Uncovering the Benefits of the Ketamine-Dexmedetomidine Combination for Procedural Sedation during the Italian COVID-19 Pandemic.

This retrospective observational study evaluated the safety and efficacy of the ketamine and dexmedetomidine combination (keta-dex) compared to ketamine or dexmedetomidine alone for sedation of patients with acute respiratory distress due to COVID-19 pneumonia who require non-invasive ventilation. The following factors were assessed: tolerance to the ventilation, sedation level on the Richmond Agitation-Sedation Scale (RASS), hemodynamic and saturation profile, adverse effects, and discontinuation or mortality during ventilation. The study included 66 patients who underwent sedation for non-invasive ventilation using keta-dex (KETA-DEX group, n = 22), ketamine (KET group, n = 22), or dexmedetomidine (DEX group, n = 22). The DEX group showed a slower sedation rate and a significant reduction in blood pressure compared to the KETA-DEX group (p < 0.05). An increase in blood pressure was recorded more frequently in the KET group. No reduction in oxygen saturation and no deaths were observed in any of the groups. None of the patients discontinued ventilation due to intolerance. The mean duration of sedation was 28.12 h. No cases of delirium were observed in any of the groups. Overall, keta-dex was associated with faster sedation rates and better hemodynamic profiles compared to dexmedetomidine alone. Keta-dex is effective and safe for sedation of uncooperative patients undergoing non-invasive ventilation.

Five Level Triage vs. Four Level Triage in a Quaternary Emergency Department: National Analysis on Waiting Time, Validity, and Crowding-The CREONTE (Crowding and RE-Organization National TriagE) Study Group.

Background and Objectives: Triage systems help provide the right care at the right time for patients presenting to emergency departments (EDs). Triage systems are generally used to subdivide patients into three to five categories according to the system used, and their performance must be carefully monitored to ensure the best care for patients. Materials and Methods: We examined ED accesses in the context of 4-level (4LT) and 5-level triage systems (5LT), implemented from 1 January 2014 to 31 December 2020. This study assessed the effects of a 5LT on wait times and under-triage (UT) and over-triage (OT). We also examined how 5LT and 4LT systems reflected actual patient acuity by correlating triage codes with severity codes at discharge. Other outcomes included the impact of crowding indices and 5LT system function during the COVID-19 pandemic in the study populations. Results: We evaluated 423,257 ED presentations. Visits to the ED by more fragile and seriously ill individuals increased, with a progressive increase in crowding. The length of stay (LOS), exit block, boarding, and processing times increased, reflecting a net raise in throughput and output factors, with a consequent lengthening of wait times. The decreased UT trend was observed after implementing the 5LT system. Conversely, a slight rise in OT was reported, although this did not affect the medium-high-intensity care area. Conclusions: Introducing a 5LT improved ED performance and patient care.

Prolonged higher dose methylprednisolone vs. conventional dexamethasone in COVID-19 pneumonia: a randomised controlled trial (MEDEAS).

INTRODUCTION: Dysregulated systemic inflammation is the primary driver of mortality in severe COVID-19 pneumonia. Current guidelines favor a 7-10-day course of any glucocorticoid equivalent to dexamethasone 6 mg·day-1. A comparative RCT with a higher dose and a longer duration of intervention was lacking. METHODS: We conducted a multi-center, open-label RCT to investigate methylprednisolone 80 mg as a continuous daily infusion for 8 days followed by slow tapering versus dexamethasone 6 mg daily for up to 10 days in adult patients with COVID-19 pneumonia requiring oxygen or noninvasive respiratory support. PRIMARY OUTCOME: reduction in 28-day mortality. SECONDARY OUTCOMES: mechanical ventilation-free days at 28 days, need for ICU referral, length of hospitalisation, need for tracheostomy, changes in PaO2:FiO2 ratio, C-reactive protein levels and WHO clinical progression scale at days 3, 7, and 14. RESULTS: 677 randomised patients were included. Findings are reported as methylprednisolone (n=337) versus dexamethasone (n=340). By day 28, there were no significant differences in mortality (35[10.4%] versus 41[12.1%]; p=0.49), nor in the median mechanical ventilation-free days (23[14] versus 24[16]; p=0.49). ICU referral was necessary in 41[12.2%] versus 45[13.2%]; p=0.68 and tracheostomy in 8[2.4%] versus 9[2.6%]; p=0.82. Survivors in the methylprednisolone group required a longer median hospitalisation (15[11] versus 14[11] days; p=0.005) and experienced an improvement in C-reactive protein levels, but not in PaO2:FiO2 ratio, at days 7 and 14. There were no differences in disease progression at the prespecified timepoints. CONCLUSION: Prolonged, higher dose methylprednisolone did not reduce mortality at 28 days compared to conventional dexamethasone in COVID-19 pneumonia.

