Risk Factors for 28-Day in-Hospital Mortality in Mechanically Ventilated Patients with COVID-19: An International Cohort Study (preprint)

Background: Risk factors associated with mortality in patients with coronavirus disease 2019 (COVID-19) on mechanical ventilation are still not fully elucidated. Thus, we aimed to identify patient-level factors, readily available at the bedside, associated with the risk of in-hospital mortality within 28 days from commencement of invasive mechanical ventilation (28-day IMV mortality) in patients with COVID-19. Methods: Prospective observational cohort study in 148 intensive care units in the global COVID-19 Critical Care Consortium . Patients with clinically suspected or laboratory confirmed COVID-19 infection admitted to the intensive care unit (ICU) from February 2 nd through December 29th, 2020, requiring IMV. No study-specific interventions were performed. Patient characteristics and clinical data were assessed upon ICU admission, the commencement of IMV and for 28 days thereafter. We primarily aimed to identify time-independent and time-dependent risk factors for 28-day IMV mortality. Results: : A total of 1713 patients were included in the survival analysis, 588 patients died in hospital within 28 days of commencing IMV (34.3%). Cox-regression analysis identified associations between the hazard of 28-day IMV mortality with age (HR 1.27 per 10-year increase in age, 95% CI 1.17 to 1.37, P<0.001), PEEP upon commencement of IMV (HR 0.78 per 5-cmH 2 O increase, 95% CI 0.66-0.93, P=0.005). Time-dependent parameters associated with 28-day IMV mortality were serum creatinine (HR 1.30 per doubling, 95% CI 1.19-1.42, P<0.001), lactate (HR 1.16 per doubling, 95% CI 1.06-1.27 P=0.001), PaCO 2 (HR 1.31 per doubling, 95% CI 1.05-1.64, P=0.015), pH (HR 0.82 per 0.1 increase, 95% CI 0.74-0.91, P<0.001), PaO 2 /FiO 2 (HR 0.56 per doubling, 95% CI 0.50-0.62, P<0.001) and mean arterial pressure (HR 0.92 per 10 mmHg increase, 95% CI 0.88-0.97, P=0.002). Conclusions: : This international study establishes that in mechanically ventilated patients with COVID-19, older age and clinically relevant variables monitored at the bedside are risk factors for 28-day IMV mortality. Further investigation is warranted to validate any causative roles these parameters might play in influencing clinical outcomes.

New susceptibility loci for severe COVID-19 by detailed GWAS analysis in European populations (preprint)

Due to the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), deepening the host genetic contribution to severe COVID-19 may further improve our understanding about underlying disease mechanisms. Here, we describe an extended GWAS meta-analysis of 3,260 COVID-19 patients with respiratory failure and 12,483 population controls from Italy, Spain, Norway and Germany, as well as hypothesis-driven targeted analysis of the human leukocyte antigen (HLA) region and chromosome Y haplotypes. We include detailed stratified analyses based on age, sex and disease severity. In addition to already established risk loci, our data identify and replicate two genome-wide significant loci at 17q21.31 and 19q13.33 associated with severe COVID-19 with respiratory failure. These associations implicate a highly pleiotropic ~0.9-Mb 17q21.31 inversion polymorphism, which affects lung function and immune and blood cell counts, and the NAPSA gene, involved in lung surfactant protein production, in COVID-19 pathogenesis.

Rationale for Polyclonal Intravenous Immunoglobulin Adjunctive Therapy in Covid19 Patients: Report of a Structured Multidisciplinary Consensus (preprint)

