Comprehensive bronchoalveolar lavage characterization in COVID-19 associated acute respiratory distress syndrome patients: a prospective cohort study.

COVID-19-related acute respiratory distress syndrome (CARDS) is associated with high mortality rates. We still have limited knowledge of the complex alterations developing in the lung microenvironment. The goal of the present study was to comprehensively analyze the cellular components, inflammatory signature, and respiratory pathogens in bronchoalveolar lavage (BAL) of CARDS patients (16) in comparison to those of other invasively mechanically ventilated patients (24). In CARDS patients, BAL analysis revealed: SARS-CoV-2 infection frequently associated with other respiratory pathogens, significantly higher neutrophil granulocyte percentage, remarkably low interferon-gamma expression, and high levels of interleukins (IL)-1ß and IL-9. The most important predictive variables for worse outcomes were age, IL-18 expression, and BAL neutrophilia. To the best of our knowledge, this is the first study that was able to identify, through a comprehensive analysis of BAL, several aspects relevant to the complex pathophysiology of CARDS.

Cefiderocol-Based versus Colistin-Based Regimens for Severe Carbapenem-Resistant Acinetobacter baumannii Infections: A Propensity Score-Weighted, Retrospective Cohort Study during the First Two Years of the COVID-19 Pandemic.

BACKGROUND: A large increase in multi-drug-resistant Acinetobacter baumannii, especially carbapenem-resistant strains, occurred during the first two years of the COVID-19 pandemic, posing important challenges in its treatment. Cefiderocol appeared to be a good option for the treatment of Carbapenem-resistant Acinetobacter baumannii (CR-Ab), but to date, the guidelines and evidence available are conflicting. METHODS: We retrospectively included a group of patients with CR-Ab infections (treated with colistin- or cefiderocol-based regimens) at Padua University Hospital (August 2020-July 2022) and assessed predictors of 30-day mortality, and differences in microbiological and clinical treatment. To evaluate the difference in outcomes, accounting for the imbalance in antibiotic treatment allocation, a propensity score weighting (PSW) approach was adopted. RESULTS: We included 111 patients, 68% males, with a median age of 69 years (IQR: 59-78). The median duration of antibiotic treatment was 13 days (IQR:11-16). In total, 60 (54.1%) and 51 (45.9%) patients received cefiderocol- and colistin-based therapy, respectively. Notably, 53 (47.7%) patients had bloodstream infections, while 58 (52.3%) had pneumonia. Colistin was combined in 96.1%, 80.4%, and 5.8% of cases with tigecycline, meropenem, and fosfomycin, respectively. Cefiderocol was combined in 13.3%, 30%, and 18.3% of cases with fosfomycin, tigecycline, and meropenem, respectively. At the baseline, the two treatment groups significantly differed in age (patients treated with colistin were significantly older), the prevalence of diabetes and obesity (more frequent in the group treated with colistin), length of stay (longer in the group receiving cefiderocol), and type of infection (BSI were more frequent in the group receiving cefiderocol). The proportion of patients who developed acute kidney injury was significantly higher in the colistin group. By using PSW, no statistically significant differences emerged for mortality or clinical and microbiological cure between the two groups. No independent predictors were detected for hospital mortality or clinical cure, while for the length of stay, the only selected predictor was age, with a non-linear effect (p-value 0.025 for non-linearity) on the prolongation of hospital stay of 0.25 days (95% CI 0.10-0.39) at increasing ages (calculated over the IQR). CONCLUSIONS: Cefiderocol treatment did not differ in terms of main outcomes and safety profile from colistin-based regimens. More prospective studies with a larger number of patients are required to confirm our results.

Vascular/epithelial changes as late sequelae after recovery from SARS-COV-2 infection: an in-vivo comparative study.

