Assessment of Clinical Indicators Registered on Admission to the Hospital Related to Mortality Risk in Cancer Patients with COVID-19.

BACKGROUND: Oncology patients are a particularly vulnerable group to the severe course of COVID-19 due to, e.g., the suppression of the immune system. The study aimed to find links between parameters registered on admission to the hospital and the risk of later death in cancer patients with COVID-19. METHODS: The study included patients with a reported history of malignant tumor (n = 151) and a control group with no history of cancer (n = 151) hospitalized due to COVID-19 between March 2020 and August 2021. The variables registered on admission were divided into categories for which we calculated the multivariate Cox proportional hazards models. RESULTS: Multivariate Cox proportional hazards models were successfully obtained for the following categories: Patient data, Comorbidities, Signs recorded on admission, Medications used before hospitalization and Laboratory results recorded on admission. With the models developed for oncology patients, we identified the following variables that registered on patients' admission were linked to significantly increased risk of death. They are: male sex, presence of metastases in neoplastic disease, impaired consciousness (somnolence or confusion), wheezes/rhonchi, the levels of white blood cells and neutrophils. CONCLUSION: Early identification of the indicators of a poorer prognosis may serve clinicians in better tailoring surveillance or treatment among cancer patients with COVID-19.

The Risk of Autoimmunity Development following mRNA COVID-19 Vaccination.

The broad spectrum of interactions between autoimmune diseases and the SARS-CoV-2 vaccination is not fully understood. This study aims to evaluate the prevalence of anti-nuclear antibodies (ANA), anti-ENA, anticardiolipin antibodies (ACL), and anti-beta-2 glycoprotein I antibodies (anti-ß2GPI) before and after the SARS-CoV-2 mRNA vaccination in a real-life setting in healthcare professionals. The identification of risk factors associated with vaccine immunogenicity was evaluated. The study group consisted of employees of two hospitals (354 individuals). Samples for antibody assays were collected before vaccination and at 7-9 months after complete immunisation. There was no significant increase in the prevalence of ANA, ACL or anti-ß2GPI antibodies, or autoimmune diseases in subjects who were vaccinated 7-9 months after complete immunisation. In terms of detected anti-ENA, the anti-DFS70 antibodies were found in 6 times more subjects than before vaccination at the second blood draw (in 18 and 3 subjects, respectively) (p = 0.001). There were no significant relationships between a SARS-CoV-2 infection history, humoral response, cellular response, subject category, smoking, sex, body weight, ANA, anti-ENA, ACL, or anti-ß2GPI. This study revealed a possible association between the severity of vaccine adverse events (VAEs) and ANA titre. Individuals with more severe VAEs (>10 points) after the second dose of the vaccine had significantly higher ANA titre after complete immunization. When analysing the significance of time between the ANA, anti-ENA, ACL, and anti- ß2GPI assays and complete immunisation antibody values, no qualitative result was statistically significant. There was correlation between the time since complete immunization and ANA after.

The Usefulness of the COVID-GRAM Score in Predicting the Outcomes of Study Population with COVID-19.

BACKGROUND: The COVID-GRAM is a clinical risk rating score for predicting the prognosis of hospitalized COVID-19 infected patients. AIM: Our study aimed to evaluate the use of the COVID-GRAM score in patients with COVID-19 based on the data from the COronavirus in the LOwer Silesia (COLOS) registry. MATERIAL AND METHODS: The study group (834 patients of Caucasian patients) was retrospectively divided into three arms according to the risk achieved on the COVID-GRAM score calculated at the time of hospital admission (between February 2020 and July 2021): low, medium, and high risk. The Omnibus chi-square test, Fisher test, and Welch ANOVA were used in the statistical analysis. Post-hoc analysis for continuous variables was performed using Tukey's correction with the Games-Howell test. Additionally, the ROC analysis was performed over time using inverse probability of censorship (IPCW) estimation. The GRAM-COVID score was estimated from the time-dependent area under the curve (AUC). RESULTS: Most patients (65%) had a low risk of complications on the COVID-GRAM scale. There were 113 patients in the high-risk group (13%). In the medium- and high-risk groups, comorbidities occurred statistically significantly more often, e.g., hypertension, diabetes, atrial fibrillation and flutter, heart failure, valvular disease, chronic kidney disease, and obstructive pulmonary disease (COPD), compared to low-risk tier subjects. These individuals were also patients with a higher incidence of neurological and cardiac complications in the past. Low saturation of oxygen values on admission, changes in C-reactive protein, leukocytosis, hyperglycemia, and procalcitonin level were associated with an increased risk of death during hospitalization. The troponin level was an independent mortality factor. A change from low to medium category reduced the overall survival probability by more than 8 times and from low to high by 25 times. The factor with the strongest impact on survival was the absence of other diseases. The medium-risk patient group was more likely to require dialysis during hospitalization. The need for antibiotics was more significant in the high-risk group on the GRAM score. CONCLUSION: The COVID-GRAM score corresponds well with total mortality. The factor with the strongest impact on survival was the absence of other diseases. The worst prognosis was for patients who were unconscious during admission. Patients with higher COVID-GRAM score were significantly less likely to return to full health during follow-up. There is a continuing need to develop reliable, easy-to-adopt tools for stratifying the course of SARS-CoV-2 infection.

