Incidence and Risk Factors for Clostridioides difficile Infections in Non-COVID and COVID-19 Patients: Experience from a Tertiary Care Hospital.

(1) Background: The aim of this study was to assess the incidence and the risk factors for healthcare-associated Clostridioides difficile infection (HA-CDI) in patients with COVID-19 and without this infection. (2) Methods: A single-center, prospective observational study was conducted at the University Clinical Hospital Center in Belgrade, Serbia, from January 2019 to December 2021. The entire hospital was a COVID-dedicated hospital for 12 months during the study period. The incidence density rates and risk factors for HA-CDI in patients with and without COVID-19 are presented. (3) Results: The incidence rates of HA-CDIs were three times higher in patients with COVID-19. The HA-CDI-COVID-patients were younger (69.9 ± 12.6 vs. 72.5 ± 11.6; p = 0.017), admitted from another hospital (20.5% vs. 2.9; p < 0.001), had antimicrobial therapy before CDI (99.1% vs. 91.3%, p < 0.001), received two or more antibiotics (p = 0.030) during a longer period (p = 0.035), received proton pump inhibitors (95.9% vs. 50.0%, p < 0.001) during a longer period (p = 0.012) and steroids (32.8% vs. 20.4%, p < 0.001). During the last month before their current hospitalization, a higher percentage of patients without COVID-19 disease were hospitalized in our hospital (p < 0.001). Independent predictors for HA-CDIs in patients with COVID-19 were admission from another hospital (p = 0.003), the length of antibiotic administration (0.020), and the use of steroids in therapy (p < 0.001). The HA-CDI predictors in the non-COVID patients were older age (p = 0.017), advanced-stage renal failure (p = 0.005), chemotherapy (p = 0.003), and a low albumin level (0.005). (4) Conclusion: Higher incidence rates of HAI-CDIs in COVID-19 patients did not occur due to reduced infection control precautions and hygiene measures but due to antibiotic therapy and therapy with other drugs used during the pandemic.

Characteristics and Outcomes of Patients with Acute Coronary Syndrome and COVID-19.

Acute coronary syndrome (ACS) in patients with COVID-19 is triggered by various mechanisms and can significantly affect the patient's further treatment and prognosis. The study aimed to investigate the characteristics, major complications, and predictors of mortality in COVID-19 patients with ACS. All consecutive patients hospitalized from 5 July 2020 to 5 May 2021 for ACS with confirmed SARS-Co-2 were prospectively enrolled and tracked for mortality until 5 June 2021. Data from the electronic records for age and diagnosis, matched non-COVID-19 and COVID-19 ACS group, were extracted and compared. Overall, 83 COVID-19 ACS patients, when compared to 166 non-COVID ACS patients, had significantly more prevalent comorbidities, unfavorable clinical characteristics on admission (acute heart failure 21.7% vs. 6.6%, p < 0.01) and higher rates of major complications, 33.7% vs. 16.8%, p < 0.01, and intrahospital 30-day mortality, 6.7% vs. 26.5%, p < 0.01. The strongest predictors of mortality were aortic regurgitation, HR 9.98, 95% CI 1.88; 52.98, p < 0.01, serum creatinine levels, HR 1.03, 95% CI 1.01; 1.04, p < 0.01, and respiratory failure therapy, HR 13.05, 95% CI 3.62; 47.01, p < 0.01. Concomitant ACS and COVID-19 is linked to underlying comorbidities, adverse presenting features, and poor outcomes. Urgent strategies are needed to improve the outcomes of these patients.

Bradykinin and Galectin-3 in Survived and Deceased Patients with COVID-19 Pneumonia: An Increasingly Promising Biochemical Target

