Thoracic UltrasONOgraphy Reporting: The TUONO Consensus.

The widespread use of the lung ultrasound (LUS) has not been followed by the development of a comprehensive standardized tool for its reporting in the intensive care unit (ICU) which could be useful to promote consistency and reproducibility during clinical examination. This work aims to define the essential features to be included in a standardized reporting tool and provides a structured model form to fully express the diagnostic potential of LUS and facilitate intensivists in the use of a LUS in everyday clinical ICU examination. We conducted a modified Delphi process to build consensus on the items to be integrated in a standardized report form and on its structure. A committee of 19 critical care physicians from 19 participating ICUs in Italy was formed, including intensivists experienced in ultrasound from both teaching hospitals and referral hospitals, and internationally renowned experts on the LUS. The consensus for 31 statements out of 33 was reached at the third Delphi round. A structured model form was developed based on the approved statements. The development of a standardized model as a backbone to report a LUS may facilitate the guidelines' application in clinical practice and increase inter-operator agreement. Further studies are needed to evaluate the effects of standardized reports in critically ill patients.

Kinetics of the Cell Cycle Arrest Biomarkers (TIMP2 and IGFBP7) for the Diagnosis of Acute Kidney Injury in Critically Ill COVID-19 Patients.

BACKGROUND: Acute kidney injury (AKI) is highly prevalent in critical COVID-19 patients. The diagnosis and staging of AKI are based on serum creatinine (sCr) and urinary output criteria, with limitations in the functional markers. New cell-cycle arrest biomarkers [TIMP2]*[IGFBP7] have been proposed for early detection of AKI, but their role in critically ill COVID-19 patients is poorly understood. METHODS: We conducted an observational study to assess the performance of [TIMP2]*[IGFBP7] for the detection of AKI in critical COVID-19 patients admitted to our intensive care unit (ICU). We sampled urinary [TIMP2]*[IGFBP7] levels at ICU admission, 12 h, 24 h, and 48 h, and compared the results to the development of AKI, as well as baseline and laboratory data. RESULTS: Forty-one patients were enrolled. The median age was 66 years [57-72] and most were males (85%). Thirteen patients (31.7%) developed no/mild stage AKI, 19 patients (46.3%) moderate AKI, and nine patients (22.0%) severe AKI. The ICU mortality was 29.3%. sCr levels in the Emergency Department or at ICU admission were not significantly different according to AKI stage. [TIMP-2]*[IGFBP-7] urinary levels were elevated in severe AKI at 12 h after ICU admission, but not at ICU admission or 24 h or 48 h after ICU admission. CONCLUSION: Urinary biomarkers [TIMP-2]*[IGFBP-7] were generally increased in this population with a high prevalence of AKI, and were higher in patients with severe AKI measured at 12 h from ICU admission. Further studies are needed to evaluate the best timing of these biomarkers in this population.

Surviving Sepsis Campaign: Guidelines on the Management of Critically Ill Adults with Coronavirus Disease 2019 (COVID-19).

BACKGROUND: The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of a rapidly spreading illness, Coronavirus Disease 2019 (COVID-19), affecting thousands of people around the world. Urgent guidance for clinicians caring for the sickest of these patients is needed. METHODS: We formed a panel of 36 experts from 12 countries. All panel members completed the World Health Organization conflict of interest disclosure form. The panel proposed 53 questions that are relevant to the management of COVID-19 in the ICU. We searched the literature for direct and indirect evidence on the management of COVID-19 in critically ill patients in the ICU. We identified relevant and recent systematic reviews on most questions relating to supportive care. We assessed the certainty in the evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach, then generated recommendations based on the balance between benefit and harm, resource and cost implications, equity, and feasibility. Recommendations were either strong or weak, or in the form of best practice recommendations. RESULTS: The Surviving Sepsis Campaign COVID-19 panel issued 54 statements, of which four are best practice statements, nine are strong recommendations, and 35 are weak recommendations. No recommendation was provided for six questions. The topics were: 1) infection control, 2) laboratory diagnosis and specimens, 3) hemodynamic support, 4) ventilatory support, and 5) COVID-19 therapy. CONCLUSION: The Surviving Sepsis Campaign COVID-19 panel issued several recommendations to help support healthcare workers caring for critically ill ICU patients with COVID-19. When available, we will provide new evidence in further releases of these guidelines.