AIMS: While there is partial evidence of lung lesions in patients suffering from long COVID there are substantial concerns about lung remodelling sequelae after COVID-19 pneumonia. The aim of the present retrospective comparative study was to ascertain morphological features in lung samples from patients undergoing tumour resection several months after SARS-CoV-2 infection. METHODS AND RESULTS: The severity of several lesions with a major focus on the vascular bed was analysed in 2 tumour-distant lung fragments of 41 cases: 21 SARS-CoV-2 (+) lung tumour (LT) patients and 20 SARS-CoV-2 (-) LT patients. A systematic evaluation of several lesions was carried out by combining their scores into a grade of I-III. Tissue SARS-CoV-2 genomic/subgenomic transcripts were also investigated. Morphological findings were compared with clinical, laboratory and radiological data. SARS-CoV-2 (+) LT patients with previous pneumonia showed more severe parenchymal and vascular lesions than those found in SARS-CoV-2 (+) LT patients without pneumonia and SARS-CoV-2 (-) LT patients, mainly when combined scores were used. SARS-CoV-2 viral transcripts were not detected in any sample. SARS-CoV-2 (+) LT patients with pneumonia showed a significantly higher radiological global injury score. No other associations were found between morphological lesions and clinical data. CONCLUSIONS: To our knowledge, this is the first study that, after a granular evaluation of tissue parameters, detected several changes in lungs from patients undergoing tumour resection after SARS-CoV-2 infection. These lesions, in particular vascular remodelling, could have an important impact overall on the future management of these frail patients.

Changing patterns and clinical outcomes of hospitalized patients with COVID-19 severe pneumonia treated with remdesivir according to vaccination status: results from a real-world retrospective study.

Since the beginning of Coronavirus Disease 2019 (COVID-19) pandemic, many drugs have been purposed for the treatment of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Remdesivir emerged as an encouraging antiviral drug for patients with documented severe COVID-19-related pneumonia. Although several studies about remdesivir effectiveness exist, no study investigated the effect of the combination of remdesivir with the vaccination status. The aim of this study was to assess whether the administration of remdesivir could show some differences in terms of clinical outcomes in patients vaccinated against SARS-CoV-2 versus those who were not. The primary outcome was the in-hospital mortality. The secondary outcomes were 30-days mortality, the need for ICU admission and for oxygen supplementation. This is a retrospective cohort study including all consecutive adult patients hospitalized for severe COVID-19 at the Padua University Hospital (Italy), between September 1st, 2020, and January 31st, 2022, and who received a 5-days course of remdesivir. A total of 708 patients were included, 467 (66%) were male, and the median age was 67 (IQR: 56-79) years. To better estimate the outcomes of interest, a propensity score weighted approach was implemented for vaccination status. A total of 605/708 patients (85.4%) did not complete the vaccination schedule. In-hospital mortality rate was 5.1% (n = 36), with no statistically significant difference between the unvaccinated (n=29, 4.8%) and vaccinated (n=7, 6.8%; p=0.4) patients. After propensity score matching, mortality between the two groups remained similar. However, both the need for ICU and oxygen supplementation were significantly lower in the vaccinated group. Our finding suggests that a complete vaccination course could have an impact in reducing the need for transfer in ICU and for high-flow therapy in moderate-to-severe COVID-19 patients treated with remdesivir.

Understanding the Factors Affecting COVID-19 Mortality in Italy: Does a Relationship Exist With a Sharp Increase in Intensive Care Unit Admissions?

OBJECTIVE: The present study aims to explore whether a relationship exists between the immediate sharp increase in intensive care unit (ICU) admissions and the mortality rates in Italy. METHODS: Official epidemiological data on coronavirus disease (COVID-19) were employed. The forward lagged (0, 3, 7, 14 days) daily variations in the number of deaths according to the number of days after the outbreak started and the daily increases in ICU admissions were estimated. RESULTS: A direct relationship between the sharp increase of ICU admissions and mortality rates has been shown. Furthermore, the analysis of the forward lagged daily variations in the number of deaths showed that an increase in the daily number of ICU admissions resulted in significantly higher mortality after 3, 7, and 14 days. The most pronounced effect was detected after 7 days, with 250 deaths (95% CI: 108.1-392.8) for the highest increase in the ICU admissions, from 100 to 200. CONCLUSIONS: These results would serve as a warning for the scientific community and the health care decision-makers to prevent a quick and out-of-control saturation of the ICU beds in case of a relapse of the COVID-19 outbreak.