Introduction There are still no definite curative or preventive strategies for COVID-19 disease. It is crucial to fully comprehend the pathogenesis of COVID-19 infection so that we can develop expedient pharmacological protocols. While the impact of cytokine storm on COVID-19 severity has been one of the most tested hypotheses, the role of bradykinin and various other oxidative stress markers has been relatively under-researched. Their levels can be determined immediately after a hospital admission so they could be used as early predictors of the further development of the disease. Aim The study aims at evaluating the possibility of using bradykinin and galectin-3 levels as early predictors that COVID-19 disease will progress into a severe case. Material and methods. The study was conducted as a prospective cross-sectional study. It included 47 consecutive adult patients with confirmed SARS-CoV-2 infection and COVID-19 pneumonia. All study subjects were admitted for a hospital treatment to the tertiary Clinical Hospital Center Bezanijska kosa, Belgrade, Serbia on June 2021. The blood samples were collected at the patients' admission. The analyses of demographic, radiological, and clinical data were later conducted for both groups (the deceased patients and those who survived). In addition, we analyzed the potential relations between the outcome and the levels of bradykinin and galectin-3 measured immediately after the patients were admitted to the hospital. Results The patients who passed away were predominantly older men with comorbidities. We recorded higher CT scores in the deceased patients and the significantly higher levels of urea, creatinine, CK, troponine, CRP, and other laboratory markers. They stayed at the ICU unit longer and required mechanical ventilation more frequently than the patients who survived. On the other hand, no differences were recorded in the time periods passing from the onset of the systems to the hospital admissions. Finally, we can highlight several independent predictors of mortality in patients with COVID-19 pneumonia, including the following: (1) patients who are 50 or more years old, (2) with in-hospital stays are longer that 4 days, (3) bradykinin levels surpass 220000 pg/ml, (4) D-dimer, creatinine, and CRP are elevated, and (5) comorbidities were present (such as hypertension and diabetes). Conclusion The present study strongly supports the bradykinin storm hypothesis. Since elevated bradykinin levels have been found in most COVID-19 cases with fatal outcomes, the future therapeutical strategies for COVID-19 have to be focused on reducing bradykinin serum concentrations.

Point-of-Care Echocardiographic Characteristics of COVID-19 Patients with Pulmonary Embolism.

INTRODUCTION: Thrombotic complications, such as pulmonary embolism, are common in COVID-19 patients. Point-of-care ultrasound is a highly recommended tool for orientation in critically ill patients with suspected or confirmed complications. METHODS: An observational study was conducted on 32 consecutive patients with confirmed pulmonary embolism and COVID-19 infection treated in the Intensive Care Unit of the University Hospital Medical Center "Bezanijska kosa", Belgrade, Serbia, between April 2021 and March 2022. Predictors of the need for oxygen support were determined, while point-of-care echocardiographic parameters and various anamnestic, laboratory, and clinically significant parameters were correlated with the Pulmonary Embolism Severity Index (PESI) score. RESULTS: More than two-thirds of patients in our study had PE symptoms present at hospital admission (68.8%). The majority of patients had segmental pulmonary embolism (48.4%), with high to very high PESI score values in 31.3% of patients. Pneumonia was present in 68.8% of the study population. The PESI score was negatively correlated with diastolic blood pressure and SaO2 at the time of PE diagnosis, LV ejection fraction, and PVAT. A positive correlation was found between the PESI score, maximum CRP, and D-dimer at the time of PTE diagnosis. A larger right ventricular diameter was associated with a greater need for oxygen support. CONCLUSION: Point-of-care echocardiography is a valuable tool for the risk assessment of COVID-19 patients with pulmonary embolism. Right ventricular size stood out as a significant marker of disease severity.

Elevated Transaminases as Predictors of COVID-19 Pneumonia Severity.

BACKGROUND: This study aimed to calculate the frequency of elevated liver enzymes in hospitalized patients with coronavirus disease 2019 (COVID-19) infection and to test if liver enzyme biochemistry levels on admission could predict the computed tomography (CT) scan severity score of bilateral interstitial pneumonia. METHODS: This single-center study comprised of 323 patients including their demographic data, laboratory analyses, and radiological findings. All the information was taken from electronic health records, followed by statistical analysis. RESULTS: Out of 323 patients, 115 of them (35.60%) had aspartate aminotransferase (AST) and/or alanine aminotransferase (ALT) over 40 U/L on admission. AST was the best predictor of CT scan severity score of bilateral interstitial pneumonia (R2 = 0.313, Adjusted R2 = 0.299). CT scan severity score in the peak of the infection could be predicted with the value of AST, neutrophils, platelets, and monocytes count (R2 = 0.535, Adjusted R2 = 0.495). CONCLUSION: AST, neutrophils, platelets, and monocytes count on admission can account for almost half (49.5%) of the variability in CT scan severity score at peak of the disease, predicting the extensiveness of interstitial pneumonia related to COVID-19 infection. Liver enzymes should be closely monitored in order to stratify COVID-19 patients with a higher risk of developing severe forms of the disease and to plan the beforehand step-up treatment.

