Outcomes in Patients With COVID-19 With Acute Encephalopathy and Coma: An International Prospective Study.

BACKGROUND AND OBJECTIVES: To report the prevalence of acute encephalopathy and outcomes in patients with severe coronavirus disease 2019 (COVID-19) and to identify determinants of 90-day outcomes. METHODS: Data from adults with severe COVID-19 and acute encephalopathy were prospectively collected for patients requiring intensive care unit management in 31 university or university-affiliated intensive care units in 6 countries (France, United States, Colombia, Spain, Mexico, and Brazil) between March and September of 2020. Acute encephalopathy was defined, as recently recommended, as subsyndromal delirium or delirium or as a comatose state in case of severely decreased level of consciousness. Logistic multivariable regression was performed to identify factors associated with 90-day outcomes. A Glasgow Outcome Scale-Extended (GOS-E) score of 1-4 was considered a poor outcome (indicating death, vegetative state, or severe disability). RESULTS: Of 4,060 patients admitted with COVID-19, 374 (9.2%) experienced acute encephalopathy at or before the intensive care unit (ICU) admission. A total of 199/345 (57.7%) patients had a poor outcome at 90-day follow-up as evaluated by the GOS-E (29 patients were lost to follow-up). On multivariable analysis, age older than 70 years (odds ratio [OR] 4.01, 95% CI 2.25-7.15), presumed fatal comorbidity (OR 3.98, 95% CI 1.68-9.44), Glasgow coma scale score <9 before/at ICU admission (OR 2.20, 95% CI 1.22-3.98), vasopressor/inotrope support during ICU stay (OR 3.91, 95% CI 1.97-7.76), renal replacement therapy during ICU stay (OR 2.31, 95% CI 1.21-4.50), and CNS ischemic or hemorrhagic complications as acute encephalopathy etiology (OR 3.22, 95% CI 1.41-7.82) were independently associated with higher odds of poor 90-day outcome. Status epilepticus, posterior reversible encephalopathy syndrome, and reversible cerebral vasoconstriction syndrome were associated with lower odds of poor 90-day outcome (OR 0.15, 95% CI 0.03-0.83). DISCUSSION: In this observational study, we found a low prevalence of acute encephalopathy at ICU admission in patients with COVID-19. More than half of patients with COVID-19 presenting with acute encephalopathy had poor outcomes as evaluated by GOS-E. Determinants of poor 90-day outcome were dominated by older age, comorbidities, degree of impairment of consciousness before/at ICU admission, association with other organ failures, and acute encephalopathy etiology. TRIAL REGISTRATION INFORMATION: The study is registered with ClinicalTrials.gov, number NCT04320472.

Impairment of central language processing in critically ill coronavirus disease 2019 patients with delirium.

Accumulating evidence indicates that coronavirus disease 2019 is a major cause of delirium. Given the global dimension of the current pandemic and the fact that delirium is a strong predictor of cognitive decline for critically ill patients, this raises concerns regarding the neurological cost of coronavirus disease 2019. Currently, there is a major knowledge gap related to the covert yet potentially incapacitating higher-order cognitive impairment underpinning coronavirus disease 2019 related delirium. The aim of the current study was to analyse the electrophysiological signatures of language processing in coronavirus disease 2019 patients with delirium by using a specifically designed multidimensional auditory event-related potential battery to probe hierarchical cognitive processes, including self-processing (P300) and semantic/lexical priming (N400). Clinical variables and electrophysiological data were prospectively collected in controls subjects (n = 14) and in critically ill coronavirus disease 2019 patients with (n = 19) and without (n = 22) delirium. The time from intensive care unit admission to first clinical sign of delirium was of 8 (3.5-20) days, and the delirium lasted for 7 (4.5-9.5) days. Overall, we have specifically identified in coronavirus disease 2019 patients with delirium, both a preservation of low-level central auditory processing (N100 and P200) and a coherent ensemble of covert higher-order cognitive dysfunctions encompassing self-related processing (P300) and sematic/lexical language priming (N400) (spatial-temporal clustering, P-cluster ≤ 0.05). We suggest that our results shed new light on the neuropsychological underpinnings of coronavirus disease 2019 related delirium, and may constitute a valuable method for patient's bedside diagnosis and monitoring in this clinically challenging setting.