Autoantibodies against chemokines post-SARS-CoV-2 infection correlate with disease course.

Infection with severe acute respiratory syndrome coronavirus 2 associates with diverse symptoms, which can persist for months. While antiviral antibodies are protective, those targeting interferons and other immune factors are associated with adverse coronavirus disease 2019 (COVID-19) outcomes. Here we discovered that antibodies against specific chemokines were omnipresent post-COVID-19, were associated with favorable disease outcome and negatively correlated with the development of long COVID at 1 yr post-infection. Chemokine antibodies were also present in HIV-1 infection and autoimmune disorders, but they targeted different chemokines compared with COVID-19. Monoclonal antibodies derived from COVID-19 convalescents that bound to the chemokine N-loop impaired cell migration. Given the role of chemokines in orchestrating immune cell trafficking, naturally arising chemokine antibodies may modulate the inflammatory response and thus bear therapeutic potential.

Unfavorable Outcome and Long-Term Sequelae in Cases with Severe COVID-19.

Emerging evidence shows that individuals with COVID-19 who survive the acute phase of illness may experience lingering symptoms in the following months. There is no clear indication as to whether these symptoms persist for a short time before resolving or if they persist for a long time. In this review, we will describe the symptoms that persist over time and possible predictors in the acute phase that indicate long-term persistence. Based on the literature available to date, fatigue/weakness, dyspnea, arthromyalgia, depression, anxiety, memory loss, slowing down, difficulty concentrating and insomnia are the most commonly reported persistent long-term symptoms. The extent and persistence of these in long-term follow-up is not clear as there are still no quality studies available. The evidence available today indicates that female subjects and those with a more severe initial disease are more likely to suffer permanent sequelae one year after the acute phase. To understand these complications, and to experiment with interventions and treatments for those at greater risk, we must first understand the physio-pathological mechanisms that sustain them.

Natural Killer Cells in SARS-CoV-2 Infection: Pathophysiology and Therapeutic Implications.

Natural Killer (NK) cells are lymphocytes of the innate immunity that play a crucial role in the control of viral infections in the absence of a prior antigen sensitization. Indeed, they display rapid effector functions against target cells with the capability of direct cell killing and antibody-dependent cell-mediated cytotoxicity. Furthermore, NK cells are endowed with immune-modulatory functions innate and adaptive immune responses via the secretion of chemokines/cytokines and by undertaking synergic crosstalks with other innate immune cells, including monocyte/macrophages, dendritic cells and neutrophils. Recently, the Coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread globally. Although the specific role of NK cells in COVID-19 pathophysiology still need to be explored, mounting evidence indicates that NK cell tissue distribution and effector functions could be affected by SARS-CoV-2 infection and that a prompt NK cell response could determine a good clinical outcome in COVID-19 patients. In this review, we give a comprehensive overview of how SARS-CoV-2 infection interferes with NK cell antiviral effectiveness and their crosstalk with other innate immune cells. We also provide a detailed characterization of the specific NK cell subsets in relation to COVID-19 patient severity generated from publicly available single cell RNA sequencing datasets. Finally, we summarize the possible NK cell-based therapeutic approaches against SARS-CoV-2 infection and the ongoing clinical trials updated at the time of submission of this review. We will also discuss how a deep understanding of NK cell responses could open new possibilities for the treatment and prevention of SARS-CoV-2 infection.

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.