COVID-19 Vaccination Willingness and Vaccine Uptake among Healthcare Workers: A Single-Center Experience.

Healthcare workers (HCWs) are at higher risk of developing COVID-19 due to their professional exposition to the SARS-CoV-2 virus. This study assesses the intention of vaccination against COVID-19 before the vaccines were approved, and the rate of vaccine uptake during the first nine months of immunization among HCWs. A cross-sectional seroprevalence study was carried out during July 2020 in University Clinical Hospital Center Bezanijska Kosa in Belgrade, Serbia that included 62.8% of all HCWs. Besides serological testing for IgG antibodies, data about HCWs' intention to accept COVID-19 vaccination if a vaccine became available were collected. This cohort of HCWs was followed up until the end of October 2021 to assess the number of vaccinated and PCR-positive staff. In the cross-sectional study, 18.3% HCWs had positive SARS-CoV-2 IgG antibodies without difference with IgG-negative HCWs regarding age, gender, profession type, and years of service. Before vaccines became available, a significantly higher percentage of IgG-positive HCWs compared to IgG-negative HCWs was unsure whether to be vaccinated (62.5% vs. 49.0%), and significantly fewer stated that they would not be vaccinated (16.7% vs. 25.1%). When the vaccines became available in Serbia, among IgG-negative HCWs, those who stated clear positive (yes) and clear negative (no) attitude toward vaccination before the immunization period had begun were vaccinated at 28% and 20%, respectively, while 51% of unsure HCWs received a vaccine (p = 0.006). Among IgG-positive HCWs, there was no statistical difference in vaccine uptake regarding those with previous negative, positive, and unsure opinions about vaccination (p = 0.498). In multivariate analysis, independent factors associated with uptake were being female (OR = 1.92; 95%CI: 1.04-3.55), age of 30-59 years, previously vaccine-unsure (OR = 1.84; 95%CI: 1.04-3.25), and those with previous positive vaccine attitudes (OR = 2.48; 95%CI:1.23-5.01), while nurses were less likely to become vaccinated (OR = 0.39 95% CI: 0.20-0.75) These findings indicate a positive change in attitudes of HCWs towards COVID-19 vaccination.

D-dimer, CRP, PCT, and IL-6 Levels at Admission to ICU Can Predict In-Hospital Mortality in Patients with COVID-19 Pneumonia.

INTRODUCTION: Health care workers have had a challenging task since the COVID-19 outbreak. Prompt and effective predictors of clinical outcomes are crucial to recognize potentially critically ill patients and improve the management of COVID-19 patients. The aim of this study was to identify potential predictors of clinical outcomes in critically ill COVID-19 patients. METHODS: The study was designed as a retrospective cohort study, which included 318 patients treated from June 2020 to January 2021 in the Intensive Care Unit (ICU) of the Clinical Hospital Center "Bezanijska Kosa" in Belgrade, Serbia. The verified diagnosis of COVID-19 disease, patients over 18 years of age, and the hospitalization in ICU were the criteria for inclusion in the study. The optimal cutoff value of D-dimer, CRP, IL-6, and PCT for predicting hospital mortality was determined using the ROC curve, while the Kaplan-Meier method and log-rank test were used to assess survival. RESULTS: The study included 318 patients: 219 (68.9%) were male and 99 (31.1%) female. The median age of patients was 69 (60-77) years. During the treatment, 195 (61.3%) patients died, thereof 130 male (66.7%) and 65 female (33.3%). 123 (38.7%) patients were discharged from hospital treatment. The cutoff value of IL-6 for in-hospital death prediction was 74.98 pg/mL (Sn 69.7%, Sp 62.7%); cutoff value of CRP was 81 mg/L (Sn 60.7%, Sp 60%); cutoff value of procalcitonin was 0.56 ng/mL (Sn 81.1%, Sp 76%); and cutoff value of D-dimer was 760 ng/mL FEU (Sn 63.4%, Sp 57.1%). IL-6 ≥ 74.98 pg/mL, CRP ≥ 81 mg/L, PCT ≥ 0.56 ng/mL, and D-dimer ≥ 760 ng/mL were statistically significant predictors of in-hospital mortality. CONCLUSION: IL-6 ≥ 74.98 pg/mL, CRP values ≥ 81 mg/L, procalcitonin ≥ 0.56 ng/mL, and D-dimer ≥ 760 ng/mL could effectively predict in-hospital mortality in COVID-19 patients.

