Outcomes of patients with COVID-19 hospitalized during the fourth pandemic wave in relation to their clinical features and vaccination status

This study aims to observe the clinical characteristics and outcomes of recovered patients from coronavirus disease 2019 (COVID-19) related to the vaccination status. We examined results of 205 COVID-19-recovered patients from 15 December 2021 to 1 March 2022 in two hospitals of Local Health Authority of Alessandria (Italy) during the fourth pandemic wave. 77% of patients were hospitalized for acute respiratory failure (ARF) with radiological pneumonia pattern (recovered for COVID), 23% for other causes with occasional positivity finding (recovered with COVID). 32% of patients were not vaccinated for SARS-CoV-2, 37% had three doses, 25% two doses, 5% only one dose. All patients without vaccination were hospitalized for ARF and they had a 7 times higher risk of hospitalization than the vaccinated. 60% of all patients had =3 comorbidities, of these 50% was vaccinated with three doses. In the fourth pandemic wave compared to the other not all patients were hospitalized for ARF and pneumonia and the presence of comorbidities >= 3 is a risk factor for hospitalization regardless of vaccination status. This justifies the administration of the fourth dose to frail patients.

Evidence of the presence of antinuclear antibodies (ANA) in healthcare workers after mRNA based anti-SARS CoV-2 vaccines

Introduction: Evidence from clinical trials strongly supports the safety and efficacy of the different COVID-19 vaccines. Indeed, the risk to develop a severe form of the disease, possibly leading to death, it is highly decreased in fully vaccinated individuals. Nowadays, vaccines effects and their possible ability to stimulate an autoimmune reaction are still poorly understood. The aim of this study was to check the development and /or persistence of antinuclear antibodies (ANA) in healthcare workers (HCPs) after mRNA based anti-SARS CoV-2 vaccines. Method(s): In this study, 77 HCPs were considered (60 females and 17 males, age range 26-67 years, median age 48) without any history of COVID-19 infection. All the subjects were vaccinated with 2 doses of BioNtech/Pfizer BNT162b2 mRNA. Furthermore, half of them received a third dose of the same vaccine, whereas the other half of Moderna (Spikevax). Blood Samples were collected before the inoculation of the vaccine (T0), at 3 (T1) and 12 months (T2) after the first dose. Therefore, at T1 all the subjects received two doses of vaccine and at T2 three doses. ANA presence was evaluated using indirect immunofluorescence on Hep-2 cells (EUROIMMUN test kit) at dilutions: 1:80, 1:160, 1:320, 1:640. Fisher and Wilcoxon statistical tests were performed using GraphPad Prism 9 Software. Result(s): Among 77 subjects enrolled, at T0 25 were positive for ANA (23 maintained this positivity also at T1 and T2) and 52 were negative. At T1, 46/52 remained negative, whereas 6/52 became ANA positive (5 maintained this positivity also at T2). At T2, 30/46 were still negative, instead 16/46 became ANA positive. In addition, from T1 to T2, it has been observed a statistically significant increase of ANA presence. Conclusion(s): Our results suggest that mRNA based anti-SARS CoV-2 vaccines seem to induce the onset of de novo ANA in 22/77 (28,57%) of subjects and that the percentage of positivity seems to directly correlate to the number of vaccine expositions: 6/77 (7,79%) after 2 doses;and 16/77 (20,78%) after 3 doses.

Mortality in Covid-19 patients hospitalized in a teaching hospital in Italy during the first 3 waves : Anna Odone

Introduction In Italy a Covid-19 pandemic pattern was observed, characterized by several waves, with an excess total mortality of 178000 deaths. Alessandria, Italy is the Piedmont province with the highest proportion of mortality from Covid-19 in the first 4 months of 2020, compared to the rest of the region. Objectives To analyze mortality in patients hospitalized for Covid-19 in the Alessandria Hospital (AO AL), considering the first 3 waves. Materials and methods Subjects aged ≥18 with a diagnosis of Covid-19 admitted to the AO AL in the first 50 days of the first 3 waves were included. The first wave started on 24 February 2020 (first day of available data by the Ministry of Health), the second wave on 14 September 2020 (first day of the 2020/21 school year), the third wave on 15 February 2021 (peak of cases detected by the Italian College of Health). The causes of death were obtained from the National Institute of Statistics death cards and codified according to the International Classification of Diseases, 9th revision, classification. Results We included 825 subjects (median age: 73 years;male prevalence: 60.7%). The subjects hospitalized in the first wave were 464, in the second wave 255, in the third wave 106. A total of 309 subjects died (37.5%), of which 218 in the first wave (70.6%), 69 in the second wave (22.3%), 22 in the third wave (7.1%). The most frequent causes of death were “Covid-19 pneumonia” (61.5%) and “respiratory distress syndrome” (19.4%). Death occurred after hospital discharge in 40% of cases. 6 months after admission, the survival rate was 53% among patients of the first wave, 73% and 78% for those of the second and third wave. Patients hospitalized in the first and second waves showed a greater risk of death compared to patients of the third wave (HR = 2.8;95% CI 1.8-4.4 and HR = 1.4;95% CI 0.8-2.2). Conclusions Data showed a difference in mortality between the 3 waves with a statistically significant variation between the first and third waves. Key messages • Data showed a difference in mortality between the 3 waves. • Data showed a statistically significant variation in mortality between the first and third waves.