Management and outcomes of pregnant women admitted to intensive care unit for severe pneumonia related to SARS-CoV-2 infection: the multicenter and international COVIDPREG study.

PURPOSE: Management and outcomes of pregnant women with coronavirus disease 2019 (COVID-19) admitted to intensive care unit (ICU) remain to be investigated. METHODS: A retrospective multicenter study conducted in 32 ICUs in France, Belgium and Switzerland. Maternal management as well as maternal and neonatal outcomes were reported. RESULTS: Among the 187 pregnant women with COVID-19 (33 ± 6 years old and 28 ± 7 weeks' gestation), 76 (41%) were obese, 12 (6%) had diabetes mellitus and 66 (35%) had pregnancy-related complications. Standard oxygenation, high-flow nasal oxygen therapy (HFNO) and non-invasive ventilation (NIV) were used as the only oxygenation technique in 41 (22%), 55 (29%) and 18 (10%) patients, respectively, and 73 (39%) were intubated. Overall, 72 (39%) patients required several oxygenation techniques and 15 (8%) required venovenous extracorporeal membrane oxygenation. Corticosteroids and tocilizumab were administered in 157 (84%) and 25 (13%) patients, respectively. Awake prone positioning or prone positioning was performed in 49 (26%) patients. In multivariate analysis, risk factors for intubation were obesity (cause-specific hazard ratio (CSH) 2.00, 95% CI (1.05-3.80), p = 0.03), term of pregnancy (CSH 1.07, 95% CI (1.02-1.10), per + 1 week gestation, p = 0.01), extent of computed tomography (CT) scan abnormalities > 50% (CSH 2.69, 95% CI (1.30-5.60), p < 0.01) and NIV use (CSH 2.06, 95% CI (1.09-3.90), p = 0.03). Delivery was required during ICU stay in 70 (37%) patients, mainly due to maternal respiratory worsening, and improved the driving pressure and oxygenation. Maternal and fetal/neonatal mortality rates were 1% and 4%, respectively. The rate of maternal and/or neonatal complications increased with the invasiveness of maternal respiratory support. CONCLUSION: In ICU, corticosteroids, tocilizumab and prone positioning were used in few pregnant women with COVID-19. Over a third of patients were intubated and delivery improved the driving pressure.

Co-Infection and Ventilator-Associated Pneumonia in Critically Ill COVID-19 Patients Requiring Mechanical Ventilation: A Retrospective Cohort Study.

Considering virus-related and drug-induced immunocompromised status of critically ill COVID-19 patients, we hypothesize that these patients would more frequently develop ventilator-associated pneumonia (VAP) than patients with ARDS from other viral causes. We conducted a retrospective observational study in two intensive care units (ICUs) from France, between 2017 and 2020. We compared bacterial co-infection at ICU admission and throughout the disease course of two retrospective longitudinally sampled groups of critically ill patients, who were admitted to ICU for either H1N1 or SARS-CoV-2 respiratory infection and depicted moderate-to-severe ARDS criteria upon admission. Sixty patients in the H1N1 group and 65 in the COVID-19 group were included in the study. Bacterial co-infection at the endotracheal intubation time was diagnosed in 33% of H1N1 and 16% COVID-19 patients (p = 0.08). The VAP incidence per 100 days of mechanical ventilation was 3.4 (2.2-5.2) in the H1N1 group and 7.2 (5.3-9.6) in the COVID-19 group (p < 0.004). The HR to develop VAP was of 2.33 (1.34-4.04) higher in the COVID-19 group (p = 0.002). Ten percent of H1N1 patients and 30% of the COVID-19 patients had a second episode of VAP (p = 0.013). COVID-19 patients have fewer bacterial co-infections upon admission, but the incidence of secondary infections increased faster in this group compared to H1N1 patients.

Lung Ultrasound to Assist ICU Admission Decision-Making Process of COVID-19 Patients With Acute Respiratory Failure.