COVID-19 Vaccination Willingness and Vaccine Uptake among Healthcare Workers: A Single-Center Experience

Healthcare workers (HCWs) are at higher risk of developing COVID-19 due to their professional exposition to the SARS-CoV-2 virus. This study assesses the intention of vaccination against COVID-19 before the vaccines were approved, and the rate of vaccine uptake during the first nine months of immunization among HCWs. A cross-sectional seroprevalence study was carried out during July 2020 in University Clinical Hospital Center Bezanijska Kosa in Belgrade, Serbia that included 62.8% of all HCWs. Besides serological testing for IgG antibodies, data about HCWs' intention to accept COVID-19 vaccination if a vaccine became available were collected. This cohort of HCWs was followed up until the end of October 2021 to assess the number of vaccinated and PCR-positive staff. In the cross-sectional study, 18.3% HCWs had positive SARS-CoV-2 IgG antibodies without difference with IgG-negative HCWs regarding age, gender, profession type, and years of service. Before vaccines became available, a significantly higher percentage of IgG-positive HCWs compared to IgG-negative HCWs was unsure whether to be vaccinated (62.5% vs. 49.0%), and significantly fewer stated that they would not be vaccinated (16.7% vs. 25.1%). When the vaccines became available in Serbia, among IgG-negative HCWs, those who stated clear positive (yes) and clear negative (no) attitude toward vaccination before the immunization period had begun were vaccinated at 28% and 20%, respectively, while 51% of unsure HCWs received a vaccine (p = 0.006). Among IgG-positive HCWs, there was no statistical difference in vaccine uptake regarding those with previous negative, positive, and unsure opinions about vaccination (p = 0.498). In multivariate analysis, independent factors associated with uptake were being female (OR = 1.92;95%CI: 1.04–3.55), age of 30–59 years, previously vaccine-unsure (OR = 1.84;95%CI: 1.04–3.25), and those with previous positive vaccine attitudes (OR = 2.48;95%CI:1.23–5.01), while nurses were less likely to become vaccinated (OR = 0.39 95% CI: 0.20–0.75) These findings indicate a positive change in attitudes of HCWs towards COVID-19 vaccination.

Characteristics and Outcomes of Patients with Acute Coronary Syndrome and COVID-19

Acute coronary syndrome (ACS) in patients with COVID-19 is triggered by various mechanisms and can significantly affect the patient's further treatment and prognosis. The study aimed to investigate the characteristics, major complications, and predictors of mortality in COVID-19 patients with ACS. All consecutive patients hospitalized from 5 July 2020 to 5 May 2021 for ACS with confirmed SARS-Co-2 were prospectively enrolled and tracked for mortality until 5 June 2021. Data from the electronic records for age and diagnosis, matched non-COVID-19 and COVID-19 ACS group, were extracted and compared. Overall, 83 COVID-19 ACS patients, when compared to 166 non-COVID ACS patients, had significantly more prevalent comorbidities, unfavorable clinical characteristics on admission (acute heart failure 21.7% vs. 6.6%, p < 0.01) and higher rates of major complications, 33.7% vs. 16.8%, p < 0.01, and intrahospital 30-day mortality, 6.7% vs. 26.5%, p < 0.01. The strongest predictors of mortality were aortic regurgitation, HR 9.98, 95% CI 1.88;52.98, p < 0.01, serum creatinine levels, HR 1.03, 95% CI 1.01;1.04, p < 0.01, and respiratory failure therapy, HR 13.05, 95% CI 3.62;47.01, p < 0.01. Concomitant ACS and COVID-19 is linked to underlying comorbidities, adverse presenting features, and poor outcomes. Urgent strategies are needed to improve the outcomes of these patients.

Development and Validation of a Multivariable Predictive Model for Mortality of COVID-19 Patients Demanding High Oxygen Flow at Admission to ICU: AIDA Score.

