scholarly journals A Multimodal Approach for the Risk Prediction of Intensive Care and Mortality in Patients with COVID-19

Diagnostics ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 56
Author(s):  
Vasileios C. Pezoulas ◽  
Konstantina D. Kourou ◽  
Costas Papaloukas ◽  
Vassiliki Triantafyllia ◽  
Vicky Lampropoulou ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care ◽  
Biological Markers ◽  
Lymphocyte Count ◽  
Dynamic Bayesian Networks ◽  
Gradient Boosting ◽  
Multimodal Approach ◽  
Icu Admission ◽  
Explainable Ai ◽  
Scoring Index

Background: Although several studies have been launched towards the prediction of risk factors for mortality and admission in the intensive care unit (ICU) in COVID-19, none of them focuses on the development of explainable AI models to define an ICU scoring index using dynamically associated biological markers. Methods: We propose a multimodal approach which combines explainable AI models with dynamic modeling methods to shed light into the clinical features of COVID-19. Dynamic Bayesian networks were used to seek associations among cytokines across four time intervals after hospitalization. Explainable gradient boosting trees were trained to predict the risk for ICU admission and mortality towards the development of an ICU scoring index. Results: Our results highlight LDH, IL-6, IL-8, Cr, number of monocytes, lymphocyte count, TNF as risk predictors for ICU admission and survival along with LDH, age, CRP, Cr, WBC, lymphocyte count for mortality in the ICU, with prediction accuracy 0.79 and 0.81, respectively. These risk factors were combined with dynamically associated biological markers to develop an ICU scoring index with accuracy 0.9. Conclusions: to our knowledge, this is the first multimodal and explainable AI model which quantifies the risk of intensive care with accuracy up to 0.9 across multiple timepoints.

Risk Factors Associated With Resistance to Ciprofloxacin in Clinical Bacterial Isolates From Intensive Care Unit Patients

2007 ◽  
Vol 28 (3) ◽  
pp. 331-336 ◽  
Author(s):  
Phillip D. Levin ◽  
Robert A. Fowler ◽  
Cameron Guest ◽  
William J. Sibbald ◽  
Alex Kiss ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Prior Treatment ◽  
Bacterial Isolates ◽  
Icu Patients ◽  
Gram Negative ◽  
Factors Associated ◽  
Icu Admission ◽  
Ciprofloxacin Resistance

Objective.To determine risk factors and outcomes associated with ciprofloxacin resistance in clinical bacterial isolates from intensive care unit (ICU) patients.Design.Prospective cohort study.Setting.Twenty-bed medical-surgical ICU in a Canadian tertiary care teaching hospital.Patients.All patients admitted to the ICU with a stay of at least 72 hours between January 1 and December 31, 2003.Methods.Prospective surveillance to determine patient comorbidities, use of medical devices, nosocomial infections, use of antimicrobials, and outcomes. Characteristics of patients with a ciprofloxacin-resistant gram-negative bacterial organism were compared with characteristics of patients without these pathogens.Results.Ciprofloxacin-resistant organisms were recovered from 20 (6%) of 338 ICU patients, representing 38 (21%) of 178 nonduplicate isolates of gram-negative bacilli. Forty-nine percent ofPseudomonas aeruginosaisolates and 29% ofEscherichia coliisolates were resistant to ciprofloxacin. In a multivariate analysis, independent risk factors associated with the recovery of a ciprofloxacin-resistant organism included duration of prior treatment with ciprofloxacin (relative risk [RR], 1.15 per day [95% confidence interval {CI}, 1.08-1.23];P< .001), duration of prior treatment with levofloxacin (RR, 1.39 per day [95% CI, 1.01-1.91];P= .04), and length of hospital stay prior to ICU admission (RR, 1.02 per day [95% CI, 1.01-1.03];P= .005). Neither ICU mortality (15% of patients with a ciprofloxacin-resistant isolate vs 23% of patients with a ciprofloxacin-susceptible isolate;P= .58 ) nor in-hospital mortality (30% vs 34%;P= .81 ) were statistically significantly associated with ciprofloxacin resistance.Conclusions.ICU patients are at risk of developing infections due to ciprofloxacin-resistant organisms. Variables associated with ciprofloxacin resistance include prior use of fluoroquinolones and duration of hospitalization prior to ICU admission. Recognition of these risk factors may influence antibiotic treatment decisions.

scholarly journals Staphylococcus aureusNasal Colonization and Subsequent Infection in Intensive Care Unit Patients: Does Methicillin Resistance Matter?