There is only low-certainty evidence on the use of predictive models to assist COVID-19 patient's ICU admission decision-making process. Accumulative evidence suggests that lung ultrasound (LUS) assessment of COVID-19 patients allows accurate bedside evaluation of lung integrity, with the added advantage of repeatability, absence of radiation exposure, reduced risk of virus dissemination, and low cost. Our goal is to assess the performance of a quantified indicator resulting from LUS data compared with standard clinical practice model to predict critical respiratory illness in the 24 hours following hospital admission. DESIGN: Prospective cohort study. SETTING: Critical Care Unit from University Hospital Purpan (Toulouse, France) between July 2020 and March 2021. PATIENTS: Adult patients for COVID-19 who were in acute respiratory failure (ARF), defined as blood oxygen saturation as measured by pulse oximetry less than 90% while breathing room air or respiratory rate greater than or equal to 30 breaths/min at hospital admission. Linear multivariate models were used to identify factors associated with critical respiratory illness, defined as death or mild/severe acute respiratory distress syndrome (Pao2/Fio2 < 200) in the 24 hours after patient's hospital admission. INTERVENTION: LUS assessment. MEASUREMENTS AND MAIN RESULTS: One hundred and forty COVID-19 patients with ARF were studied. This cohort was split into two independent groups: learning sample (first 70 patients) and validation sample (last 70 patients). Interstitial lung water, thickening of the pleural line, and alveolar consolidation detection were strongly associated with patient's outcome. The LUS model predicted more accurately patient's outcomes than the standard clinical practice model (DeLong test: Testing: z score = 2.50, p value = 0.01; Validation: z score = 2.11, p value = 0.03). CONCLUSIONS: LUS assessment of COVID-19 patients with ARF at hospital admission allows a more accurate prediction of the risk of critical respiratory illness than standard clinical practice. These results hold the promise of improving ICU resource allocation process, particularly in the case of massive influx of patients or limited resources, both now and in future anticipated pandemics.

Human NLRP1 is a sensor of pathogenic coronavirus 3CL proteases in lung epithelial cells.

Inflammation observed in SARS-CoV-2-infected patients suggests that inflammasomes, proinflammatory intracellular complexes, regulate various steps of infection. Lung epithelial cells express inflammasome-forming sensors and constitute the primary entry door of SARS-CoV-2. Here, we describe that the NLRP1 inflammasome detects SARS-CoV-2 infection in human lung epithelial cells. Specifically, human NLRP1 is cleaved at the Q333 site by multiple coronavirus 3CL proteases, which triggers inflammasome assembly and cell death and limits the production of infectious viral particles. Analysis of NLRP1-associated pathways unveils that 3CL proteases also inactivate the pyroptosis executioner Gasdermin D (GSDMD). Subsequently, caspase-3 and GSDME promote alternative cell pyroptosis. Finally, analysis of pyroptosis markers in plasma from COVID-19 patients with characterized severe pneumonia due to autoantibodies against, or inborn errors of, type I interferons (IFNs) highlights GSDME/caspase-3 as potential markers of disease severity. Overall, our findings identify NLRP1 as a sensor of SARS-CoV-2 infection in lung epithelia.

Mass Training In Situ During COVID-19 Pandemic: Enhancing Efficiency and Minimizing Sick Leaves.

INTRODUCTION: Avoiding coronavirus disease 2019 (COVID-19) work-related infection in frontline healthcare workers is a major challenge. A massive training program was launched in our university hospital for anesthesia/intensive care unit and operating room staff, aiming at upskilling 2249 healthcare workers for COVID-19 patients' management. We hypothesized that such a massive training was feasible in a 2-week time frame and efficient in avoiding sick leaves. METHODS: We performed a retrospective observational study. Training focused on personal protective equipment donning/doffing and airway management in a COVID-19 simulated patient. The educational models used were in situ procedural and immersive simulation, peer-teaching, and rapid cycle deliberate practice. Self-learning organization principles were used for trainers' management. Ordinary disease quantity in full-time equivalent in March and April 2020 were compared with the same period in 2017, 2018, and 2019. RESULTS: A total of 1668 healthcare workers were trained (74.2% of the target population) in 99 training sessions over 11 days. The median number of learners per session was 16 (interquartile range = 9-25). In the first 5 days, the median number of people trained per weekday was 311 (interquartile range = 124-385). Sick leaves did not increase in March to April 2020 compared with the same period in the 3 preceding years. CONCLUSIONS: Massive training for COVID-19 patient management in frontline healthcare workers is feasible in a very short time and efficient in limiting the rate of sick leave. This experience could be used in the anticipation of new COVID-19 waves or for rapidly preparing hospital staff for an unexpected major health crisis.

BMI and pneumonia outcomes in critically ill covid-19 patients: An international multicenter study.