Adjunctive therapy with polyclonal intravenous immunoglobins (IVIg) is currently used for preventing or managing infections and sepsis, especially in immunocompromised patients. The pathobiology of COVID19 and the mechanisms of action of Ig led to consider this adjunctive therapy also in patients with respiratory failure by SARS-CoV2 infection. This manuscript report the rationale, the available data and the results of a structured consensus on intravenous Ig therapy in patients with severe COVID19. METHODS A panel of multidisciplinary experts defined the clinical phenotypes of COVID19 patients with severe respiratory failure and, after literature review, voted for the agreement on the rationale and the potential role of IVIg therapy for each phenotype. Due to the scarce evidence available, a modified RAND/UCLA appropriateness method was used. RESULTS Three different phenotypes of COVID19 patients with severe respiratory failure were identified: patients with an abrupt and dysregulated hyperinflammatory response (early phase), patients with suspected immune-paralysis (late phase), and patients with sepsis by hospital-acquired superinfection (sepsis by bacterial superinfection). The rationale for intravenous Ig therapy in the early phase was considered uncertain whereas the panellists considered appropriate its use in the late phase and patients with sepsis/septic shock by bacterial superinfection. CONCLUSION As with other immunotherapies, IVIg adjunctive therapy may a potential role in the managing of COVID19 patients. The ongoing trials will clarify the appropriate target population and the true effectiveness.

Artificial Intelligence to Predict Mortality in Critically ill COVID-19 Patients Using Data from the First 24h: A Case Study from Lombardy Outbreak (preprint)

Introduction: SARS-CoV-2 infection was first identified at the end of 2019 in China, and subsequently spread globally. 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, considering that baseline comorbidities, age, and patient conditions at admission have been associated to poorer outcomes. Supervised machine learning techniques are increasingly diffuse in clinical medicine and can predict mortality and test associations reaching high predictive performance. We assessed performances of a machine learning approach to predict mortality in COVID-19 patients admitted to ICU using data from the Lombardy ICU Network.Methods: this is a secondary analysis of prospectively collected data from Lombardy ICU network. To predict survival at 7-,14- and 28 days we built two different models; model A included patient demographics, medications before admission and comorbidities, while model B also included the data of the first day since ICU admission. 10-fold cross validation was repeated 2500 times, to ensure optimal hyperparameter choice. The only constrain imposed to model optimization was the choice of logistic regression as final layer to increase clinical interpretability. Different imputation and over-sampling techniques were employed in model training.Results 1503 patients were included, with 766 deaths (51%). Exploratory analysis and Kaplan-Meier curves demonstrated mortality association with age and gender. Model A and B reached the greatest predictive performance at 28 days (AUC 0.77 and 0.79), with lower performance at 14 days (AUC 0.72 and 0.74) and 7 days (AUC 0.68 and 0.71). Male gender, age and number of comorbidities were strongly associated with mortality in both models. Among comorbidities, chronic kidney disease and chronic obstructive pulmonary disease demonstrated association. Mode of ventilatory assistance at ICU admission and Fraction of Inspired oxygen were associated with mortality in model B.Conclusions Supervised machine learning models demonstrated good performance in prediction of 28-day mortality. 7-days and 14-days predictions demonstrated lower performance. Machine learning techniques may be useful in emergency phases to reach higher predictive performance with reduced human supervision using complex data.

Decreasing hospital burden of COVID-19 during the first wave in Regione Lombardia: an emergency measures context (preprint)

Background: The aim of this study is to quantify the hospital burden of COVID-19 during the first wave and how it changed over calendar time; to interpret the results in light of the emergency measures introduced to manage the strain on secondary healthcare. Methods: : This is a cohort study of hospitalised confirmed cases of COVID-19 admitted from February-June 2020 and followed up till 17th July 2020, analysed using a mixture multi-state model. All hospital patients with confirmed COVID-19 disease in Regione Lombardia were involved, admitted from February-June 2020, with non-missing hospital of admission and non-missing admission date. Results: : The cohort consists of 40,550 patients hospitalised during the first wave. These patients had a median age of 69 (interquartile range 56-80) and were more likely to be men (60%) than women (40%). The hospital-fatality risk, averaged over all pathways through hospital, was 27.5% (95% CI 27.1-28.0%); and steadily decreased from 34.6% (32.5-36.6%) in February to 7.6% (6.3-10.6%) in June. Among surviving patients, median length of stay in hospital was 11.8 (11.6-12.3) days, compared to 8.1 (7.8-8.5) days in non-survivors. Averaged over final outcomes, median length of stay in hospital decreased from 21.4 (20.5-22.8) days in February to 5.2 (4.7-5.8) days in June. Conclusions: : The hospital burden, in terms of both risks of poor outcomes and lengths of stay in hospital, has been demonstrated to have decreased over the months of the first wave, perhaps reflecting improved treatment and management of COVID-19 cases, as well as reduced burden as the first wave waned. The quantified burden allows for planning of hospital beds needed for current and future waves of SARS-CoV-2.