Usefulness of C2HEST Score in Predicting Clinical Outcomes of COVID-19 in Heart Failure and Non-Heart-Failure Cohorts.

BACKGROUND: Patients with heart failure represent a vulnerable population for COVID-19 and are prone to having worse prognoses and higher fatality rates. Still, the clinical course of the infection is dynamic, and complication occurrence in particular in patients with heart failure is fairly unpredictable. Considering that individual components of the C2HEST (C2: Coronary Artery Diseases (CAD)/Chronic obstructive pulmonary disease (COPD); H: Hypertension; E: Elderly (Age ≥ 75); S: Systolic HF; T: Thyroid disease) are parallel to COVID-19 mortality risk factors, we evaluate the predictive value of C2HEST score in patients with heart failure (HF) Material and Methods: The retrospective medical data analysis of 2184 COVID-19 patients hospitalized in the University Hospital in Wroclaw between February 2020 and June 2021 was the basis of the study. The measured outcomes included: in-hospital mortality, 3-month and 6-month all-cause-mortality, non-fatal end of hospitalization, and adverse in-hospital clinical events. RESULTS: The heart failure cohort consists of 255 patients, while 1929 patients were assigned to the non-HF cohort. The in-hospital, 3-month, and 6-month mortality rates were highest in the HF cohort high-risk C2HEST stratum, reaching 38.61%, 53.96%, and 65.36%, respectively. In the non-HF cohort, in-hospital, 3-month, and 6-month mortalities were also highest in the high-risk C2HEST stratum and came to 26.39%, 52.78%, and 65.0%, respectively. An additional point in the C2HEST score increased the total death intensity in 10% of HF subjects (HR 1.100, 95% CI 0.968-1.250 p = 0.143) while in the non-HF cohort, the same value increased by 62.3% (HR 1.623, 95% CI 1.518-1.734 p < 0.0001). CONCLUSIONS: The C2HEST score risk in the HF cohort failed to show discriminatory performance in terms of mortality and other clinical adverse outcomes during hospitalization. C2HEST score in the non-HF cohort showed significantly better performance in terms of predicting in-hospital and 6-month mortality and other non-fatal clinical outcomes such as cardiovascular events (myocardial injury, acute heart failure, myocardial infarction, cardiogenic shock), pneumonia, sepsis, and acute renal injury.

The assessment of the risk of COVID-19 infection and its course in the medical staff of a COVID-only and a non-COVID hospital.

BACKGROUND: Medical workers are a group that is particularly vulnerable to infection during the coronavirus disease 2019 (COVID-19) pandemic. OBJECTIVES: The study aimed to assess the risk of COVID-19 infection and its course in the medical staff of a COVID-only and a non-COVID hospital. MATERIAL AND METHODS: The observational study included 732 participants who were medical workers. The study was conducted between June 2020 and December 2020, before widespread COVID-19 immunization was introduced. RESULTS: Of the 732 employees of the hospitals, 377 had a history of COVID-19. The risk of disease was twice as high in the medical staff of the COVID-only hospital compared to the medical staff of the non-COVID hospital (odds ratio (OR) = 2.0; p < 0.001). Among medical personnel, 20.6% of the participants were asymptomatic and 6.4% required hospitalization. For the non-COVID hospital, the employees who were most frequently infected with COVID-19 were nurses/paramedics/medical caretakers. The factor influencing the risk of infection was body mass index (BMI; OR = 1.05; p = 0.004). The risk of COVID-19 infection was lower in the influenza vaccine group (OR = 2.23, p < 0.001). CONCLUSIONS: The study results indicate that employees of the hospital treating only COVID patients have a higher risk of infection. Previous observations on factors predisposing to COVID-19 infection like gender and BMI were confirmed. However, the observations carried out on the studied population did not confirm the influence of other factors, such as the coexistence of chronic diseases (apart from diabetes) on the risk of developing COVID-19. In addition, we noticed that seasonal influenza vaccination has a beneficial effect in patients with COVID-19 infection.