OBJECTIVE: Previous studies have unveiled a relationship between the severity of coronavirus disease 2019 (COVID-19) pneumonia and obesity. The aims of this multicenter retrospective cohort study were to disentangle the association of BMI and associated metabolic risk factors (diabetes, hypertension, hyperlipidemia, and current smoking status) in critically ill patients with COVID-19. METHODS: Patients admitted to intensive care units for COVID-19 in 21 centers (in Europe, Israel, and the United States) were enrolled in this study between February 19, 2020, and May 19, 2020. Primary and secondary outcomes were the need for invasive mechanical ventilation (IMV) and 28-day mortality, respectively. RESULTS: A total of 1,461 patients were enrolled; the median (interquartile range) age was 64 years (40.9-72.0); 73.2% of patients were male; the median BMI was 28.1 kg/m2 (25.4-32.3); a total of 1,080 patients (73.9%) required IMV; and the 28-day mortality estimate was 36.1% (95% CI: 33.0-39.5). An adjusted mixed logistic regression model showed a significant linear relationship between BMI and IMV: odds ratio = 1.27 (95% CI: 1.12-1.45) per 5 kg/m2 . An adjusted Cox proportional hazards regression model showed a significant association between BMI and mortality, which was increased only in obesity class III (≥40; hazard ratio = 1.68 [95% CI: 1.06-2.64]). CONCLUSIONS: In critically ill COVID-19 patients, a linear association between BMI and the need for IMV, independent of other metabolic risk factors, and a nonlinear association between BMI and mortality risk were observed.

Systematic Screening for Deep Vein Thrombosis in Critically Ill Inpatients With COVID-19: Impact on the Incidence of Venous Thromboembolism.

Background: Several studies suggest an increased incidence of thrombosis in COVID-19 patients. However, evidence on how to prevent and even treat it is scarce. The aim of this study was to compare the cumulative incidence of venous thromboembolism (VTE) of two different methods for lower extremity deep vein thrombosis (LE-DVT) diagnosis: systematic vs. clinically guided complete compression venous ultrasonography (CCUS). We conducted a monocentric, prospective, open-label, non-randomized study. All consecutive patients admitted in three intensive care units (ICUs) of University Hospital of Toulouse for COVID-19 pneumonia were included: one performed systematic screening for LE-DVT, the others did not. The primary outcome was the 21-day cumulative incidence of VTE. The secondary end points were the 21-day cumulative incidences of major bleeding and death. Results: Among the 78 patients included, 27 (34.6%) underwent systematic screening for DVT 7 ± 2 days after ICU admission. Thirty-two patients (41.0%) were diagnosed with VTE, with a 21-day cumulative incidence of 42.3% (95% CI, 31.4-55.2), without difference between screened and non-screened patients (hazard ratio 1.45, 95% CI, 0.72-2.93). In the screened group, the frequency of isolated DVT was higher (25.9 vs. 5.9%, p-value = 0.027), but the frequency of pulmonary embolism was not reduced (25.9 vs. 29.4%, p-value = 0.745). The 21-day cumulative incidences of major bleeding and death were 9.6% (95% CI, 4.7-19.2) and 10.3% (95% CI, 5.0-20.8), respectively, without difference between the two groups. Conclusions: A systematic screening for DVT in patients hospitalized in ICU was not associated with a higher diagnosis of VTE or a reduced diagnosis of PE.

Detection of Line Artifacts in Lung Ultrasound Images of COVID-19 Patients Via Nonconvex Regularization.

In this article, we present a novel method for line artifacts quantification in lung ultrasound (LUS) images of COVID-19 patients. We formulate this as a nonconvex regularization problem involving a sparsity-enforcing, Cauchy-based penalty function, and the inverse Radon transform. We employ a simple local maxima detection technique in the Radon transform domain, associated with known clinical definitions of line artifacts. Despite being nonconvex, the proposed technique is guaranteed to convergence through our proposed Cauchy proximal splitting (CPS) method, and accurately identifies both horizontal and vertical line artifacts in LUS images. To reduce the number of false and missed detection, our method includes a two-stage validation mechanism, which is performed in both Radon and image domains. We evaluate the performance of the proposed method in comparison to the current state-of-the-art B-line identification method, and show a considerable performance gain with 87% correctly detected B-lines in LUS images of nine COVID-19 patients.