Outcome prediction during an ICU surge using a purely data-driven approach: A supervised machine learning case-study in critically ill patients from COVID-19 Lombardy outbreak.

PURPOSE: COVID-19 disease frequently affects the lungs leading to bilateral viral pneumonia, progressing in some cases to severe respiratory failure requiring ICU admission and mechanical ventilation. Risk stratification at ICU admission is fundamental for resource allocation and decision making. We assessed performances of three machine learning approaches to predict mortality in COVID-19 patients admitted to ICU using early operative data from the Lombardy ICU Network. METHODS: This is a secondary analysis of prospectively collected data from Lombardy ICU network. A logistic regression, balanced logistic regression and random forest were built to predict survival on two datasets: dataset A included patient demographics, medications before admission and comorbidities, and dataset B included respiratory data the first day in ICU. RESULTS: Models were trained on 1484 patients on four outcomes (7/14/21/28 days) and reached the greatest predictive performance at 28 days (F1-score: 0.75 and AUC: 0.80). Age, number of comorbidities and male gender were strongly associated with mortality. On dataset B, mode of ventilatory assistance at ICU admission and fraction of inspired oxygen were associated with an increase in prediction performances. CONCLUSIONS: Machine learning techniques might be useful in emergency phases to reach good predictive performances maintaining interpretability to gain knowledge on complex situations and enhance patient management and resources.

Impact of dexamethasone on the incidence of ventilator-associated pneumonia in mechanically ventilated COVID-19 patients: a propensity-matched cohort study.

OBJECTIVE: To assess the impact of treatment with steroids on the incidence and outcome of ventilator-associated pneumonia (VAP) in mechanically ventilated COVID-19 patients. DESIGN: Propensity-matched retrospective cohort study from February 24 to December 31, 2020, in 4 dedicated COVID-19 Intensive Care Units (ICU) in Lombardy (Italy). PATIENTS: Adult consecutive mechanically ventilated COVID-19 patients were subdivided into two groups: (1) treated with low-dose corticosteroids (dexamethasone 6 mg/day intravenous for 10 days) (DEXA+); (2) not treated with corticosteroids (DEXA-). A propensity score matching procedure (1:1 ratio) identified patients' cohorts based on: age, weight, PEEP Level, PaO2/FiO2 ratio, non-respiratory Sequential Organ Failure Assessment (SOFA) score, Charlson Comorbidity Index (CCI), C reactive protein plasma concentration at admission, sex and admission hospital (exact matching). INTERVENTION: Dexamethasone 6 mg/day intravenous for 10 days from hospital admission. MEASUREMENTS AND MAIN RESULTS: Seven hundred and thirty-nine patients were included, and the propensity-score matching identified two groups of 158 subjects each. Eighty-nine (56%) DEXA+ versus 55 (34%) DEXA- patients developed a VAP (RR 1.61 (1.26-2.098), p = 0.0001), after similar time from hospitalization, ICU admission and intubation. DEXA+ patients had higher crude VAP incidence rate (49.58 (49.26-49.91) vs. 31.65 (31.38-31.91)VAP*1000/pd), (IRR 1.57 (1.55-1.58), p < 0.0001) and risk for VAP (HR 1.81 (1.31-2.50), p = 0.0003), with longer ICU LOS and invasive mechanical ventilation but similar mortality (RR 1.17 (0.85-1.63), p = 0.3332). VAPs were similarly due to G+ bacteria (mostly Staphylococcus aureus) and G- bacteria (mostly Enterobacterales). Forty-one (28%) VAPs were due to multi-drug resistant bacteria. VAP was associated with almost doubled ICU and hospital LOS and invasive mechanical ventilation, and increased mortality (RR 1.64 [1.02-2.65], p = 0.040) with no differences among patients' groups. CONCLUSIONS: Critically ill COVID-19 patients are at high risk for VAP, frequently caused by multidrug-resistant bacteria, and the risk is increased by corticosteroid treatment. TRIAL REGISTRATION: NCT04388670, retrospectively registered May 14, 2020.