2010 ◽  
Vol 31 (6) ◽  
pp. 584-591 ◽  
Author(s):  
Hitoshi Honda ◽  
Melissa J. Krauss ◽  
Craig M. Coopersmith ◽  
Marin H. Kollef ◽  
Amy M. Richmond ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Confidence Interval ◽  
Methicillin Resistance ◽  
Hazard Ratio ◽  
Adjusted Hazard Ratio ◽  
Patient Specific ◽  
Icu Patients ◽  
Icu Admission

Background.Staphylococcus aureusis an important cause of infection in intensive care unit (ICU) patients. Colonization with methicillin-resistantS. aureus(MRSA) is a risk factor for subsequentS. aureusinfection. However, MRSA-colonized patients may have more comorbidities than methicillin-susceptibleS. aureus(MSSA)-colonized or noncolonized patients and therefore may be more susceptible to infection on that basis.Objective.To determine whether MRSA-colonized patients who are admitted to medical and surgical ICUs are more likely to develop anyS. aureusinfection in the ICU, compared with patients colonized with MSSA or not colonized withS. aureus,independent of predisposing patient risk factors.Design.Prospective cohort study.Setting.A 24-bed surgical ICU and a 19-bed medical ICU of a 1,252-bed, academic hospital.Patients.A total of 9,523 patients for whom nasal swab samples were cultured forS. aureusat ICU admission during the period from December 2002 through August 2007.Methods.Patients in the ICU for more than 48 hours were examined for an ICU-acquired S.aureusinfection, defined as development ofS. aureusinfection more than 48 hours after ICU admission.Results.S. aureuscolonization was present at admission for 1,433 (27.8%) of 5,161 patients (674 [47.0%] with MRSA and 759 [53.0%] with MSSA). An ICU-acquiredS. aureusinfection developed in 113 (2.19%) patients, of whom 75 (66.4%) had an infection due to MRSA. Risk factors associated with an ICU-acquiredS. aureusinfection included MRSA colonization at admission (adjusted hazard ratio, 4.70 [95% confidence interval, 3.07-7.21]) and MSSA colonization at admission (adjusted hazard ratio, 2.47 [95% confidence interval, 1.52-4.01]).Conclusion.ICU patients colonized with S.aureuswere at greater risk of developing aS. aureusinfection in the ICU. Even after adjusting for patient-specific risk factors, MRSA-colonized patients were more likely to developS. aureusinfection, compared with MSSA-colonized or noncolonized patients.

scholarly journals COVID-19 in Multiple Myeloma Patients: Frequencies and Risk Factors for Hospitalization, Ventilatory Support, Intensive Care Admission and Mortality -Cooperative Registry from Grupo Brasileiro De Mieloma Multiplo (GBRAM)

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 4104-4104
Author(s):  
Marcia Garnica ◽  
Edvan De Queiroz Crusoe ◽  
Glaciano Ribeiro ◽  
Rosane Bittencourt ◽  
Roberto José Pessoa Magalhães ◽  
...  
Keyword(s):  
Risk Factors ◽  
Multiple Myeloma ◽  
Intensive Care ◽  
High Frequency ◽  
Respiratory Symptoms ◽  
Performance Status ◽  
Ventilatory Support ◽  
Case Series ◽  
Ecog Performance Status ◽  
Icu Admission

