood gases\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003ePaO\u003csub\u003e2\u003c/sub\u003e / FiO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e175 \u0026plusmn; 65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e180 \u0026plusmn; 66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003epH\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e7.39 \u0026plusmn; 0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e7.40 \u0026plusmn; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003ePaCO\u003csub\u003e2\u003c/sub\u003e, mmHg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e45.0 \u0026plusmn; 10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e44.2 \u0026plusmn; 8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003eBicarbonates, mmol/l\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e26.3 \u0026plusmn; 3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e26.9 \u0026plusmn; 3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.003\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003eLactate, mmol/l\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e1.6 \u0026plusmn; 0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e1.4 \u0026plusmn; 0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cem\u003eRescue therapy\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003eNumber of days in PP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e0.8 \u0026plusmn; 0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e0.7 \u0026plusmn; 0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.386\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003eNumber of days NO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e0.1 \u0026plusmn; 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e0.1 \u0026plusmn; 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.740\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cem\u003eHemodynamic parameters\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003eNumber of days vasopressors\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e1.8 \u0026plusmn; 1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e1.6 \u0026plusmn; 1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003eRV dysfunction over 3 days, N (%)\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e22 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e13 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0.102\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eData are presented as mean \u0026plusmn; standard deviation or numbers and percentages (%).\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e calculated with driving pressure = plateau pressure - total PEEP\u0026nbsp;\u003cbr\u003e\u003csup\u003eb\u003c/sup\u003e calculated with static compliance = tidal volume / driving pressure\u003cbr\u003e\u003csup\u003ec\u003c/sup\u003e a Student\u0026apos;s t test has been performed here\u003cbr\u003e\u003csup\u003ed\u0026nbsp;\u003c/sup\u003eif trans-thoracic ultrasound was performed\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eAKI\u003c/em\u003e acute kidney injury, \u003cem\u003ePEEP\u003c/em\u003e positive expiratory pressure, \u003cem\u003eIBW\u003c/em\u003e ideal body weight, \u003cem\u003ePaO\u003csub\u003e2\u003c/sub\u003e/FiO\u003csub\u003e2\u003c/sub\u003e\u003c/em\u003e arterial partial pressure of oxygen on fraction inspired in oxygen, \u003cem\u003ePaCO\u003csub\u003e2\u003c/sub\u003e\u003c/em\u003e arterial partial pressure of carbon dioxide, \u003cem\u003ePP\u003c/em\u003e prone position, \u003cem\u003eNO\u003c/em\u003e inhaled nitric oxide, \u003cem\u003eRV\u003c/em\u003e right ventricle\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":false,"email":"","identity":"journal-of-intensive-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Journal of Intensive Care","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false},"keywords":"acute kidney injury, positive end-expiratory pressure, mechanical ventilation, COVID-19, acute respiratory distress syndrome","lastPublishedDoi":"10.21203/rs.3.rs-6880811/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6880811/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAcute Kidney Injury (AKI) is common in patients admitted to intensive care unit (ICU) for severe SARS-CoV-2 pneumonia and is associated with a worse prognosis. Mechanical ventilation has been identified as a risk factor for renal damage in COVID-19. However, few studies have examined the specific ventilatory settings involved. We hypothesized that positive end-expiratory pressure (PEEP) may contribute to the onset of AKI. Our objective was to assess the association between higher PEEP levels and the occurrence of AKI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted an ancillary analysis of the international, prospective, multicenter COVID-ICU study, which included 4244 COVID-19 ICU patients across 149 intensive care units. For our study, only patients who underwent mechanical ventilation for at least 48 hours and had normal renal function before intubation were included. AKI was defined according to Kidney Disease Improving Global Outcome (KDIGO) criteria. A multivariate logistic regression model was used to evaluate the association between PEEP levels and the development of AKI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 1,066 patients were included in the analysis. Among them, 510 (48%) developed AKI within five days of intubation. Mortality at 28 days was higher in patients with AKI (28% vs. 18%, p \u0026lt; 0.001) compared to those without. After adjusting for confounding factors, higher PEEP levels during the first three days of mechanical ventilation were independently associated with AKI (odds ratio [OR] 1.09; 95% confidence interval [95% CI 1.04–1.15]). A PEEP level exceeding 15 cmH₂O was strongly linked to an increased risk of AKI (OR 2.77; 95% CI [1.31–6.24]). Additionally, vasopressor use and elevated lactate levels were associated with renal impairment. AKI was significantly related to 28-day mortality, whereas PEEP levels were not.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWithin five days of intubation in COVID-19 ARDS patients, higher PEEP levels were independently associated with an increased risk of AKI. While AKI was linked to higher mortality, PEEP level was not.\u003c/p\u003e","manuscriptTitle":"PEEP-AKI-COVID ICU: Effect of Positive End-Expiratory Pressure on Acute Kidney Injury Development in Patients with COVID-19-Associated Acute Respiratory Distress Syndrome: An Ancillary Analysis of the COVID-ICU Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-18 09:21:25","doi":"10.21203/rs.3.rs-6880811/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-24T00:01:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-23T16:15:44+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-20T11:58:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"115731054165241675199212209581483479098","date":"2025-06-19T09:02:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-18T07:31:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"42629701712851003997347015604737727266","date":"2025-06-17T06:53:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"272142736128556476667498579497066151903","date":"2025-06-17T06:31:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"296066515226113031233633524814963336850","date":"2025-06-16T22:27:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-15T23:02:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-13T07:43:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-13T07:42:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Intensive Care","date":"2025-06-12T13:21:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":false,"email":"","identity":"journal-of-intensive-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Journal of Intensive Care","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"17485db1-05a1-435d-a827-6914f2c50ed1","owner":[],"postedDate":"June 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-10-09T05:38:56+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-18 09:21:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6880811","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6880811","identity":"rs-6880811","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}