Clinical and organizational factors associated with mortality during the peak of first COVID-19 wave: the global UNITE-COVID study.

PURPOSE: To accommodate the unprecedented number of critically ill patients with pneumonia caused by coronavirus disease 2019 (COVID-19) expansion of the capacity of intensive care unit (ICU) to clinical areas not previously used for critical care was necessary. We describe the global burden of COVID-19 admissions and the clinical and organizational characteristics associated with outcomes in critically ill COVID-19 patients. METHODS: Multicenter, international, point prevalence study, including adult patients with SARS-CoV-2 infection confirmed by polymerase chain reaction (PCR) and a diagnosis of COVID-19 admitted to ICU between February 15th and May 15th, 2020. RESULTS: 4994 patients from 280 ICUs in 46 countries were included. Included ICUs increased their total capacity from 4931 to 7630 beds, deploying personnel from other areas. Overall, 1986 (39.8%) patients were admitted to surge capacity beds. Invasive ventilation at admission was present in 2325 (46.5%) patients and was required during ICU stay in 85.8% of patients. 60-day mortality was 33.9% (IQR across units: 20%-50%) and ICU mortality 32.7%. Older age, invasive mechanical ventilation, and acute kidney injury (AKI) were associated with increased mortality. These associations were also confirmed specifically in mechanically ventilated patients. Admission to surge capacity beds was not associated with mortality, even after controlling for other factors. CONCLUSIONS: ICUs responded to the increase in COVID-19 patients by increasing bed availability and staff, admitting up to 40% of patients in surge capacity beds. Although mortality in this population was high, admission to a surge capacity bed was not associated with increased mortality. Older age, invasive mechanical ventilation, and AKI were identified as the strongest predictors of mortality.

Early prediction of SARS-CoV-2 reproductive number from environmental, atmospheric and mobility data: A supervised machine learning approach.

INTRODUCTION: SARS-CoV-2 was declared a pandemic by the WHO on March 11th, 2020. Public protective measures were enforced in every country to limit the diffusion of SARS-CoV-2. Its transmission, mainly by droplets, has been measured by the effective reproduction number (Rt) that counts the number of secondary cases caused in a population by an average infectious individual at time t. Current strategies to calculate Rt reflect the number of secondary cases after several days, due to a delay from symptoms onset to reporting. We propose a complementary Rt estimation using supervised machine learning techniques to predict short term variations with more timely results. MATERIAL AND METHODS: Our primary goal was to predict Rt of the current day in the twelve provinces of Lombardy with the highest possible accuracy, and with no influence of the local testing strategies. We gathered data about mobility, weather, and pollution from different public sources as a proxy of human behavior and public health measures. We built four supervised machine learning algorithms with different strategies: the outcome variable was the daily median Rt values per province obtained from officially adopted algorithms. RESULTS: Data from 243 days for every province were presented to our four models (from February 15th, 2020, to October 14th, 2020). Two models using differential calculation of Rt instead of the raw values showed the highest mean coefficient of determination (0.93 for both) and residuals reported the lowest mean error (-0.03 and 0.01) and standard deviation (0.13 for both) as well. The one with access to the value of Rt of the day before heavily relied on that feature for prediction, while the other one had more distributed weights. DISCUSSION: The model that had not access to the Rt value of the previous day and used Rt differential value as outcome (FDRt) was considered the most robust according to the metrics. Its forecasts were able to predict the trend that Rt values would have developed over different weeks, but it was not particularly accurate in predicting the precise value of Rt. A correlation among mobility, atmospheric, features, pollution and Rt values is plausible, but further testing should be performed.