Abstract Patients with multiple myeloma (MM) have an increased risk for severe infections due to both the disease and anti-myeloma therapies. During the COVID-19 pandemic, case series of MM patients have demonstrated a poor outcome in those who required hospitalization due to COVID-19, and there are few data regarding those managed out of hospitals or risk factors for hospitalization. In Brazil, where the scenario is of restricted resources to treat MM patients and large numbers of COVID-19 cases and related death, the outcome can be even worse. Objective: To assess risk factors and outcomes of COVID-19 in Brazilian patients with MM. This retrospective case series investigated 81 MM patients with documented COVID-19, managed in and out-hospital, from 8 states, representing 4 of 5 regions in Brazil. This study has been conducted by "Grupo Brasileiro de Mieloma" (GBRAM), and the present analyses included cases from April 2020 to July 2021. Clinical features and risk factors were analyzed with the severity of COVID-19 and outcomes (hospital admissions, intensive care unit (ICU) admission, ventilatory support, and death). The frequency of MM treatment modification due to COVID-19 was also accessed. There were 81 MM patients (male 50%; median age 63 years; and ISS III at diagnosis 25%) diagnosed with COVID-19. At least one comorbidity was present in 47 (58%) patients: most frequently hypertension and diabetes (56% and 27%). Twenty-eight (35%) patients had more than one comorbidity. At COVID episode, 21 (26%) patients had an active disease or progression disease, and 40% received at least two prior lines of treatment. COVID-19 management required hospitalization in 49 (61%), ventilatory support in 30 (40%) and ICU in 28 (35%). Hospitalization was associated with age (p=0.008), presence of comorbidity (p=0.02), hypertension (p=0.02), presence of fever (p=0.005) and low respiratory symptoms (p=0.003). Ventilatory support was more frequent in patients with cardiac disease (p=0.05), receiving immunomodulatory (p=0.03), or monoclonal drugs (p=0.006). Patients receiving corticosteroids (p=0.02), immunomodulatory (p=0.06), or monoclonal drugs (p=0.06) in MM treatment had a higher frequency of ICU admission. By adjusted multivariate analysis, age, the clinical presentation with fever and low respiratory symptoms (p&lt;0.001, p=0.05 and p=0.001, respectively) were independent associated with hospitalization; low respiratory symptoms and MM therapy including monoclonal drugs (p=0.07 and p=0.02) were associated with ventilatory support; therapy with corticosteroids and immunomodulatory drugs (p=0.019 and p=0.05) were associated with ICU admission. Overall mortality was 29%. Mortality rates were 47%, 68%, and 77% in hospitalized, ventilatory support, and ICU patients, respectively. By univariate analysis, age, ECOG performance status, and MM therapy including corticosteroids, were associated with increased mortality. By multivariate model, only ECOG performance status remained as an independent risk factor for death. ISS, prior lines of therapy, prior stem cell transplantation, and disease status at COVID-19 were not associated with any analyzed outcomes. MM patients who recovered from COVID had the current MM treatment delayed in 61% of cases. In this series, COVID-19 MM patients had a very high frequency of hospitalization, ventilatory support requirement, ICU admission, and deaths due to COVID-19. Although not associated with increased mortality, prior therapy drug classes were associated with severity of manifestation in our series. We also observed a high frequency of MM treatment delay in recovered patients, and the post-COVID clinical impact should be more explored. The high mortality observed reinforces the importance of preventing COVID-19, such as social distancing, wearing masks, and vaccination. Disclosures De Queiroz Crusoe: Janssen: Research Funding. Hungria: Takeda: Honoraria; Amgen, BMS, Celgene, Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Support for attending meetings/travel ; Abbvie: Honoraria; Sanofi: Honoraria, Other: Support for attending meetings/travel .

Acute Myeloid Leukemia and Survival on the Intensive Care Unit (ICU) - Biology- and Treatment-Related Determinants of Outcome - An Analysis of the AML-CG

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 2166-2166
Author(s):  
Bernhard Heilmeier ◽  
Johannes Thudium ◽  
Matthias Kochanek ◽  
Christoph Schmid ◽  
Joachim Stemmler ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care ◽  
Renal Replacement Therapy ◽  
Replacement Therapy ◽  
Univariate Analysis ◽  
Primary Diagnosis ◽  
Induction Phase ◽  
Icu Admission ◽  
Saps Ii ◽  
Icu Outcome