Long-term benefit of lurbinectedin as palliative chemotherapy in progressive malignant pleural mesothelioma (MPM): final efficacy and translational data of the SAKK 17/16 study.

BACKGROUND: The SAKK 17/16 study showed promising efficacy data with lurbinectedin as second- or third-line palliative therapy in malignant pleural mesothelioma. Here, we evaluated long-term outcome and analyzed the impact of lurbinectedin monotherapy on the tumor microenvironment at the cellular and molecular level to predict outcomes. MATERIAL AND METHODS: Forty-two patients were treated with lurbinectedin in this single-arm study. Twenty-nine samples were available at baseline, and seven additional matched samples at day one of cycle two of treatment. Survival curves and rates between groups were compared using the log-rank test and Kaplan-Meier method. Statistical significance was set at P value <0.05. RESULTS: Updated median overall survival (OS) was slightly increased to 11.5 months [95% confidence interval (CI) 8.8-13.8 months]. Thirty-six patients (85%) had died. The OS rate at 12 and 18 months was 47% (95% CI 32.1% to 61.6%) and 31% (95% CI 17.8% to 45.0%), respectively. Median progression-free survival was 4.1 months (95% CI 2.6-5.5 months). No new safety signals were observed. Patients with lower frequencies of regulatory T cells, as well as lower tumor-associated macrophages (TAMs) at baseline, had a better OS. Comparing matched biopsies, a decrease of M2 macrophages was observed in five out of seven patients after exposure to lurbinectedin, and two out of four patients showed increased CD8+ T-cell infiltrates in tumor. DISCUSSION: Lurbinectedin continues to be active in patients with progressing malignant pleural mesothelioma. According to our very small sample size, we hypothesize that baseline TAMs and regulatory T cells are associated with survival. Lurbinectedin seems to inhibit conversion of TAMs to M2 phenotype in humans.

The acute phase response identifies cancer patients with adverse outcomes from SARS-CoV-2 infection as quantified by the OnCovid Inflammatory Score

We sought to determine parameters of the acute phase response, a feature of innate immunity activated by infectious noxae and cancer, deranged by Covid-19 and establish oncological indices' prognostic potential for patients with concomitant cancer and Covid-19. Between 27/02 and 23/06/2020, OnCovid retrospectively accrued 1,318 consecutive referrals of patients with cancer and Covid-19 aged 18 from the U.K., Spain, Italy, Belgium, and Germany. Patients with myeloma, leukemia, or insufficient data were excluded. The neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), prognostic nutritional index (PNI), modified Glasgow prognostic score (mGPS), and prognostic index (PI) were evaluated for their prognostic potential, with the NLR, PLR, and PNI risk stratifications dichotomized around median values and the pre-established risk categorizations from literature utilized for the mGPS and PI. 1,071 eligible patients were randomly assorted into a training set (TS, n=529) and validation set (VS, n=542) matched for age (67.9±13.3 TS, 68.5±13.5 VS), presence of 1 comorbidity (52.1% TS, 49.8% VS), development of 1 Covid-19 complication (27% TS, 25.9% VS), and active malignancy at Covid-19 diagnosis (66.7% TS, 61.6% VS). Among all 1,071 patients, deceased patients tended to categorize into poor risk groups for the NLR, PNI, mGPS, and PI (P<0.0001) with a return to pre-Covid-19 diagnosis NLR, PNI, and mGPS categorizations following recovery (P<0.01). In the TS, higher mortality rates were associated with NLR>6 (44.6% vs 28%, P<0.0001), PNI<40 (46.6% vs 20.9%, P<0.0001), mGPS (50.6% for mGPS2 vs 30.4% and 11.4% for mGPS1 and 0, P<0.0001), and PI (50% for PI2 vs 40% for PI1 and 9.1% for PI0, P<0.0001). Findings were confirmed in the VS (P<0.001 for all comparisons). Patients in poor risk categories had shorter median overall survival [OS], (NLR>6 30 days 95%CI 1-63, PNI<40 23 days 95%CI 10-35, mGPS2 20 days 95%CI 8-32, PI2 23 days 95%CI 1-56) compared to patients in good risk categories, for whom median OS was not reached (P<0.001 for all comparisons). The PLR was not associated with survival. Analyses of survival in the VS confirmed the NLR (P<0.0001), PNI (P<0.0001), PI (P<0.01), and mGPS (P<0.001) as predictors of survival. In a multivariable Cox regression model including all inflammatory indices and pre-established prognostic factors for severe Covid-19 including sex, age, comorbid burden, malignancy status, and receipt of anti-cancer therapy at Covid-19 diagnosis, the PNI was the only factor to emerge with a significant hazard ratio [HR] in both TS and VS analysis (TS HR 1.97, 95%CI 1.19-3.26, P=0.008;VS HR 2.48, 95%CI 1.47- 4.20, P=0.001). We conclude that systemic inflammation drives mortality from Covid-19 through hypoalbuminemia and lymphocytopenia as measured by the PNI and propose the PNI as the OnCovid Inflammatory Score (OIS) in this context.