Risk Factors for Severe Hospital Burden During the First Wave of COVID-19 Disease in Regione Lombardia (preprint)

Background: Understanding the risk factors associated with hospital burden of COVID-19 is crucial for healthcare planning for any future waves of infection.Methods: An observational cohort study is performed, using data on all RT-PCR confirmed cases of COVID-19 in Regione Lombardia, Italy, during the first wave of infection from February-June 2020. A multi-state modelling approach is used to simultaneously estimate risks of progression through hospital to final outcomes of either death or discharge, by pathway (via critical care or not) and the times to final events (lengths of stay). Logistic and time-to-event regressions are used to quantify the association of patient and population characteristics with the risks of hospital outcomes and lengths of stay respectively.Findings: Risks of severe outcomes such as ICU admission and mortality have decreased with month of admission and increased with age. Care home residents aged 65+ are at increased risk of hospital mortality and decreased risk of ICU admission. Being a healthcare worker appears to have a protective effect on mortality risk and length of stay. Lengths of stay decrease with month of admission for survivors, but do not appear to vary with month for non-survivors.Interpretation: Improvements in clinical knowledge, treatment, patient and hospital management and public health surveillance, together with the waning of the first wave after the first lockdown, are hypothesised to have contributed to the reduced risks and lengths of stay over time.Funding: This work has been funded by the Medical Research Council (De Angelis, Jackson, Presanis: Unit programme number MC UU 00002/11; Kunzmann: Unit programme number MC_UU_00002/10); and the UKRI-MRC COVID-19 Rapid Call (Presanis, De Angelis, grant no MC_PC_19074).Declaration of Interests: None to declare.

Prone Position in Intubated, Mechanically Ventilated Patients with Coronavirus Disease-19. (preprint)

Background: Limited data are available on the use of prone position in intubated, invasively ventilated patients with Coronavirus disease-19 (COVID-19). Aim of this study is to investigate the use and effect of prone position in this population during the first 2020 pandemic wave.Methods: Retrospective, multicentre, national cohort study conducted between February 24 and June 14, 2020 in 24 Italian Intensive Care Units (ICU) on adult patients needing invasive mechanical ventilation for respiratory failure caused by COVID-19.Clinical data were collected on the day of ICU admission. Information regarding the use of prone position were collected daily. Follow-up for patient outcomes was performed on July 15, 2020. The respiratory effects of the first prone position were studied in a subset of 78 patients. Patients were classified as Responders if the PaO2/FiO2 ratio increased ≥ 20 mmHg during prone position. Results:  Of 1057 included patients, mild, moderate and severe ARDS was present in 15, 50 and 35% of patients, respectively and had a resulting mortality of 25, 33 and 41%. Prone position was applied in 61% of the patients. Patients placed prone had a more severe disease and died significantly more (45% vs 33%, p<0.001). Overall, prone position induced a significant increase in PaO2/FiO2 ratio, while no change in respiratory system compliance was observed. Seventy-eight % of patients were Responders to prone position. Non-Responders had a more severe respiratory failure and died more often in the ICU (65% vs. 38%, p=0.047).Conclusions: During the COVID-19 pandemic, prone position has been widely adopted to treat mechanically ventilated patients with respiratory failure. The majority of patients improved their oxygenation during prone position, most likely due to a better ventilation perfusion matching.Trial registration: clinicaltrials.gov  number: NCT04388670

Healthcare strain and intensive care during the COVID-19 outbreak in the Lombardy region: a retrospective observational study on 43,538 hospitalized patients (preprint)