Ethics committees in the time of COVID-19.

BACKGROUND: ethics committees (ECs) protect the rights, safety, and well-being of research participants and ensure the scientific correctness of clinical research. COVID-19 pandemic and the lockdown from 9 March to 16 May 2020 have potentially influenced several activities, including ECs. OBJECTIVES: to assess the impact of COVID-19 outbreak on Italian ECs and their performance during the lockdown. DESIGN: cross-sectional survey. SETTING AND PARTICIPANTS: the survey was conducted in mid-June 2020 in Italy contacting all the 90 local ECs. MAIN OUTCOME MEASURES: amount and kind of activities performed during the lockdown, characteristics of submitted studies and adoption of standard protocols of evaluation of research applications during the pandemic. Chi-square test was used to estimate the differences between territories with higher incidence (HI) and lower incidence (LI) of COVID-19. RESULTS: 258 questionnaires were collected from 46 ECs that participated in the study. Ten were excluded due to missing substantial data. Responses were divided into two groups according to location of EC: the HI (125 responses) and the LI (123 responses). Seventy-five percent of the HI describe an increase in the number of studies submitted, while 53% of the LI does not (p=0.001). Due to the pandemic and its effects on research, the 15% of participants belonging to HI territories reported that consideration and respect of research-related and general ethical principles could have decreased, as well the adoption of standard protocols of evaluation of research applications. EC secretariats located in HI Regions moved to smart working more than in LI ones (75% vs 59%; p=0.001). Where the EC workload increased significantly, it was reported that it was impossible to perform an accurate analysis of the submitted documentation, with the effect of providing a favorable opinion to studies of not excellent quality, though always ensuring the respect of ethical principles and patients' safety. CONCLUSIONS: COVID-19 impact on ECs has been heavier in HI territories, but smart working has been effective in ensuring EC activities and the subsequent activation of clinical studies potentially useful to face the pandemic. Clear differences arise between ECs belonging to the Italian Regions that have recorded a HI of COVID-19 cases compared to those located in Regions with a LI of cases. In some EC members' perception, the high number of studies in the most affected Regions together with the emergency experienced during the lockdown may have exposed ECs to the risk of decreasing the adoption of ethical principles and standard protocols of evaluation of research applications.

The PROVENT-C19 registry: A study protocol for international multicenter SIAARTI registry on the use of prone positioning in mechanically ventilated patients with COVID-19 ARDS.

BACKGROUND: The worldwide use of prone position (PP) for invasively ventilated patients with COVID-19 is progressively increasing from the first pandemic wave in everyday clinical practice. Among the suggested treatments for the management of ARDS patients, PP was recommended in the Surviving Sepsis Campaign COVID-19 guidelines as an adjuvant therapy for improving ventilation. In patients with severe classical ARDS, some authors reported that early application of prolonged PP sessions significantly decreases 28-day and 90-day mortality. METHODS AND ANALYSIS: Since January 2021, the COVID19 Veneto ICU Network research group has developed and implemented nationally and internationally the "PROVENT-C19 Registry", endorsed by the Italian Society of Anesthesia Analgesia Resuscitation and Intensive Care…'(SIAARTI). The PROVENT-C19 Registry wishes to describe 1. The real clinical practice on the use of PP in COVID-19 patients during the pandemic at a National and International level; and 2. Potential baseline and clinical characteristics that identify subpopulations of invasively ventilated patients with COVID-19 that may improve daily from PP therapy. This web-based registry will provide relevant information on how the database research tools may improve our daily clinical practice. CONCLUSIONS: This multicenter, prospective registry is the first to identify and characterize the role of PP on clinical outcome in COVID-19 patients. In recent years, data emerging from large registries have been increasingly used to provide real-world evidence on the effectiveness, quality, and safety of a clinical intervention. Indeed observation-based registries could be effective tools aimed at identifying specific clusters of patients within a large study population with widely heterogeneous clinical characteristics. TRIAL REGISTRATION: The registry was registered (ClinicalTrial.Gov Trials Register NCT04905875) on May 28,2021.