Natural Killer Cells in SARS-CoV-2 Infection: Pathophysiology and Therapeutic Implications

Natural Killer (NK) cells are lymphocytes of the innate immunity that play a crucial role in the control of viral infections in the absence of a prior antigen sensitization. Indeed, they display rapid effector functions against target cells with the capability of direct cell killing and antibody-dependent cell-mediated cytotoxicity. Furthermore, NK cells are endowed with immune-modulatory functions innate and adaptive immune responses via the secretion of chemokines/cytokines and by undertaking synergic crosstalks with other innate immune cells, including monocyte/macrophages, dendritic cells and neutrophils. Recently, the Coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread globally. Although the specific role of NK cells in COVID-19 pathophysiology still need to be explored, mounting evidence indicates that NK cell tissue distribution and effector functions could be affected by SARS-CoV-2 infection and that a prompt NK cell response could determine a good clinical outcome in COVID-19 patients. In this review, we give a comprehensive overview of how SARS-CoV-2 infection interferes with NK cell antiviral effectiveness and their crosstalk with other innate immune cells. We also provide a detailed characterization of the specific NK cell subsets in relation to COVID-19 patient severity generated from publicly available single cell RNA sequencing datasets. Finally, we summarize the possible NK cell-based therapeutic approaches against SARS-CoV-2 infection and the ongoing clinical trials updated at the time of submission of this review. We will also discuss how a deep understanding of NK cell responses could open new possibilities for the treatment and prevention of SARS-CoV-2 infection.

An individualized algorithm to predict mortality in COVID-19 pneumonia: a machine learning based study.

Introduction: Identifying SARS-CoV-2 patients at higher risk of mortality is crucial in the management of a pandemic. Artificial intelligence techniques allow one to analyze large amounts of data to find hidden patterns. We aimed to develop and validate a mortality score at admission for COVID-19 based on high-level machine learning. Material and methods: We conducted a retrospective cohort study on hospitalized adult COVID-19 patients between March and December 2020. The primary outcome was in-hospital mortality. A machine learning approach based on vital parameters, laboratory values and demographic features was applied to develop different models. Then, a feature importance analysis was performed to reduce the number of variables included in the model, to develop a risk score with good overall performance, that was finally evaluated in terms of discrimination and calibration capabilities. All results underwent cross-validation. Results: 1,135 consecutive patients (median age 70 years, 64% male) were enrolled, 48 patients were excluded, and the cohort was randomly divided into training (760) and test (327) groups. During hospitalization, 251 (22%) patients died. After feature selection, the best performing classifier was random forest (AUC 0.88 ±0.03). Based on the relative importance of each variable, a pragmatic score was developed, showing good performances (AUC 0.85 ±0.025), and three levels were defined that correlated well with in-hospital mortality. Conclusions: Machine learning techniques were applied in order to develop an accurate in-hospital mortality risk score for COVID-19 based on ten variables. The application of the proposed score has utility in clinical settings to guide the management and prognostication of COVID-19 patients.

BNT162b2 vaccine induces antibody release in saliva: a possible role for mucosal viral protection?

Vaccination against an airborne pathogen is very effective if it induces also the development of mucosal antibodies that can protect against infection. The mRNA-based vaccine-encoding SARS-CoV-2 full-length spike protein (BNT162b2, Pfizer/BioNTech) protects also against infection despite being administered systemically. Here, we show that upon vaccination, cognate IgG molecules are also found in the saliva and are more abundant in SARS-CoV-2 previously exposed subjects, paralleling the development of plasma IgG. The antibodies titer declines at 3 months from vaccination. We identified a concentration of specific IgG in the plasma above which the relevant IgG can be detected in the saliva. Regarding IgA antibodies, we found only protease-susceptible IgA1 antibodies in plasma while they were present at very low levels in the saliva over the course of vaccination of SARS-CoV-2-naïve subjects. Thus, in response to BNT162b2 vaccine, plasma IgG can permeate into mucosal sites and participate in viral protection. It is not clear why IgA1 are detected in low amount, they may be proteolytically cleaved.

COVID-19 in Immunocompromised Patients: A Systematic Review.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) was first identified as a novel coronavirus in Wuhan, Hubei province, central China, in December 2019, and is responsible for the 2019-to-present pandemic. According to the most recent data released by the World Health Organization, more than 200 million people have been infected by SARS-CoV-2 so far, and more than 4 million people died worldwide. Although our knowledge on SARS-CoV-2 and COVID-19 is constantly growing, data on COVID-19 in immunocompromised patients are still limited. The aim of the present systematic review is to describe clinical picture, disease severity, proposed treatment regimen, and response to vaccination in patients with different types and severity of immunosuppression.

A 'Multiomic' Approach of Saliva Metabolomics, Microbiota, and Serum Biomarkers to Assess the Need of Hospitalization in Coronavirus Disease 2019.