Background. During the spring of 2020, the SARS-CoV-2 epidemic has caused significant resource strain in hospitals of Lombardy, Italy, with the demand for intensive care beds for COVID-19 patients exceeding the overall pre-crisis capacity. In this study, we evaluate the effect of healthcare strain on ICU admission and survival. Methods. We used data on 43,538 patients admitted to a hospital in the region between February 20 and July 12, 2020, of which 3,993 (9.2%) were admitted to an ICU. We applied logistic regression to model the probability of being admitted to an ICU and the probability of survival among ICU patients. Negative binomial regressions were used to model the time between hospital and ICU admission and the length of stay in ICU. Results. During the period of highest hospital strain (March 16 - April 22), individuals older than 70 years had a significantly lower probability of being admitted to an ICU and significantly longer times between hospital and ICU admission, indicating elective admission due to constrained resources. Healthcare strain did not have a clear effect on mortality, with the overall proportion of deaths declining from 52.1% (95%CI 49.8-54.5) for ICU patients admitted to the hospital before March 16, to 43.4% (95%CI 41.5-45.6) between March 16 and April 22, to 27.6% (95%CI 20.0-35.2) after April 22. Conclusions. These data demonstrate and quantify the adoption of elective admission to ICUs during the peak phase of the SARS-CoV-2 epidemic in Lombardy. However, we show that for patients admitted to ICUs, clinical outcomes progressively improved despite the saturation of healthcare resources.

Infection fatality ratio of SARS-CoV-2 in Italy (preprint)

We analyzed 5,484 close contacts of COVID-19 cases from Italy, all of them tested for SARS-CoV-2 infection. We found an infection fatality ratio of 2.2% (95%CI 1.69-2.81%) and identified male sex, age >70 years, cardiovascular comorbidities, and infection early in the epidemics as risk factors for death.

Early Detection Of Deep Vein Thrombosis In Patients With Coronavirus Disease 2019: Who to Screen and Who not to with Doppler Ultrasound? (preprint)

BACKGROUND. Aim of the study is to evaluate the incidence of DVT in COVID-19 patients and its correlation with the severity of the disease and with clinical and laboratory findings.METHODS. 234 symptomatic patients with COVID-19, diagnosed according to the World Health Organization guidelines, were included in the study. The severity of the disease was classified as moderate, severe and critical. Doppler ultrasound (DUS) was performed in all patients. DUS findings, clinical, laboratory’s and therapeutic variables were investigated by contingency tables, Pearson chi square test and by Student T test and Fisher's exact test. ROC curve analysis was applied to study significant continuous variables.RESULTS. Overall incidence of DVT was 10.7% (25/234): 1.6% (1/60) among moderate cases, 13.8% (24/174) in severely and critically ill patients. Prolonged bedrest and intensive care unit admission were significantly associated with the presence of DVT (19.7%). Fraction of inspired oxygen, P/F ratio, respiratory rate, heparin administration, D-dimer, IL-6, ferritin and CRP showed correlation with DVT. CONCLUSIONS. DUS may be considered a useful and valid tool for early identification of DVT. In less severely affected patients, DUS as screening of DVT might be unnecessary. High rate of DVT found in severe patients and its correlation with respiratory parameters and some significant laboratory findings suggests that these can be used as a screening tool for patients who should be getting DUS.

The ABO blood group locus and a chromosome 3 gene cluster associate with SARS-CoV-2 respiratory failure in an Italian-Spanish genome-wide association analysis (preprint)