Complete (Humoral and Cellular) Response to Vaccination against COVID-19 in a Group of Healthcare Workers-Assessment of Factors Affecting Immunogenicity.

Vaccination is the best way to limit the extent of the COVID pandemic. Knowledge of the duration of the immune response will allow the planning of a vaccination protocol. This study aims to validate the complete (humoral and cellular) immune responses over time in large population groups following the full vaccination of healthcare professionals in real-life conditions and to assess the relationship between antibody levels and T-cell activity in relation to the characteristics of the study group. The samples for the study were obtained from volunteers (staff of two hospitals) on three occasions: before vaccination, T0, then 4-9 weeks after full vaccination (two doses BNT162b2), T1, and 7-9 months after vaccination, T2. The humoral response was investigated by the titre of anti-SARS-CoV-2 IgG antibodies to S1 protein. Assays were performed three times at intervals. The cellular response was assessed in a subgroup of 189 subjects by QuanT-Cell SARS-CoV-2 (IGRA). The assay was performed once. A group of 344 subjects fully vaccinated with the BNT162b2 vaccine were included in the study. The humoral response was observed in 100% of subjects at both 4-7 weeks and 7-9 months, but antibody titres fell by almost 90% in this interval. The cellular response was observed in 94% (177/189) of subjects 7-9 months after the second dose of vaccine. In subjects with a negative cellular response, eight out of 12 smoked. A factor associated with greater immunogenicity of vaccination was past SARS-CoV-2 infection. The administration of full BNT162b2 vaccination (two doses) induces humoral and cellular responses detectable even more than six months after vaccination. Smoking may be a factor associated with impaired cellular response to vaccination.

Post-COVID-19 syndrome in patients with primary Sjögren's syndrome after acute SARS-CoV-2 infection.

OBJECTIVES: To analyse the frequency and characteristics of post-COVID-19 syndrome in patients with primary Sjögren's syndrome (pSS) affected by acute SARS-CoV-2 infection. METHODS: By the first week of April 2021, all centres included in the Big Data Sjögren Consortium were contacted asking for patients included in the Registry diagnosed with SARSCoV-2 infection according to the ECDC guidelines. According to the NICE definitions, symptoms related to COVID-19 were classified as acute COVID-19 (signs and symptoms for up to 4 weeks), ongoing symptomatic COVID-19 (presence of signs and symptoms from 4 to 12 weeks) and post-COVID-19 syndrome (signs and symptoms that continue for > 12 weeks not explained by an alternative diagnosis after a protocolized study). RESULTS: We identified 132 patients who were followed a mean follow-up of 137.8 days (ranging from 5 days to 388 days) after being diagnosed with COVID-19. In the last visit, 75 (57%) patients remained symptomatic: 68 (52%) remained symptomatic for more than 4 weeks fulfilling the NICE definition for ongoing symptomatic post-COVID-19, and 38 (29%) remained symptomatic for more than 12 weeks fulfilling the definition of post-COVID-19 syndrome. More than 40% of pSS patients reported the persistence of four symptoms or more, including anxiety/depression (59%), arthralgias (56%), sleep disorder (44%), fatigue (40%), anosmia (34%) and myalgias (32%). Age-sex adjusted multivariate analysis identified raised LDH levels (OR 10.36), raised CRP levels (OR 7.33), use of hydroxychloroquine (OR 3.51) and antiviral agents (OR 3.38), hospital admission (OR 8.29), mean length of hospital admission (OR 1.1) and requirement of supplemental oxygen (OR 6.94) as factors associated with a higher risk of developing post-COVID-19 syndrome. A sensitivity analysis including hospital admission in the adjusted model confirmed raised CRP levels (OR 8.6, 95% CI 1.33-104.44) and use of hydroxychloroquine (OR 2.52, 95% CI 1.00-6.47) as the key independent factors associated with an enhanced risk of developing post-COVID-19 syndrome. CONCLUSIONS: This is the first study that analyses the frequency and characteristics of post-COVID-19 syndrome in patients affected by a systemic autoimmune disease. We found that 57% of patients with pSS affected by COVID-19 remain symptomatic after a mean follow-up of 5 months. The risk of developing post-COVID-19 syndrome in patients who required hospitalisation was 8-times higher than in non-hospitalised patients, with baseline raised CRP levels and the use of hydroxychloroquine being independent risk factors for post-COVID-19.