BACKGROUND AND AIMS: The SARS-CoV-2 pandemic has overwhelmed the treatment capacity of the health care systems during the highest viral diffusion rate. Patients reaching the emergency department had to be either hospitalized (inpatients) or discharged (outpatients). Still, the decision was taken based on the individual assessment of the actual clinical condition, without specific biomarkers to predict future improvement or deterioration, and discharged patients often returned to the hospital for aggravation of their condition. Here, we have developed a new combined approach of omics to identify factors that could distinguish coronavirus disease 19 (COVID-19) inpatients from outpatients. METHODS: Saliva and blood samples were collected over the course of two observational cohort studies. By using machine learning approaches, we compared salivary metabolome of 50 COVID-19 patients with that of 270 healthy individuals having previously been exposed or not to SARS-CoV-2. We then correlated the salivary metabolites that allowed separating COVID-19 inpatients from outpatients with serum biomarkers and salivary microbiota taxa differentially represented in the two groups of patients. RESULTS: We identified nine salivary metabolites that allowed assessing the need of hospitalization. When combined with serum biomarkers, just two salivary metabolites (myo-inositol and 2-pyrrolidineacetic acid) and one serum protein, chitinase 3-like-1 (CHI3L1), were sufficient to separate inpatients from outpatients completely and correlated with modulated microbiota taxa. In particular, we found Corynebacterium 1 to be overrepresented in inpatients, whereas Actinomycetaceae F0332, Candidatus Saccharimonas, and Haemophilus were all underrepresented in the hospitalized population. CONCLUSION: This is a proof of concept that a combined omic analysis can be used to stratify patients independently from COVID-19.

Short-Term Adverse Events and Antibody Response to the BNT162b2 SARS-CoV-2 Vaccine in 4156 Health Care Professionals.

Short-term adverse events are common following the BNT162b2 vaccine for SARS-Cov-2 and have been possibly associated with IgG response. We aimed to determine the incidence of adverse reactions to the vaccine and the impact on IgG response. Our study included 4156 health-care professionals who received two doses of the BNT162b2 vaccine 21 days apart and obtained 6113 online questionnaires inquiring about adverse events. The serum response was tested in 2765 subjects 10 days after the second dose. Adverse events, most frequently a local reaction at the site of injection, were reported by 39% of subjects. Multivariate analysis showed that female sex (odds ratio-OR-1.95; 95% confidence interval-CI-1.74-2.19; p < 0.001), younger age (OR 0.98 per year, p < 0.001), second dose of vaccine (OR 1.36, p < 0.001), and previous COVID-19 infection (OR 1.41, p < 0.001) were independently associated with adverse events. IgG response was significantly higher in subjects with adverse events (1110 AU/mL-IQR 345-1630 vs. 386 AU/mL, IQR 261-1350, p < 0.0001), and the association was more pronounced in subjects experiencing myalgia, fever, and lymphadenopathy. We demonstrate that a more pronounced IgG response is associated with specific adverse events, and these are commonly reported by health care professionals after the BNT162b2 vaccine for SARS-Cov-2.

Algorithm for Individual Prediction of COVID-19-Related Hospitalization Based on Symptoms: Development and Implementation Study.

BACKGROUND: The COVID-19 pandemic has placed a huge strain on the health care system globally. The metropolitan area of Milan, Italy, was one of the regions most impacted by the COVID-19 pandemic worldwide. Risk prediction models developed by combining administrative databases and basic clinical data are needed to stratify individual patient risk for public health purposes. OBJECTIVE: This study aims to develop a stratification tool aimed at improving COVID-19 patient management and health care organization. METHODS: A predictive algorithm was developed and applied to 36,834 patients with COVID-19 in Italy between March 8 and the October 9, 2020, in order to foresee their risk of hospitalization. Exposures considered were age, sex, comorbidities, and symptoms associated with COVID-19 (eg, vomiting, cough, fever, diarrhea, myalgia, asthenia, headache, anosmia, ageusia, and dyspnea). The outcome was hospitalizations and emergency department admissions for COVID-19. Discrimination and calibration of the model were also assessed. RESULTS: The predictive model showed a good fit for predicting COVID-19 hospitalization (C-index 0.79) and a good overall prediction accuracy (Brier score 0.14). The model was well calibrated (intercept -0.0028, slope 0.9970). Based on these results, 118,804 patients diagnosed with COVID-19 from October 25 to December 11, 2020, were stratified into low, medium, and high risk for COVID-19 severity. Among the overall study population, 67,030 (56.42%) were classified as low-risk patients; 43,886 (36.94%), as medium-risk patients; and 7888 (6.64%), as high-risk patients. In all, 89.37% (106,179/118,804) of the overall study population was being assisted at home, 9% (10,695/118,804) was hospitalized, and 1.62% (1930/118,804) died. Among those assisted at home, most people (63,983/106,179, 60.26%) were classified as low risk, whereas only 3.63% (3858/106,179) were classified at high risk. According to ordinal logistic regression, the odds ratio (OR) of being hospitalized or dead was 5.0 (95% CI 4.6-5.4) among high-risk patients and 2.7 (95% CI 2.6-2.9) among medium-risk patients, as compared to low-risk patients. CONCLUSIONS: A simple monitoring system, based on primary care data sets linked to COVID-19 testing results, hospital admissions data, and death records may assist in the proper planning and allocation of patients and resources during the ongoing COVID-19 pandemic.