INTRODUCTION: Risk stratification is an important aspect of COVID-19 management, especially in patients admitted to ICU as it can provide more useful consumption of health resources, as well as prioritize critical care services in situations of overwhelming number of patients. MATERIALS AND METHODS: A multivariable predictive model for mortality was developed using data solely from a derivation cohort of 160 COVID-19 patients with moderate to severe ARDS admitted to ICU. The regression coefficients from the final multivariate model of the derivation study were used to assign points for the risk model, consisted of all significant variables from the multivariate analysis and age as a known risk factor for COVID-19 patient mortality. The newly developed AIDA score was arrived at by assigning 5 points for serum albumin and 1 point for IL-6, D dimer, and age. The score was further validated on a cohort of 304 patients admitted to ICU due to the severe form of COVID-19. RESULTS: The study population included 160 COVID-19 patients admitted to ICU in the derivation and 304 in the validation cohort. The mean patient age was 66.7 years (range, 20-93 years), with 68.1% men and 31.9% women. Most patients (76.8%) had comorbidities with hypertension (67.7%), diabetes (31.7), and coronary artery disease (19.3) as the most frequent. A total of 316 patients (68.3%) were treated with mechanical ventilation. Ninety-six (60.0%) in the derivation cohort and 221 (72.7%) patients in the validation cohort had a lethal outcome. The population was divided into the following risk categories for mortality based on the risk model score: low risk (score 0-1) and at-risk (score > 1). In addition, patients were considered at high risk with a risk score > 2. By applying the risk model to the validation cohort (n = 304), the positive predictive value was 78.8% (95% CI 75.5% to 81.8%); the negative predictive value was 46.6% (95% CI 37.3% to 56.2%); the sensitivity was 82.4% (95% CI 76.7% to 87.1%), and the specificity was 41.0% (95% CI 30.3% to 52.3%). The C statistic was 0.863 (95% CI 0.805-0.921) and 0.665 (95% CI 0.598-0.732) in the derivation and validation cohorts, respectively, indicating a high discriminative value of the proposed score. CONCLUSION: In the present study, AIDA score showed a valuable significance in estimating the mortality risk in patients with the severe form of COVID-19 disease at admission to ICU. Further external validation on a larger group of patients is needed to provide more insights into the utility of this score in everyday practice.

Predictors of Mortality in Critically Ill COVID-19 Patients Demanding High Oxygen Flow: A Thin Line between Inflammation, Cytokine Storm, and Coagulopathy.

INTRODUCTION: Mortality among critically ill COVID-19 patients remains relatively high despite different potential therapeutic modalities being introduced recently. The treatment of critically ill patients is a challenging task, without identified credible predictors of mortality. METHODS: We performed an analysis of 160 consecutive patients with confirmed COVID-19 infection admitted to the Respiratory Intensive Care Unit between June 23, 2020, and October 2, 2020, in University Hospital Center Bezanijska kosa, Belgrade, Serbia. Patients on invasive, noninvasive ventilation and high flow oxygen therapy with moderate to severe ARDS, according to the Berlin definition of ARDS, were selected for the study. Demographic data, past medical history, laboratory values, and CT severity score were analyzed to identify predictors of mortality. Univariate and multivariate logistic regression models were used to assess potential predictors of mortality in critically ill COVID-19 patients. RESULTS: The mean patient age was 65.6 years (range, 29-92 years), predominantly men, 68.8%. 107 (66.9%) patients were on invasive mechanical ventilation, 31 (19.3%) on noninvasive, and 22 (13.8%) on high flow oxygen therapy machine. The median total number of ICU days was 10 (25th to 75th percentile: 6-18), while the median total number of hospital stay was 18 (25th to 75th percentile: 12-28). The mortality rate was 60% (96/160). Univariate logistic regression analysis confirmed the significance of age, CRP, and lymphocytes at admission to hospital, serum albumin, D-dimer, and IL-6 at admission to ICU, and CT score. Serum albumin, D-dimer, and IL-6 at admission to ICU were independently associated with mortality in the final multivariate analysis. CONCLUSION: In the present study of 160 consecutive critically ill COVID-19 patients with moderate to severe ARDS, IL-6, serum albumin, and D-dimer at admission to ICU, accompanied by chest CT severity score, were marked as independent predictors of mortality.