Clinical Outcomes in the Second versus First Pandemic Wave in Italy: Impact of Hospital Changes and Reorganization

The region of Lombardy was the epicenter of the COVID-19 outbreak in Italy. Emergency Hospital 19 (EH19) was built in the Milan metropolitan area during the pandemic’s second wave as a facility of Humanitas Clinical and Research Center (HCRC). The present study aimed to assess whether the implementation of EH19 was effective in improving the quality of care of COVID-19 patients during the second wave compared with the first one. The demographics, mortality rate, and in-hospital length of stay (LOS) of two groups of patients were compared: the study group involved patients admitted at HCRC and managed in EH19 during the second pandemic wave, while the control group included patients managed exclusively at HCRC throughout the first wave. The study and control group included 903 (56.7%) and 690 (43.3%) patients, respectively. The study group was six years older on average and had more pre-existing comorbidities. EH19 was associated with a decrease in the intensive care unit admission rate (16.9% vs. 8.75%, p <0.001), and an equal decrease in invasive oxygen therapy (3.8% vs. 0.23%, p <0.001). Crude mortality was similar but overlap propensity score weighting revealed a trend toward a potential small decrease. The adjusted difference in LOS was not significant. The implementation of an additional COVID-19 hospital facility was effective in improving the overall quality of care of COVID-19 patients during the first wave of the pandemic when compared with the second. Further studies are necessary to validate the suggested approach.

The effect of COVID-19 epidemic on vital signs in hospitalized patients: a pre-post heat-map study from a large teaching hospital.

The Lombardy SARS-CoV-2 outbreak in February 2020 represented the beginning of COVID-19 epidemic in Italy. Hospitals were flooded by thousands of patients with bilateral pneumonia and severe respiratory, and vital sign derangements compared to the standard hospital population. We propose a new visual analysis technique using heat maps to describe the impact of COVID-19 epidemic on vital sign anomalies in hospitalized patients. We conducted an electronic health record study, including all confirmed COVID-19 patients hospitalized from February 21st, 2020 to April 21st, 2020 as cases, and all non-COVID-19 patients hospitalized in the same wards from January 1st, 2018 to December 31st, 2018. All data on temperature, peripheral oxygen saturation, respiratory rate, arterial blood pressure, and heart rate were retrieved. Derangement of vital signs was defined according to predefined thresholds. 470 COVID-19 patients and 9241 controls were included. Cases were older than controls, with a median age of 79 vs 76 years in non survivors (p = < 0.002). Gender was not associated with mortality. Overall mortality in COVID-19 hospitalized patients was 18%, ranging from 1.4% in patients below 65 years to about 30% in patients over 65 years. Heat maps analysis demonstrated that COVID-19 patients had an increased frequency in episodes of compromised respiratory rate, acute desaturation, and fever. COVID-19 epidemic profoundly affected the incidence of severe derangements in vital signs in a large academic hospital. We validated heat maps as a method to analyze the clinical stability of hospitalized patients. This method may help to improve resource allocation according to patient characteristics.

Hospital-Acquired Infections in Critically Ill Patients With COVID-19.