Abstract Abstract 2166 Background: An established factor for predicting the mortality of patients admitted to an ICU is the Severe Acute Physiology Score (SAPS) II. However, for patients with acute myeloid leukemia (AML) it is uncertain whether factors beyond SAPS II do influence the ICU outcome. Therefore we examined additional factors including age and factors related to AML biology and its treatment in the so far largest cohort of patients with AML worldwide regarding their ICU outcome. Methods: Retrospective analysis of 256 patients with 366 admissions to medical ICU between 2004 and 2009 in 3 large German hematologic centers. Patient age and gender, reason for ICU admission, duration of intensive care, SAPSII, need for invasive mechanical ventilation (IMV), renal replacement therapy and/or vasopressors, laboratory values at ICU admission for creatinine, bilirubin and C-reactive protein, AML karyotype, presence of FLT3-ITD and/or NPM1-mutation, FAB classification, last AML treatment, AML status and allogeneic transplant status were evaluated as potential risk factors. Correlations were analyzed using the Mann-Whitney U test. Univariate analysis was performed using the log rank test for the time until death on ICU occurred. Significant risk factors were studied in multivariate analysis (Cox regression). Results: At the time of analysis (08/2010) the median age of patients was 55.3 (range 19.7–84.9) years, and 47.5% were female. 46% of ICU admissions were due to infectious complications. A respiratory problem was present in 60% of the ICU transfers. IMV, vasopressors and renal replacement therapy were necessary in 51.3%, 42.6% and 22.7%, respectively, of the ICU courses. ICU survival was 64.8%. AML status was primary diagnosis/induction phase in 53.3%, postremission phase in 15.8% and relapse/refractory in 27.6% of ICU courses. 66.4% of admissions to ICU had conservative treatment (no transplant), 15.8% underwent allogeneic hematopoietic stem cell transplantation (allo SCT) in the same hospital stay (peritransplant status) and 14.5% had had allo SCT in a former hospital stay (posttransplant status). AML karyotype was favourable in 7.1%, intermediate in 47.8% and unfavourable in 20.2%. SAPS II was available in 208 ICU transfers. Duration of intensive care was 8.1 (mean)/3.0 (median) days with a range from 0.5–76 days. In univariate analysis risk factors predicting diminished ICU survival were high SAPS II (p=0.008), sepsis as reason for ICU admission (p=0.007), need for IMV (p<0.001), use of vasopressors (p<0.001), renal replacement therapy (p=0.002), intermediate or unfavourable AML karyotype (p=0.027), FAB classification other than AML M3 (p=0.012), postremission or relapse/refractory status of AML (p=0.029) and posttransplant status of AML (p=0.002). ICU mortality was lower in primary diagnosis/induction phase and higher in posttransplant phase of AML than predicted by the median SAPS II of these cohorts. In multivariate analysis the only significant predictor of inferior ICU survival was the extent of vasopressor treatment (hazard ratio (hr) 1.83, 95% CI 1.09–3.08; p=0.022), whereas high SAPS II was of borderline significance (hr 1.02, 95% CI 1.00– 1.03; p=0.064). Conclusions: In contrast to the broad majority of ICU patients, SAPS II is not an optimal predictor of ICU survival in patients with AML. Disease status was of high relevance with an AML status of primary diagnosis/induction phase indicating a better and posttransplant (but not peritransplant) status a worse ICU survival than predicted by SAPS II. The strongest predictor for ICU mortality was the extent of vasopressor use. In contrast age up to the 8th decade had no impact on ICU survival. These results may help to better define ICU admission and treatment policies for patients with AML. Disclosures: No relevant conflicts of interest to declare.

Incidence, Risk factors, and Biomarkers Predicting Ischemic or Hemorrhagic Stroke Associated Acute Kidney Injury and Outcome: A Retrospective Study in a General Intensive Care Unit

2019 ◽  
Vol 47 (4) ◽  
pp. 317-326 ◽  
Author(s):  
Fang Jiang ◽  
Lianjiu Su ◽  
Hui Xiang ◽  
Xiaoyi Zhang ◽  
Dongxue Xu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Acute Kidney Injury ◽  
Intensive Care ◽  
Hemorrhagic Stroke ◽  
Kidney Injury ◽  
Roc Curves ◽  
Regression Analyses ◽  
Stroke Patients ◽  
Icu Admission

