COVID-19 in Liver Transplant Patients: A University Hospital Experience.

BACKGROUND: We aimed to examine the comorbidity, disease progress, and vaccination status of liver transplant patients followed up in our hospital who had COVID-19. METHODS: Liver transplant patients with COVID-19 were included between 11 March 2020 and 15 September 2022. Demographic data, disease progress, and COVID-19 vaccines were recorded. The SPSS 24.0 (IBM SPSS, Inc, Armonk, NY, United States) program was used for analysis. The data were analyzed using the χ2 test. P values < .05 were considered clinically significant. RESULTS: Sixteen SARS-CoV-2 polymerase chain reaction (+) patients were detected. Twelve (75.0%) patients were male; the mean age was 49.56 ± 14.0 years (24-76 years). The mean transplant time was 156.69 ± 54.05 months. Four (25.0%) of the 5 (31.3%) patients with comorbidities had hypertension, and 1 (6.3%) had diabetes. None of the patients had an underlying lung disease. All the patients received immunosuppressive therapy, and the most common combination was antimetabolite and calcineurin inhibitor (9 patients [69.2%]). Nine patients (56.3%) had a fever, whereas 6 (37.5%) had respiratory symptoms. Two (33.3%) had pneumonia. Five (31.4%) patients were hospitalized, and 1 (20%) was admitted to the intensive care unit due to non-invasive mechanical ventilation needs. No patient died due to COVID-19. A statistically significant correlation was found between the presence of fever, respiratory symptoms, and hospitalization (P < .05). Of those vaccinated, 10 (66.7%) were infected before the COVID-19 vaccination. CONCLUSIONS: The course of COVID-19 in liver recipients without any underlying disease other than transplantation is not different from that in the healthy population. Immunosuppressive therapy was continued in patients with the disease, and two-thirds did not require hospitalization.

COVID-19 IN LIVER TRANSPLANT PATIENTS: A UNIVERSITY HOSPITAL EXPERIENCE

Aim: We aimed to examine the comorbidity, disease progress and vaccination status of the liver transplant patients followed up in our hospital who had COVID-19. Method: Liver transplant patients with COVID-19 were included between 11 March 2020 and 15 September 2022. Demographic data, disease progress and COVID-19 vaccines were recorded. SPSS24.0 program was used for analysis. The data were analyzed with the chi-square test. P values ​​<0.05 were considered clinically significant. Results: SARS-CoV-2 PCR(+) 16 patients were detected. Twelve (75.0%) patients were male, and the mean age was 49.56 ± 14.0 (24-76). The mean transplant time was 156.69 ± 54.05 months. Four (25.0%) of the five (31.3%) patients with comorbidities had hypertension and one (6.3%) had diabetes. None of the patients had an underlying lung disease. All the patients received immunosuppressive therapy, and the most common combination was the antimetabolite and calcineurin inhibitor group [9 patients (69.2%)]. Nine patients (56.3%) had fever, while six (37.5%) had respiratory symptoms. Two (33.3%) of them had pneumonia. Five (31.4%) patients were hospitalized, and one (20%) was admitted to ICU due to non-invasive mechanical ventilation needs. No patient died due to COVID-19. A statistically significant correlation was found between the presence of fever, respiratory symptoms and hospitalization(p<0.05). Of those vaccinated, 10 (66.7%) were infected before COVID-19 vaccination. Conclusion: The course of COVID-19 in liver recipients without any underlying disease other than transplantation is not different from the healthy population. Immunosuppressive therapy continued in patients with the disease, and two-thirds did not require hospitalization.

Evaluation of SARS-CoV-2 antibody persistence and viral spread in stool: a long-term care experience before COVID-19 vaccination.