BACKGROUND: Few small studies have described hospital-acquired infections (HAIs) occurring in patients with COVID-19. RESEARCH QUESTION: What characteristics in critically ill patients with COVID-19 are associated with HAIs and how are HAIs associated with outcomes in these patients? STUDY DESIGN AND METHODS: Multicenter retrospective analysis of prospectively collected data including adult patients with severe COVID-19 admitted to eight Italian hub hospitals from February 20, 2020, through May 20, 2020. Descriptive statistics and univariate and multivariate Weibull regression models were used to assess incidence, microbial cause, resistance patterns, risk factors (ie, demographics, comorbidities, exposure to medication), and impact on outcomes (ie, ICU discharge, length of ICU and hospital stays, and duration of mechanical ventilation) of microbiologically confirmed HAIs. RESULTS: Of the 774 included patients, 359 patients (46%) demonstrated 759 HAIs (44.7 infections/1,000 ICU patient-days; 35% multidrug-resistant [MDR] bacteria). Ventilator-associated pneumonia (VAP; n = 389 [50%]), bloodstream infections (BSIs; n = 183 [34%]), and catheter-related BSIs (n = 74 [10%]) were the most frequent HAIs, with 26.0 (95% CI, 23.6-28.8) VAPs per 1,000 intubation-days, 11.7 (95% CI, 10.1-13.5) BSIs per 1,000 ICU patient-days, and 4.7 (95% CI, 3.8-5.9) catheter-related BSIs per 1,000 ICU patient-days. Gram-negative bacteria (especially Enterobacterales) and Staphylococcus aureus caused 64% and 28% of cases of VAP, respectively. Variables independently associated with infection were age, positive end expiratory pressure, and treatment with broad-spectrum antibiotics at admission. Two hundred thirty-four patients (30%) died in the ICU (15.3 deaths/1,000 ICU patient-days). Patients with HAIs complicated by septic shock showed an almost doubled mortality rate (52% vs 29%), whereas noncomplicated infections did not affect mortality. HAIs prolonged mechanical ventilation (median, 24 days [interquartile range (IQR), 14-39 days] vs 9 days [IQR, 5-13 days]; P < .001), ICU stay (24 days [IQR, 16-41 days] vs 9 days [IQR, 6-14 days]; P = .003), and hospital stay (42 days [IQR, 25-59 days] vs 23 days [IQR, 13-34 days]; P < .001). INTERPRETATION: Critically ill patients with COVID-19 are at high risk for HAIs, especially VAPs and BSIs resulting from MDR organisms. HAIs prolong mechanical ventilation and hospitalization, and HAIs complicated by septic shock almost double mortality. TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT04388670; URL: www.clinicaltrials.gov.

Critical Care Outreach Team During COVID-19: Ventilatory Support in the Ward and Outcomes.

BACKGROUND: During the coronavirus disease 2019 (COVID-19) outbreak, a critical care outreach team was implemented in our hospital to guarantee multidisciplinary patient assessment at admission and prompt ICU support in medical wards. In this paper, we report the activity plan results and describe the baseline characteristics of the referred subjects. METHODS: We retrospectively evaluated data from 125 subjects referred to the critical care outreach team from March 22 to April 22, 2020. We considered subjects with a ceiling of care decision, with those deemed eligible assigned to level 3 care (ward subgroup), and those deemed ineligible admitted to the ICU (ICU subgroup). Quality indicators of the outreach team plan delivery included number of cardiac arrest calls, number of intubations in level 2 areas, and ineffective palliative support. RESULTS: We enrolled 125 consecutive adult subjects with a confirmed diagnosis of COVID-19. We did not report any emergency endotracheal intubations in the clinical ward. In the care ceiling subgroup, we had 2 (3.3%) emergency calls for cardiac arrest, whereas signs of ineffective palliative support were reported in 5 subjects (12.5%). Noninvasive forms of respiratory assistance were delivered to 40.0% of subjects in the ward subgroup (median 3 d [interquartile range (IQR) 2-5]), to 45.9% of subjects in the care ceiling subgroup (median 5 d [IQR 3-7]), and to 64.7% of subjects in the ICU subgroup (median 2.5 d [IQR 1-3]). Thirty of the 31 ward subjects (96.7%), 26 of the 34 ICU subjects, (76.4%), and 19 of the 61 ceiling of care subjects (31.1%) were discharged. CONCLUSIONS: In the context of a hospital and ICU surge, a multidisciplinary daily plan supported by a dedicated critical care outreach team was associated with a low rate of cardiac arrest calls, no emergency intubations in the ward, and appropriate palliative care support for subjects with a ceiling of care decision.

Surviving Sepsis Campaign Guidelines on the Management of Adults With Coronavirus Disease 2019 (COVID-19) in the ICU: First Update.