Evidence of autoantibodies in hospitalized COVID-19 patients

Recent studies highlight the evidence of autoantibodies in patients affected by Corona Virus Disease-2019 (COVID-19). We evaluated whether severe acute respiratory syndrome (SARS-CoV-2) stimulates autoantibody production and contributes to autoimmunity activation. We enrolled 40 adult patients (66.8 years mean age) admitted to Alessandria hospital between March and April 2020 with a confirmed COVID-19 diagnosis by real-time polymerase chain reaction (RT-PCR) and no previously clinical record of autoimmune disease. 40 blood donors were analyzed for the same markers and considered as healthy controls. All hospitalized patients had high levels of common inflammatory markers, such as C Reactive Protein, Lactate Dehydrogenase, ferritin and creatinine. Interleukin-6 concentrations were also increased, supporting the major role of this interleukin during COVID-19 infection. Lymphocytes number was generally lower compared to healthy individuals. All the patients were also screened for the most common autoantibodies. We found a significant prevalence of ANA (57,5%), ANCA (25%), and ASCA IgA (25%) antibodies in COVID-19 patients compared to healthy controls. We observed that patients having a de novo autoimmune response had the worst acute viral disease prognosis and outcome. Our results sustain the hypothesis that COVID-19 virus might break the body tolerance to itself and stimulate autoimmune responses, suggesting they were directly related to viral infection, instead of being a preexisting condition. The observed increase of autoantibodies remained stable in six-month follow-up of COVID-19 patients. Moreover, preliminary data indicate in a few patients the apparence of clinical manifestations suggestive of autoimmune disease onset. More study will be needed to find out whether these autoimmune profiles persist in COVID-19 affected patients.

A Preliminary Analysis of Hospitalized Covid-19 Patients in Alessandria Area: A machine learning approach

In 2020, severe coronavirus 2 respiratory syndrome (SARS-Cov-2) has quickly risen, becoming a worldwide pandemic that is still ongoing nowadays. Differently from other viruses the COVID-19, responsible for SARS-Cov-2, demonstrated an unmatched capability of transmission that led towards an unprecedented challenge for the global health system. All health facilities, ranging from Hospitals to local health surveillance units, have been severely tested due to the high number of infected people. In this scenario, the use of methodologies that can improve and optimize, at any level, the management of infected patients is highly advisable. One of the goals of Artificial Intelligence in medicine is to develop advanced tools and methodologies to support patient care and to help physicians and medical work in the decision-making process. More specifically, Machine Learning (ML) methods have been successfully used to build predictive models starting from clinical patient data. In our paper, we study whether ML can be used to build prognostic models capable of predicting the potential disease outcome. In our study, we evaluate different unsupervised and supervised ML approaches using SARS-Cov-2 data collected from the "Azienda Ospedaliera SS Antonio e Biagio e Cesare Arrigo"Hospital in Alessandria area, Italy, from 24th February to 31st October 2020. Our preliminary goal is to develop a ML model able to promptly identify patients with a high risk of fatal outcome, to steer medical doctors and clinicians towards the best management strategies. © 2021 IEEE.