COVID-19 hospitalizations and patients' age at admission: The neglected importance of data variability for containment policies.

Introduction: An excess in the daily fluctuation of COVID-19 in hospital admissions could cause uncertainty and delays in the implementation of care interventions. This study aims to characterize a possible source of extravariability in the number of hospitalizations for COVID-19 by considering age at admission as a potential explanatory factor. Age at hospitalization provides a clear idea of the epidemiological impact of the disease, as the elderly population is more at risk of severe COVID-19 outcomes. Administrative data for the Veneto region, Northern Italy from February 1, 2020, to November 20, 2021, were considered. Methods: An inferential approach based on quasi-likelihood estimates through the generalized estimation equation (GEE) Poisson link function was used to quantify the overdispersion. The daily variation in the number of hospitalizations in the Veneto region that lagged at 3, 7, 10, and 15 days was associated with the number of news items retrieved from Global Database of Events, Language, and Tone (GDELT) regarding containment interventions to determine whether the magnitude of the past variation in daily hospitalizations could impact the number of preventive policies. Results: This study demonstrated a significant increase in the pattern of hospitalizations for COVID-19 in Veneto beginning in December 2020. Age at admission affected the excess variability in the number of admissions. This effect increased as age increased. Specifically, the dispersion was significantly lower in people under 30 years of age. From an epidemiological point of view, controlling the overdispersion of hospitalizations and the variables characterizing this phenomenon is crucial. In this context, the policies should prevent the spread of the virus in particular in the elderly, as the uncontrolled diffusion in this age group would result in an extra variability in daily hospitalizations. Discussion: This study demonstrated that the overdispersion, together with the increase in hospitalizations, results in a lagged inflation of the containment policies. However, all these interventions represent strategies designed to contain a mechanism that has already been triggered. Further efforts should be directed toward preventive policies aimed at protecting the most fragile subjects, such as the elderly. Therefore, it is essential to implement containment strategies before the occurrence of potentially out-of-control situations, resulting in congestion in hospitals and health services.

A topic trend analysis on COVID-19 literature

Objective In the past 2 years, the number of scientific publications has grown exponentially. The COVID-19 outbreak hugely contributed to this dramatic increase in the volume of published research. Currently, text mining of the volume of SARS-CoV-2 and COVID-19 publications is limited to the first months of the outbreak. We aim to identify the major topics in COVID-19 literature collected from several citational sources and analyze the temporal trend from November 2019 to December 2021. Methods We performed an extensive literature search on SARS-Cov-2 and COVID-19 publications on PubMed, Scopus, and Web of Science (WoS) and a structural topic modelling on the retrieved s. The temporal trend of the recognized topics was analyzed. Furthermore, a comparison between our corpus and the COVID-19 Open Research Dataset (CORD-19) repository was performed. Results We collected 269,186 publications and identified 10 topics. The most popular topic was related to the clinical pictures of the COVID-19 outbreak, which has a constant trend, and the least popular includes studies on COVID-19 literature and databases. “Telemedicine”, “Vaccine development”, and “Epidemiology” were popular topics in the early phase of the pandemic;increasing topics in the last period are “COVID-19 impact on mental health”, “Forecasting”, and “Molecular Biology”. “Education” was the second most popular topic, which emerged in September 2020. Conclusions We identified 10 topics for classifying COVID-19 research publications and estimated a nonlinear temporal trend that gives an overview of their unfolding over time. Several citational databases must be searched to retrieve a complete set of studies despite the efforts to build repositories for COVID-19 literature. Our collected data can help build a more focused literature search between November 2019 and December 2021 when carrying out systematic and rapid reviews and our findings can give a complete picture on the topic.

Outcomes of COVID-19 Patients with Severe Hypoxemic Acute Respiratory Failure: Non-Invasive Ventilation vs. Straight Intubation-A Propensity Score-Matched Multicenter Cohort Study.