BACKGROUND: The coronavirus disease 2019 pandemic continues to affect millions worldwide. Given the rapidly growing evidence base, we implemented a living guideline model to provide guidance on the management of patients with severe or critical coronavirus disease 2019 in the ICU. METHODS: The Surviving Sepsis Campaign Coronavirus Disease 2019 panel has expanded to include 43 experts from 14 countries; all panel members completed an electronic conflict-of-interest disclosure form. In this update, the panel addressed nine questions relevant to managing severe or critical coronavirus disease 2019 in the ICU. We used the World Health Organization's definition of severe and critical coronavirus disease 2019. The systematic reviews team searched the literature for relevant evidence, aiming to identify systematic reviews and clinical trials. When appropriate, we performed a random-effects meta-analysis to summarize treatment effects. We assessed the quality of the evidence using the Grading of Recommendations, Assessment, Development, and Evaluation approach, then used the evidence-to-decision framework to generate recommendations based on the balance between benefit and harm, resource and cost implications, equity, and feasibility. RESULTS: The Surviving Sepsis Campaign Coronavirus Diease 2019 panel issued nine statements (three new and six updated) related to ICU patients with severe or critical coronavirus disease 2019. For severe or critical coronavirus disease 2019, the panel strongly recommends using systemic corticosteroids and venous thromboprophylaxis but strongly recommends against using hydroxychloroquine. In addition, the panel suggests using dexamethasone (compared with other corticosteroids) and suggests against using convalescent plasma and therapeutic anticoagulation outside clinical trials. The Surviving Sepsis Campaign Coronavirus Diease 2019 panel suggests using remdesivir in nonventilated patients with severe coronavirus disease 2019 and suggests against starting remdesivir in patients with critical coronavirus disease 2019 outside clinical trials. Because of insufficient evidence, the panel did not issue a recommendation on the use of awake prone positioning. CONCLUSION: The Surviving Sepsis Campaign Coronavirus Diease 2019 panel issued several recommendations to guide healthcare professionals caring for adults with critical or severe coronavirus disease 2019 in the ICU. Based on a living guideline model the recommendations will be updated as new evidence becomes available.

Risk Factors Associated With Mortality Among Patients With COVID-19 in Intensive Care Units in Lombardy, Italy.

Importance: Many patients with coronavirus disease 2019 (COVID-19) are critically ill and require care in the intensive care unit (ICU). Objective: To evaluate the independent risk factors associated with mortality of patients with COVID-19 requiring treatment in ICUs in the Lombardy region of Italy. Design, Setting, and Participants: This retrospective, observational cohort study included 3988 consecutive critically ill patients with laboratory-confirmed COVID-19 referred for ICU admission to the coordinating center (Fondazione IRCCS [Istituto di Ricovero e Cura a Carattere Scientifico] Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy) of the COVID-19 Lombardy ICU Network from February 20 to April 22, 2020. Infection with severe acute respiratory syndrome coronavirus 2 was confirmed by real-time reverse transcriptase-polymerase chain reaction assay of nasopharyngeal swabs. Follow-up was completed on May 30, 2020. Exposures: Baseline characteristics, comorbidities, long-term medications, and ventilatory support at ICU admission. Main Outcomes and Measures: Time to death in days from ICU admission to hospital discharge. The independent risk factors associated with mortality were evaluated with a multivariable Cox proportional hazards regression. Results: Of the 3988 patients included in this cohort study, the median age was 63 (interquartile range [IQR] 56-69) years; 3188 (79.9%; 95% CI, 78.7%-81.1%) were men, and 1998 of 3300 (60.5%; 95% CI, 58.9%-62.2%) had at least 1 comorbidity. At ICU admission, 2929 patients (87.3%; 95% CI, 86.1%-88.4%) required invasive mechanical ventilation (IMV). The median follow-up was 44 (95% CI, 40-47; IQR, 11-69; range, 0-100) days; median time from symptoms onset to ICU admission was 10 (95% CI, 9-10; IQR, 6-14) days; median length of ICU stay was 12 (95% CI, 12-13; IQR, 6-21) days; and median length of IMV was 10 (95% CI, 10-11; IQR, 6-17) days. Cumulative observation time was 164 305 patient-days. Hospital and ICU mortality rates were 12 (95% CI, 11-12) and 27 (95% CI, 26-29) per 1000 patients-days, respectively. In the subgroup of the first 1715 patients, as of May 30, 2020, 865 (50.4%) had been discharged from the ICU, 836 (48.7%) had died in the ICU, and 14 (0.8%) were still in the ICU; overall, 915 patients (53.4%) died in the hospital. Independent risk factors associated with mortality included older age (hazard ratio [HR], 1.75; 95% CI, 1.60-1.92), male sex (HR, 1.57; 95% CI, 1.31-1.88), high fraction of inspired oxygen (Fio2) (HR, 1.14; 95% CI, 1.10-1.19), high positive end-expiratory pressure (HR, 1.04; 95% CI, 1.01-1.06) or low Pao2:Fio2 ratio (HR, 0.80; 95% CI, 0.74-0.87) on ICU admission, and history of chronic obstructive pulmonary disease (HR, 1.68; 95% CI, 1.28-2.19), hypercholesterolemia (HR, 1.25; 95% CI, 1.02-1.52), and type 2 diabetes (HR, 1.18; 95% CI, 1.01-1.39). No medication was independently associated with mortality (angiotensin-converting enzyme inhibitors HR, 1.17; 95% CI, 0.97-1.42; angiotensin receptor blockers HR, 1.05; 95% CI, 0.85-1.29). Conclusions and Relevance: In this retrospective cohort study of critically ill patients admitted to ICUs in Lombardy, Italy, with laboratory-confirmed COVID-19, most patients required IMV. The mortality rate and absolute mortality were high.

