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 (25^th to 75^th percentile: 6–18), while the median total number of hospital stay was 18 (25^th to 75^th 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.

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.

(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.

Cancer-promoting proinflammatory microenvironment influences colorectal cancer (CRC) development. We examined the biomarkers of inflammation, intestinal differentiation, and DNA activity correlated with the clinical parameters to observe progression and prognosis in the adenocarcinoma subtype of CRC. Their immunohistology, immunoblotting, and RT-PCR analyses were performed in the adenocarcinoma and neighboring healthy tissues of 64 patients with CRC after routine colorectal surgery. Proinflammatory nuclear factor kappa B (NFκB) signaling as well as interleukin 6 (IL-6) and S100 protein levels were upregulated in adenocarcinoma compared with nearby healthy colon tissue. In contrast to nitrotyrosine expression, the oxidative stress marker 8-Hydroxy-2′-deoxyguanosine (8-OHdG) was increased in adenocarcinoma tissue. Biomarkers of intestinal differentiation β-catenin and mucin 2 (MUC2) were inversely regulated, with the former upregulated in adenocarcinoma tissue and positively correlated with tumor marker CA19-9. Downregulation of MUC2 expression correlated with the increased 2-year survival rate of patients with CRC. Proliferation-related mammalian target of rapamycin (mTOR) signaling was activated, and Ki67 frequency was three-fold augmented in positive correlation with metastasis and cancer stage, respectively. Conclusion: We demonstrated a parallel induction of oxidative stress and inflammation biomarkers in adenocarcinoma tissue that was not reflected in the neighboring healthy colon tissue of CRC. The expansiveness of colorectal adenocarcinoma was confirmed by irregular intestinal differentiation and elevated proliferation biomarkers, predominantly Ki67. The origin of the linked inflammatory factors was in adenocarcinoma tissue, with an accompanying systemic immune response.

Background/Objectives: Composite hemangioendothelioma (CHE) is a rare vascular endothelial tumor with borderline malignancy. This study presents a case of CHE and an updated systematic review of previously reported cases, providing insights into recurrence patterns and survival outcomes. Methods: A comprehensive electronic search was conducted across PubMed, Scopus, the Cochrane Library, and Web of Science up to 31 December 2024, to identify eligible case reports. Kaplan–Meier curves were used to estimate event-free survival. Results: We report a 61-year-old man with a splenic lesion associated with weight loss and abdominal pain persisting for 1 year. Intraoperative findings revealed an enlarged spleen and multiple hepatic deposits. Splenectomy and liver biopsy revealed a well-demarcated, nodular tumor measuring 160 × 145 × 100 mm, with histological and immunohistochemical findings consistent with CHE, complicated by hepatic metastasis. Of 405 potentially eligible studies, 59 were included in the review, covering cases from 2000 to 2024, with a peak in 2020 and 2023. The median age of patients was 42 years, with the most common tumor sites being the lower extremities (30.48%), followed by the face, head, and neck (20.95%), and upper extremities (18.1%). Surgical intervention was the most common treatment (60.95%). Recurrence-free survival was observed in 42.86% of cases, while 15.24% experienced recurrence with or without metastasis. Two patients (1.90%) died from the disease. The median recurrence-free survival was 48 months (95% CI: 7.3–88.7). Conclusions: CHE exhibits significant morphological variation and can mimic other vascular tumors. Accurate diagnosis is crucial for proper prognosis and avoiding overtreatment due to misdiagnosis as more aggressive neoplasms. Patients with high-risk CHE should undergo closer surveillance to ensure timely detection of progression.

Background/Objectives: Data about the relationship between COVID-19 and healthcare-associated Clostridioides difficile infection (HA-CDI) occurrence are still controversial. This study examines antibiotics associated with CDI in patients with and without COVID-19 infection. Methods: A prospective cohort study was conducted at the University Clinical Center Belgrade, Serbia, from January 2019 to December 2021. Patients with the first episode of HA-CDI without and with COVID-19 were included. Results of bacteriology analyses, demographic and clinical data, and data on antibiotic usage and daily defined doses (DDD) were collected by the hospital Infection Control Team. Results: Out of 547 HA-CDI cases, 341 (62.3%) had COVID-19 infection. HA-CDI patients with COVID-19 were significantly younger (p = 0.017) with fewer comorbidities (<0.001). Two or more antibiotics in therapy were more frequently used by those patients (p = 0.03). COVID-19 patients were treated significantly more by third- and fourth-generation cephalosporins, fluoroquinolones (p < 0.001) and macrolides (p = 0.01). Ceftriaxone had a higher median DDD in COVID-19 patients (6.00, range 1.00–20.00) compared to non-COVID-19 patients (4.00, range 1.00–14.00), (p = 0.007). Conversely, meropenem showed a lower median DDD in COVID-19 patients. Multivariate analysis identified the use of fourth-generation cephalosporins and fluoroquinolones as independent risk factors for HA-CDI in COVID-19 patients. Conclusions: Patients with HA-CDI and COVID-19 more frequently received two or more antibiotics before the onset of HAI-CDI. The third and fourth generations of cephalosporins, fluoroquinolones and macrolides were administered significantly more often in these patients. More frequent administration of ceftriaxone was observed, but the lower DDD associated with meropenem needed additional analysis.