Objective: We investigated the epidemiology, risk factors, and predictive parameters for ischemic or hemorrhagic stroke-associated acute kidney injury (AKI) and mortality in a general intensive care unit (ICU) in China. Methods: During 5 years, 479 stroke patients were screened, and 381 were enrolled. AKI was diagnosed within 7 days after ICU admission, based on the Kidney Disease Improving Global Outcomes criteria. Risk factors of AKI were assessed by Logistic regression analyses, and the predictive biomarkers for AKI were determined using receiver operating characteristic (ROC) curves. Also examined were factors influencing 28-day mortality, using Cox regression analyses and Kaplan-Meier curves. ­Results: Among all, 115 (30.18%) patients developed AKI. Multivariate regression analyses revealed that the following features at ICU admission significantly increased the risk of developing AKI: an increased National Institutes of Health Stroke Scale score (OR 1.136, p < 0.001) and Acute Physiology and Chronic Health Evaluation II score (OR 1.107, p = 0.042); hypertension (OR 2.346, p = 0.008); use of loop diuretics (OR 1.961, p = 0.032); and higher serum cystatin C (sCysC; OR 8.156, p = 0.001). The area under the ROC curves for predicting AKI using sCysC was 0.772, slightly better than that of other biomarkers. The sCysC ≥0.93 mg/L (hazard ratio 1.844, p = 0.004) significantly predicted 28-day mortality. Conclusions: Among stroke patients in ICU, we identified significant risk factors of stroke-associated AKI. Serum CysC level at ICU admission was an important biomarker for predicting AKI and 28-day mortality.

scholarly journals The swedish covid‐19 intensive care cohort: Risk factors of ICU admission and ICU mortality

2021 ◽  
Author(s):  
Björn Ahlström ◽  
Robert Frithiof ◽  
Michael Hultström ◽  
Ing‐Marie Larsson ◽  
Gunnar Strandberg ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care ◽  
Icu Mortality ◽  
Icu Admission

scholarly journals Image and structured data analysis for prognostication of health outcomes in patients presenting to the Emergency Department during the COVID-19 pandemic

2021 ◽  
Author(s):  
Liam Butler ◽  
Ibrahim Karabayir ◽  
Mohammad Samie Tootooni ◽  
Majid Afshar ◽  
Ari Goldberg ◽  
...  
Keyword(s):  
Machine Learning ◽  
Emergency Department ◽  
Intensive Care ◽  
Deep Learning ◽  
Clinical Data ◽  
Chest Radiographs ◽  
Gradient Boosting ◽  
Learning Models ◽  
Icu Admission ◽  
Light Gradient

Background: Patients admitted to the emergency department (ED) with COVID-19 symptoms are routinely required to have chest radiographs and computed tomography (CT) scans. COVID-19 infection has been directly related to development of acute respiratory distress syndrome (ARDS) and severe infections lead to admission to intensive care and can also lead to death. The use of clinical data in machine learning models available at time of admission to ED can be used to assess possible risk of ARDS, need for intensive care unit (ICU) admission as well as risk of mortality. In addition, chest radiographs can be inputted into a deep learning model to further assess these risks. Purpose: This research aimed to develop machine and deep learning models using both structured clinical data and image data from the electronic health record (EHR) to adverse outcomes following ED admission. Materials and Methods: Light Gradient Boosting Machines (LightGBM) was used as the main machine learning algorithm using all clinical data including 42 variables. Compact models were also developed using 15 the most important variables to increase applicability of the models in clinical settings. To predict risk of the aforementioned health outcome events, transfer learning from the CheXNet model was implemented on our data as well. This research utilized clinical data and chest radiographs of 3571 patients 18 years and older admitted to the emergency department between 9th March 2020 and 29th October 2020 at Loyola University Medical Center. Main Findings: Our research results show that we can detect COVID-19 infection (AUC = 0.790 (0.746-0.835)) and predict the risk of developing ARDS (AUC = 0.781 (0.690-0.872), ICU admission (AUC = 0.675 (0.620-0.713)), and mortality (AUC = 0.759 (0.678-0.840)) at moderate accuracy from both chest X-ray images and clinical data. Principal Conclusions: The results can help in clinical decision making, especially when addressing ARDS and mortality, during the assessment of patients admitted to the ED with or without COVID-19 symptoms.

scholarly journals Incidence, risk factors, and causes of maternal near-miss admitted to the intensive care unit in Yangzhou, China: A 5-year retrospective study