Barotrauma in mechanically ventilated patients with Coronavirus disease 2019: a survey of 38 hospitals in Lombardy, Italy.

BACKGROUND: The aim was to describe the incidence and risk factors of barotrauma in patients with the Coronavirus disease 2019 (COVID-19) on invasive mechanical ventilation, during the outbreak in our region (Lombardy, Italy). METHODS: The study was an electronic survey open from March 27th to May 2nd, 2020. Patients with COVID-19 who developed barotrauma while on invasive mechanical ventilation from 61 hospitals of the COVID-19 Lombardy Intensive Care Unit network were involved. RESULTS: The response rate was 38/61 (62%). The incidence of barotrauma was 145/2041 (7.1%; 95%-CI: 6.1-8.3%). Only a few cases occurred with ventilatory settings that may be considered non-protective such as a plateau airway pressure >35 cmH2O (2/113 [2%]), a driving airway pressure >15 cmH2O (30/113 [27%]), or a tidal volume >8 mL/kg of ideal body weight and a plateau airway pressure >30 cmH2O (12/134 [9%]). CONCLUSIONS: Within the limits of a survey, patients with COVID-19 might be at high risk for barotrauma during invasive (and allegedly lung-protective) mechanical ventilation.

Blood purification therapy with a hemodiafilter featuring enhanced adsorptive properties for cytokine removal in patients presenting COVID-19: a pilot study.

BACKGROUND: Systemic inflammation in COVID-19 often leads to multiple organ failure, including acute kidney injury (AKI). Renal replacement therapy (RRT) in combination with sequential extracorporeal blood purification therapies (EBP) might support renal function, attenuate systemic inflammation, and prevent or mitigate multiple organ dysfunctions in COVID-19. AIM: Describe overtime variations of clinical and biochemical features of critically ill patients with COVID-19 treated with EBP with a hemodiafilter characterized by enhanced cytokine adsorption properties. METHODS: An observational prospective study assessing the outcome of patients with COVID-19 admitted to the ICU (February to April 2020) treated with EBP according to local practice. Main endpoints included overtime variation of IL-6 and multiorgan function-scores, mortality, and occurrence of technical complications or adverse events. RESULTS: The study evaluated 37 patients. Median baseline IL-6 was 1230 pg/ml (IQR 895) and decreased overtime (p < 0.001 Kruskal-Wallis test) during the first 72 h of the treatment, with the most significant decrease in the first 24 h (p = 0.001). The reduction in serum IL-6 concentrations correlated with the improvement in organ function, as measured in the decrease of SOFA score (rho = 0.48, p = 0.0003). Median baseline SOFA was 13 (IQR 6) and decreased significantly overtime (p < 0.001 at Kruskal-Wallis test) during the first 72 h of the treatment, with the most significant decrease in the first 48 h (median 8 IQR 5, p = 0.001). Compared to the expected mortality rates, as calculated by APACHE IV, the mean observed rates were 8.3% lower after treatment. The best improvement in mortality rate was observed in patients receiving EBP early on during the ICU stay. Premature clotting (running < 24 h) occurred in patients (18.9% of total) which featured higher effluent dose (median 33.6 ml/kg/h, IQR 9) and higher filtration fraction (median 31%, IQR 7.4). No electrolyte disorders, catheter displacement, circuit disconnection, unexpected bleeding, air, or thromboembolisms due to venous cannulation of EBP were recorded during the treatment. In one case, infection of vascular access occurred during RRT, requiring replacement. CONCLUSIONS: EBP with heparin-coated hemodiafilter featuring cytokine adsorption properties administered to patients with COVID-19 showed to be feasible and with no adverse events. During the treatment, patients experienced serum IL-6 level reduction, attenuation of systemic inflammation, multiorgan dysfunction improvement, and reduction in expected ICU mortality rate.