The best timing for endotracheal intubation in patients with coronavirus disease 2019 (COVID-19) hypoxemic acute respiratory failure (hARF) remains debated. Aim of this study is to compare the outcomes of COVID-19 patients with hARF receiving either a trial of non-invasive ventilation (NIV) or intubated with no prior attempt of NIV ("straight intubation"). All consecutive patients admitted to the 25 participating ICUs were included and divided in two groups: the "straight intubation" group and the "NIV" group. A propensity score matching was performed to correct for biases associated with the choice of the respiratory support. Primary outcome was in-hospital mortality. Secondary outcomes were length of mechanical ventilation, hospital stay and reintubation rate. A total of 704 COVID-19 patients were admitted to ICUs during the study period. After matching, 141 patients were included in each group. No clinically relevant difference at ICU admission was found between groups. In-hospital mortality was significantly lower in the NIV group (22.0% vs. 36.2%), with no significant difference in secondary endpoints. There was no significant mortality difference between patients who received straight intubation and those intubated after NIV failure. In COVID-19 patients with hARF it is worth and safe attempting a trial of NIV prior to intubation.

Impact of the COVID-19 lockdown on psychological health and nutritional habits in Italy: results from the #PRESTOinsieme study.

OBJECTIVES: The present work aims to present the results of the 'PRESTOinsieme' (which is 'we will be together soon' in English). The web-based survey (www.prestoinsieme.com) describes changes in lifestyle habits and symptoms of psychological discomfort in the Italian population during the COVID-19 lockdown. DESIGN: Cross-sectional online survey disseminated by messaging apps (ie, WhatsApp and Telegram) and social networks (ie, Instagram, Facebook and LinkedIn). SETTING: Italy. PARTICIPANTS: Italian population older than 16 years of age. EXPOSURE: COVID-19 lockdown. MAIN OUTCOMES AND MEASURES: Survey respondents filled out a set of validated questionnaires aimed at assessing lifestyle habits and psychological health, that is, the General Health Questionnaire (GHQ-12) to screen for psychological distress, the Impact of Event Scale-Revised (IES-R) to screen for post-traumatic stress and the Center for Epidemiologic Studies Depression Scale (CES-D). RESULTS: Survey respondents totalled 5008. Moderate or severe psychological distress was reported in 25.5% and 22% of survey respondents, respectively. Lower age, female gender, being unemployed (OR 1.57, 95% CI 1.22 to 2.02) or being a student (OR 1.73, 95% CI 1.31 to 2.28) were predictors of more severe depressive symptoms. CONCLUSIONS: The present study is one of the largest population-based surveys conducted in Italy during the first COVID-19 lockdown, providing valuable data about the Italian population's psychological health. Further studies should be conducted to understand whether psychological distress persists after the end of the lockdown.

Impact of the "atherosclerotic pabulum" on in-hospital mortality for SARS-CoV-2 infection. Is calcium score able to identify at-risk patients?

BACKGROUND: Although the primary cause of death in COVID-19 infection is respiratory failure, there is evidence that cardiac manifestations may contribute to overall mortality and can even be the primary cause of death. More importantly, it is recognized that COVID-19 is associated with a high incidence of thrombotic complications. HYPOTHESIS: Evaluate if the coronary artery calcium (CAC) score was useful to predict in-hospital (in-H) mortality in patients with COVID-19. Secondary end-points were needed for mechanical ventilation and intensive care unit admission. METHODS: Two-hundred eighty-four patients (63, 25 years, 67% male) with proven severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection who had a noncontrast chest computed tomography were analyzed for CAC score. Clinical and radiological data were retrieved. RESULTS: Patients with CAC had a higher inflammatory burden at admission (d-dimer, p = .002; C-reactive protein, p = .002; procalcitonin, p = .016) and a higher high-sensitive cardiac troponin I (HScTnI, p = <.001) at admission and at peak. While there was no association with presence of lung consolidation and ground-glass opacities, patients with CAC had higher incidence of bilateral infiltration (p = .043) and higher in-H mortality (p = .048). On the other side, peak HScTnI >200 ng/dl was a better determinant of all outcomes in both univariate (p = <.001) and multivariate analysis (p = <.001). CONCLUSION: The main finding of our research is that CAC was positively related to in-H mortality, but it did not completely identify all the population at risk of events in the setting of COVID-19 patients. This raises the possibility that other factors, including the presence of soft, unstable plaques, may have a role in adverse outcomes in SARS-CoV-2 infection.