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.

Environmental triggers for connective tissue disease: the case of COVID-19 associated with dermatomyositis-specific autoantibodies.

PURPOSE OF REVIEW: The aim of the present review is to analyze the link between autoimmune diseases and environmental factors, in particular severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (COVID-19) as it shares numerous features with the interstitial lung disease associated with connective tissue diseases positive for rare autoantibodies directed at highly specific autoantigens (i.e., MDA5 and RIG1) among the intracellular sensors of SARS-CoV-2 in the innate response against viruses. RECENT FINDINGS: As shown in recent publications and in our original data, specific autoantibodies may be functionally relevant to COVID-19 infection. We evaluated sera from 35 hospitalized patients with COVID-19 to identify antinuclear antibodies and autoantibodies directed against specific antigenic targets, and we identified anti-nuclear antibodies (ANA) in 20/35 of patients with COVID-19 (57%), in patients with need for supplemental oxygen (90% vs. 20% in ANA-negative cases; P < 0.0001). In 7/35 COVID-19 sera, we detected anti-MJ/NXP2 (n = 3), anti-RIG1 (n = 2), anti-Scl-70/TOPO1 (n = 1), and anti-MDA5 (n = 1), overall associated with a significantly worse pulmonary involvement at lung computerized tomography scans. Eleven (31%) patients were positive for antibodies against the E2/E3 subunits of mitochondrial pyruvate dehydrogenase complex. SUMMARY: Viral infections such as COVID-19 are associated with ANA and autoantibodies directed toward antiviral signaling antigens in particular in patients with worse pulmonary involvement.

The Impact of Risk-Adjusted Heparin Regimens on the Outcome of Patients with COVID-19 Infection. A Prospective Cohort Study.

BACKGROUND: According to recent guidelines, all hospitalized patients with COVID-19 should receive pharmacological prophylaxis for venous thromboembolism (VTE), unless there are specific contraindications. However, the optimal preventive strategy in terms of intensity of anticoagulation for these patients is not well established. OBJECTIVES: To investigate the impact of individualized regimens of enoxaparin on the development of VTE and on the risk of major bleeding complications during hospitalization in patients with COVID-19 infection. METHODS: All consecutive patients admitted to the medical wards of six Italian hospitals between 15 September and 15 October 2020 with COVID-19 infection of moderate severity were administered enoxaparin in subcutaneous daily doses adjusted to the Padua Prediction Score stratification model: No heparin in patients scoring less than 4, 4000 IU daily in those scoring 4, 6000 IU in those scoring 5, and 8000 in those scoring six or more. Objective tests were performed in patients developing clinical symptoms of deep vein thrombosis and/or pulmonary embolism. Bleeding complications were defined according to the ISTH classification. RESULTS: From the 154 eligible patients, enoxaparin was administered in all: 4000 IU in 73 patients, 6000 IU in 53, and 8000 IU in the remaining 28. During the course of hospitalization, 27 patients (17.5%) died. VTE developed in 14 of the 154 patients (9.1%; 95% CI, 4.6% to 13.6%), and was fatal in 1. Major bleeding complications developed in 35 patients (22.7%; 95% CI, 16.1% to 29.3%), and were fatal in 8. CONCLUSIONS: Despite the use of risk-adjusted doses of enoxaparin, the rate of VTE events was consistent with that reported in contemporary studies where fixed-dose low-molecular-weight heparin was used. The unexpectedly high risk of bleeding complications should induce caution in administering enoxaparin in doses higher than the conventional low ones.