Early Predictors of Clinical Deterioration in a Cohort of 239 Patients Hospitalized for Covid-19 Infection in Lombardy, Italy.

We described features of hospitalized Covid-19 patients and identified predictors of clinical deterioration. We included patients consecutively admitted at Humanitas Research Hospital (Rozzano, Milan, Italy); retrospectively extracted demographic; clinical; laboratory and imaging findings at admission; used survival methods to identify factors associated with clinical deterioration (defined as intensive care unit (ICU) transfer or death), and developed a prognostic index. Overall; we analyzed 239 patients (29.3% females) with a mean age of 63.9 (standard deviation [SD]; 14.0) years. Clinical deterioration occurred in 70 patients (29.3%), including 41 (17.2%) ICU transfers and 36 (15.1%) deaths. The most common symptoms and signs at admission were cough (77.8%) and elevated respiratory rate (34.1%), while 66.5% of patients had at least one coexisting medical condition. Imaging frequently revealed ground-glass opacity (68.9%) and consolidation (23.8%). Age; increased respiratory rate; abnormal blood gas parameters and imaging findings; coexisting coronary heart disease; leukocytosis; lymphocytopenia; and several laboratory parameters (elevated procalcitonin; interleukin-6; serum ferritin; C-reactive protein; aspartate aminotransferase; lactate dehydrogenase; creatinine; fibrinogen; troponin-I; and D-dimer) were significant predictors of clinical deterioration. We suggested a prognostic index to assist risk-stratification (C-statistic; 0.845; 95% CI; 0.802‒0.887). These results could aid early identification and management of patients at risk, who should therefore receive additional monitoring and aggressive supportive care.

Surviving Sepsis Campaign: guidelines on the management of critically ill adults with Coronavirus Disease 2019 (COVID-19).

BACKGROUND: The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of a rapidly spreading illness, Coronavirus Disease 2019 (COVID-19), affecting thousands of people around the world. Urgent guidance for clinicians caring for the sickest of these patients is needed. METHODS: We formed a panel of 36 experts from 12 countries. All panel members completed the World Health Organization conflict of interest disclosure form. The panel proposed 53 questions that are relevant to the management of COVID-19 in the ICU. We searched the literature for direct and indirect evidence on the management of COVID-19 in critically ill patients in the ICU. We identified relevant and recent systematic reviews on most questions relating to supportive care. We assessed the certainty in the evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach, then generated recommendations based on the balance between benefit and harm, resource and cost implications, equity, and feasibility. Recommendations were either strong or weak, or in the form of best practice recommendations. RESULTS: The Surviving Sepsis Campaign COVID-19 panel issued 54 statements, of which 4 are best practice statements, 9 are strong recommendations, and 35 are weak recommendations. No recommendation was provided for 6 questions. The topics were: (1) infection control, (2) laboratory diagnosis and specimens, (3) hemodynamic support, (4) ventilatory support, and (5) COVID-19 therapy. CONCLUSION: The Surviving Sepsis Campaign COVID-19 panel issued several recommendations to help support healthcare workers caring for critically ill ICU patients with COVID-19. When available, we will provide new recommendations in further releases of these guidelines.