A Web-Based Application to Monitor and Inform about the COVID-19 Outbreak in Italy: The {COVID-19ita} Initiative.

The pandemic outbreak of COVID-19 has posed several questions about public health emergency risk communication. Due to the effort required for the population to adopt appropriate behaviors in response to the emergency, it is essential to inform the public of the epidemic situation with transparent data sources. The COVID-19ita project aimed to develop a public open-source tool to provide timely, updated information on the pandemic's evolution in Italy. It is a web-based application, the front end for the eponymously named R package freely available on GitHub, deployed both in English and Italian. The web application pulls the data from the official repository of the Italian COVID-19 outbreak at the national, regional, and provincial levels. The app allows the user to select information to visualize data in an interactive environment and compare epidemic situations over time and across different Italian regions. At the same time, it provides insights about the outbreak that are explained and commented upon to yield reasoned, focused, timely, and updated information about the outbreak evolution.

Thrombotic Events after COVID-19 Vaccination in the Over-50s: Results from a Population-Based Study in Italy.

Several European countries suspended or changed recommendations for the use of Vaxzevria (AstraZeneca) for suspected adverse effects due to atypical blood-clotting. This research aims to identify a reference point towards the number of thrombotic events expected in the Italian population over 50 years of age who received Vaxzevria from 22 January to 12 April 2021. The venous thromboembolism (VT) and immune thrombocytopenia (ITP) event rates were estimated from a population-based cohort. The overall VT rate was 1.15 (95% CI 0.93-1.42) per 1000 person-years, and the ITP rate was 2.7 (95% CI 0.7-11) per 100,000 person-years. These figures translate into 83 and two expected events of VT and ITP, respectively, in the 15 days following the first administration of Vaxzevria. The number of thrombotic events reported from the Italian Medicines Agency does not appear to have increased beyond that expected in individuals over 50 years of age.

COVID-19 ICU mortality prediction: a machine learning approach using SuperLearner algorithm.

BACKGROUND: Since the beginning of coronavirus disease 2019 (COVID-19), the development of predictive models has sparked relevant interest due to the initial lack of knowledge about diagnosis, treatment, and prognosis. The present study aimed at developing a model, through a machine learning approach, to predict intensive care unit (ICU) mortality in COVID-19 patients based on predefined clinical parameters. RESULTS: Observational multicenter cohort study. All COVID-19 adult patients admitted to 25 ICUs belonging to the VENETO ICU network (February 28th 2020-april 4th 2021) were enrolled. Patients admitted to the ICUs before 4th March 2021 were used for model training ("training set"), while patients admitted after the 5th of March 2021 were used for external validation ("test set 1"). A further group of patients ("test set 2"), admitted to the ICU of IRCCS Ca' Granda Ospedale Maggiore Policlinico of Milan, was used for external validation. A SuperLearner machine learning algorithm was applied for model development, and both internal and external validation was performed. Clinical variables available for the model were (i) age, gender, sequential organ failure assessment score, Charlson Comorbidity Index score (not adjusted for age), Palliative Performance Score; (ii) need of invasive mechanical ventilation, non-invasive mechanical ventilation, O2 therapy, vasoactive agents, extracorporeal membrane oxygenation, continuous venous-venous hemofiltration, tracheostomy, re-intubation, prone position during ICU stay; and (iii) re-admission in ICU. One thousand two hundred ninety-three (80%) patients were included in the "training set", while 124 (8%) and 199 (12%) patients were included in the "test set 1" and "test set 2," respectively. Three different predictive models were developed. Each model included different sets of clinical variables. The three models showed similar predictive performances, with a training balanced accuracy that ranged between 0.72 and 0.90, while the cross-validation performance ranged from 0.75 to 0.85. Age was the leading predictor for all the considered models. CONCLUSIONS: Our study provides a useful and reliable tool, through a machine learning approach, for predicting ICU mortality in COVID-19 patients. In all the estimated models, age was the variable showing the most important impact on mortality.