BACKGROUND: Due to elderly residents, nursing homes/assisted living facilities were the most affected places in COVID-19 pandemic. Besides symptomatic patients, asymptomatic patients were detected during routine screening. AIM: This study aims to determine the factors that affect antibody response and viral shedding in stool samples after natural exposure to the virus in residents and staff who recovered from COVID-19 before the vaccine was available. METHODS: This prospective cross-sectional study was conducted at the nation's highest-capacity Residential and Nursing Home. Blood samples were collected between December 15, 2020 and January 15, 2021 from participating residents and staff for anti-SARS-CoV-2 antibody testing. Stool samples were obtained for SARS-CoV-2 PCR testing 2 months after COVID-19. The Social Sciences (SPSS) program version 15.0 was used for statistical analysis. The Mann-Whitney U test compared SARS-CoV-2 antibody concentration between two groups. RESULTS: Four hundred sixty-four (52.3%) residents and 424 (47.7%) staff participated. Entirely 259 (29.2%) participants were anti-SARS-CoV-2 IgG (+) and 255 (28.7%) were SARS-CoV-2 PCR (+). Both antibody and PCR positivity was detected in 196 (76.9%). In PCR (-) group, 63 (10.0%) participants were SARS-CoV-2 IgG (+). Antibody titers were found highest in SARS-CoV-2 PCR (+) male residents. SARS-CoV-2 IgG titers were significantly high in SARS-CoV-2 PCR (+) and hospitalized participants regardless of age. Stool samples were obtained from 61(23.9%) participants and were found negative. CONCLUSION: A durable SARS-CoV-2 IgG antibody response was monitored at least 9 months after the participants were diagnosed with COVID-19. SARS-CoV-2 antibody positivity was detected 76.9% in PCR (+) and 10.0% in PCR (-) participants. Knowing the duration of detectable antibodies is an important finding for developing disease prevention and public health strategies.

Fungal colonization and infections in patients with COVID-19 in intensive care units: A real-life experience at a tertiary-care hospital.

PURPOSE: To evaluate the management of patients with COVID-19 in the intensive care units (ICUs) with fungal infection/colonization and to highlight diagnostic problems in these patients. METHODS: We included all patients with a COVID-19 diagnosis who were aged ≥18 years and followed in the ICU for the first 8 months. Patient data were obtained from medical records. We compared the risk factors, laboratory data, and outcomes of patients with fungal infection/colonization. RESULTS: A total of 118 patients (81 men and 37 women) were included. The mean age was 70.3 ± 14.8 (35-94) years. Of the patients, 79 (66.9%) patients were ≥65 years old. Fungal infection/colonization was detected in 39 (33.1%) patients. Fungi were isolated from 34 (28.8%) patients. Ten fungal species were isolated from 51 samples (the most common being Candida albicans). Three patients (2.5%) had proven candidemia. We observed two (1.7%) possible cases of COVID-19-associated pulmonary aspergillosis (CAPA). Eighteen patients (15.3%) underwent antifungal therapy. The risk of fungal infection/colonization increased as the duration of invasive mechanical ventilation increased. The fatality rate was 61.9% and increased with age and the use of mechanical ventilation. The fatality rate was 4.2-times-higher and the use of mechanical ventilation was 35.9-times-higher in the patients aged ≥65 years than in the patients aged <65 years. No relationship was found between fungal colonization/infection, antifungal treatment, and the fatality rate. CONCLUSION: During the pandemic, approximately one-third of the patients in ICUs exhibited fungal infection/colonization. Candida albicans was the most common species of fungal infection as in the pre-pandemic area. Because of the cross-contamination risk, we did not performed diagnostic bronchoscopy and control thorax computed tomography during the ICU stay, and our patients mainly received empirical antifungal therapy.