Background. Respiratory failure is a key feature of severe Covid-19 and a critical driver of mortality, but for reasons poorly defined affects less than 10% of SARS-CoV-2 infected patients. Methods. We included 1,980 patients with Covid-19 respiratory failure at seven centers in the Italian and Spanish epicenters of the SARS-CoV-2 pandemic in Europe (Milan, Monza, Madrid, San Sebastian and Barcelona) for a genome-wide association analysis. After quality control and exclusion of population outliers, 835 patients and 1,255 population-derived controls from Italy, and 775 patients and 950 controls from Spain were included in the final analysis. In total we analyzed 8,582,968 single-nucleotide polymorphisms (SNPs) and conducted a meta-analysis of both case-control panels. Results. We detected cross-replicating associations with rs11385942 at chromosome 3p21.31 and rs657152 at 9q34, which were genome-wide significant (P<5x10-8) in the meta-analysis of both study panels, odds ratio [OR], 1.77; 95% confidence interval [CI], 1.48 to 2.11; P=1.14x10-10 and OR 1.32 (95% CI, 1.20 to 1.47; P=4.95x10-8), respectively. Among six genes at 3p21.31, SLC6A20 encodes a known interaction partner with angiotensin converting enzyme 2 (ACE2). The association signal at 9q34 was located at the ABO blood group locus and a blood-group-specific analysis showed higher risk for A-positive individuals (OR=1.45, 95% CI, 1.20 to 1.75, P=1.48x10-4) and a protective effect for blood group O (OR=0.65, 95% CI, 0.53 to 0.79, P=1.06x10-5). Conclusions. We herein report the first robust genetic susceptibility loci for the development of respiratory failure in Covid-19. Identified variants may help guide targeted exploration of severe Covid-19 pathophysiology.

Analysis of the role of Chest X-Ray in a large cohort of 1117 patients with SARS-CoV-2 infection: an Italian multicenter study (preprint)

Objective. To describe the radiographic key patterns on CXR in patients with SARS-CoV-2 infection, assessing the prevalence of radiographic signs of interstitial pneumonia. To evaluate pattern variation between a baseline and a follow-up CXR.Materials and methods. 1117 patients tested positive for SARS-CoV-2 infection were retrospectively enrolled from four centers in Lombardy region. All patients underwent a CXR at presentation. Follow-up CXR was performed when clinically indicated.Two radiologists in each center reviewed CXR images and classified them as suggestive or not for interstitial pneumonia, recording the presence of ground-glass opacity (GGO), reticular pattern or consolidation and their distribution.Pearson’s chi-square test for categorical variables and McNemar test (chi-square for paired data) were performed.Results. Patients mean age 63.3 years, 767 were males (65.5%). The main result is the large proportion of positive CXR in COVID-19 patients.Baseline CXR was positive in 940 patients (80.3%), with significant differences in age and sex distribution between patients with positive and negative CXR. 382 patients underwent a follow-up CXR. The most frequent pattern on baseline CXR was the GGO (66.1%), on follow-up was consolidation (53.4%). The most common distributions were peripheral and middle-lower lung zone.Conclusions. We described key-patterns and their distribution on CXR in a large cohort of COVID-19 patients: GGO was the most frequent finding on baseline CXR, while we found an increase in the proportion of lung consolidation on follow-up CXR. CXR proved to be a reliable tool in our cohort obtaining positive results in 80.3% of the baseline cases.

Early phases of COVID-19 are characterized by a reduction of lymphocyte populations and the presence of atypical monocytes (preprint)

Background Severe acute respiratory syndrome coronavirus 2 is a recently discovered pathogen responsible of coronavirus disease 2019 (COVID-19). The immunological changes associated with this infection are largely unknown. Methods We evaluated the peripheral blood mononuclear cells profile of 63 patients with COVID-19 at diagnosis and the presence of association with inflammatory biomarkers and 28-days mortality. Results Lymphocytopenia was present in 51 of 63 (80.9%) patients. This reduction was mirrored also on CD8+ lymphocytes (128 cells/uL), natural killer cells (67 cells/uL) and natural killer T cells (31 cells/uL). Monocytes were preserved in total number but displayed a subpopulation composed mainly of cells with a reduced expression of both CD14 and HLA-DR. A direct correlation was found between serum values of IL-6 and the frequency of Th2 lymphocytes (R=0.17; p=0.04) but not with the monocytes count (R=0.01; p=0.60). Patients who died in the 28 days from admission (N=10, 15.9%), when compared to those who did not, displayed lower mean values of CD3+ (p=0.028) and CD4+ cells (p=0.042) and higher mean percentages of CD8+/CD38+/HLA-DR+ lymphocytes (p=0.026). Conclusions The early phases of COVID-19 are characterized by lymphocytopenia, predominance of Th2 lymphocytes and less immunocompetent monocytes, which include atypical mononuclear cells.