2020 ◽  
Author(s):  
Ying Chen ◽  
Jiaoyang Shi ◽  
Yuting Zhu ◽  
Xiang Kong ◽  
Yang Lu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Retrospective Study ◽  
Near Miss ◽  
World Health ◽  
Maternal Near Miss ◽  
Icu Admission ◽  
Medical Institutions ◽  
Incidence Risk

Abstract BackgroundThe maternal near-miss (MNM) criterion formulated by the WHO can dynamically evaluate the obstetric quality and maternal health in medical institutions. The study aims to explore the incidence, risk factors, and causes of MNM cases admitted to the intensive care unit (ICU) within 5 years.MethodsThis study is a retrospective study. The data of MNM admitted to the ICU comes from the medical records of Subei People's Hospital in Yangzhou from 2015 to 2019. The study subjects meet at least one World Health Organization (WHO) criterion of MNM. The MNM who had not been admitted to the ICU in the same year served as the control group. We use descriptive analysis, Chi-Square test and Fisher’s exact test for data analysis.Results151 women met the WHO criteria of MNM and there was one maternal death in 2016. The average maternal near-miss rate（MNMR）for ICU admission was 3.5 per 1,000LBs, and the average MNM morbidity was 0.36%. The average maternal mortality ratio (MMR) was 5 per 100,000LBs. The 5-year research period witnessed moderate growth in MNM admitted to the ICU. The region, referral, gravidity, prenatal examination, and mode of delivery were significantly related to the MNM admitted to the ICU(p<0.05). Concerning neonatal characteristics, there is a significant difference in preterm birth rate and low Apgar scores at 1 min and 5 min(p<0.05). The direct obstetric causes were the primary cause of MNM, regardless of the ICU admission. The leading direct obstetric causes of MNM admitted to the ICU were obstetric hemorrhage diseases(38.8%)，following hypertension diseases(18.8%), while the leading indirect obstetric cause of MNM admitted to the ICU was heart-related diseases (7.2%). MNM for the ICU admission were mostly postpartum (96.9%), who underwent multiple interventions.ConclusionsICU is one of the most important endpoints of MNM management. In the context of "universal two-child", medical institutions should strengthen multidisciplinary joint treatment. In the future, it needs to be expanded to multi-center research to determine the criteria for MNM admitted to the ICU.

scholarly journals Factors Associated with 90-Day Mortality in Invasively Ventilated Patients with COVID-19 in Marseille, France

2021 ◽  
Vol 10 (23) ◽  
pp. 5650
Author(s):  
Maxime Volff ◽  
David Tonon ◽  
Youri Bommel ◽  
Noémie Peres ◽  
David Lagier ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care ◽  
Respiratory Failure ◽  
Intensive Care Units ◽  
Arterial Thrombosis ◽  
Invasive Mechanical Ventilation ◽  
Multivariable Analysis ◽  
Factors Associated ◽  
Icu Admission ◽  
Ventilated Patients

Objectives: To describe clinical characteristics and management of intensive care units (ICU) patients with laboratory-confirmed COVID-19 and to determine 90-day mortality after ICU admission and associated risk factors. Methods: This observational retrospective study was conducted in six intensive care units (ICUs) in three university hospitals in Marseille, France. Between 10 March and 10 May 2020, all adult patients admitted in ICU with laboratory-confirmed SARS-CoV-2 and respiratory failure were eligible for inclusion. The statistical analysis was focused on the mechanically ventilated patients. The primary outcome was the 90-day mortality after ICU admission. Results: Included in the study were 172 patients with COVID-19 related respiratory failure, 117 of whom (67%) received invasive mechanical ventilation. 90-day mortality of the invasively ventilated patients was 27.4%. Median duration of ventilation and median length of stay in ICU for these patients were 20 (9–33) days and 29 (17–46) days. Mortality increased with the severity of ARDS at ICU admission. After multivariable analysis was carried out, risk factors associated with 90-day mortality were age, elevated Charlson comorbidity index, chronic statins intake and occurrence of an arterial thrombosis. Conclusion: In this cohort, age and number of comorbidities were the main predictors of mortality in invasively ventilated patients. The only modifiable factor associated with mortality in multivariate analysis was arterial thrombosis.

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