Antibiotic use and Influencing Factors Among Hospitalized Patients with COVID-19: A Multicenter Point-Prevalence Study from Turkey

Background: Broad-spectrum empirical antimicrobials are frequently prescribed for patients with coronavirus disease 2019 (COVID-19) despite the lack of evidence for bacterial coinfection. Aims: We aimed to cross-sectionally determine the frequency of antibiotics use, type of antibiotics prescribed, and the factors influencing antibiotics use in hospitalized patients with COVID-19 confirmed by polymerase chain reaction. Study Design: The study was a national, multicenter, retrospective, and single-day point prevalence study. Methods: This was a national, multicenter, retrospective, and single-day point-prevalence study, conducted in the 24-h period between 00:00 and 24:00 on November 18, 2020, during the start of the second COVID-19 peak in Turkey. Results: A total of 1500 patients hospitalized with a diagnosis of COVID-19 were included in the study. The mean age ± standard deviation of the patients was 65.0 ± 15.5, and 56.2% (n = 843) of these patients were men. Of these hospitalized patients, 11.9% (n = 178) were undergoing invasive mechanical ventilation or ECMO. It was observed that 1118 (74.5%) patients were receiving antibiotics, of which 416 (37.2%) were prescribed a combination of antibiotics. In total, 71.2% of the patients had neither a clinical diagnosis nor microbiological evidence for prescribing antibiotics. In the multivariate logistic regression analysis, hospitalization in a state hospital (p < 0.001), requiring any supplemental oxygen (p = 0.005), presence of moderate/diffuse lung involvement (p < 0.001), C-reactive protein > 10 ULT coefficient (p < 0.001), lymphocyte count < 800 (p = 0.007), and clinical diagnosis and/or confirmation by culture (p < 0.001) were found to be independent factors associated with increased antibiotic use. Conclusion: The necessity of empirical antibiotics use in patients with COVID-19 should be reconsidered according to their clinical, imaging, and laboratory findings.

Risk factors associated with mortality in intensive care COVID-19 patients: the importance of chest CT score and intubation timing as risk factors

Background/aim: Coronavirus disease 2019 (COVID-19) is a disease with a high rate of progression to critical illness. However, the predictors of mortality in critically ill patients admitted to the intensive care unit (ICU) are not yet well understood. In this study, we aimed to investigate the risk factors associated with ICU mortality in our hospital. Materials and methods: In this single-centered retrospective study, we enrolled 86 critically ill adult patients with COVID-19 admitted to ICU of Dokuz Eylül University Hospital (Izmir, Turkey) between 18 March 2020 and 31 October 2020. Data on demographic information, preexisting comorbidities, treatments, the laboratory findings at ICU admission, and clinical outcomes were collected. The chest computerized tomography (CT) of the patients were evaluated specifically for COVID-19 and CT score was calculated. Data of the survivors and nonsurvivors were compared with survival analysis to identify risk factors of mortality in the ICU. Results: The mean age of the patients was 71.1 ± 14.1 years. The patients were predominantly male. The most common comorbidity in patients was hypertension. ICU mortality was 62.8%. Being over 60 years old, CT score > 15, acute physiology and chronic health evaluation (APACHE) II score ≥ 15, having dementia, treatment without favipiravir, base excess in blood gas analysis ≤ ­2.0, WBC > 10,000/mm3, D-dimer > 1.6 µg/mL, troponin > 24 ng/L, Na ≥ 145 mmol/L were considered to link with ICU mortality according to Kaplan­Meier curves (log-rank test, p < 0.05). The APACHE II score (HR: 1.055, 95% CI: 1.021­1.090) and chest CT score (HR: 2.411, 95% CI:1.193­4.875) were associated with ICU mortality in the cox proportional-hazard regression model adjusted for age, dementia, favipiravir treatment and troponin. Howewer, no difference was found between survivors and nonsurvivors in terms of intubation timing. Conclusions: COVID-19 patients have a high ICU admission and mortality rate. Studies in the ICU are also crucial in this respect. In our study, we investigated the ICU mortality risk factors of COVID-19 patients. We determined a predictive mortality model consisting of APACHE II score and chest CT score. It was thought that this feasible and practical model would assist in making clinical decisions.