The hepatitis B virus (HBV) is one of the major causes of chronic liver disease. From the perspective of hospital workers (HWs), employees are at risk of he ...

Background and Objective: Multidrug and carbapenem resistant gram-negative bacilli bloodstream infections cause high mortality in intensive care units (ICUs). Predicting mortality can improve treatment and support end-of-life decisions. This study aimed to develop a machine learning model to predict mortality in ICU patients with these infections. Methods: This retrospective cohort study was conducted at a tertiary care medical center between 2017 and 2023. Adult ICU patients with bloodstream infections caused by multidrug and carbapenem resistant Klebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii were included. Demographic, clinical, and laboratory data were collected. Mann-Whitney U and Chi-square tests were used to compare the groups. Multivariable analysis with binary logistic regression was used to identify mortality risk factors. Ten machine learning classifiers were evaluated using stratified 5-fold cross-validation, and model predictions were interpreted with SHapley Additive exPlanations (SHAP). Results: 197 patients were included, with a 15-day mortality rate of 48%. The Light Gradient Boosting Machine (LightGBM) classifier showed the best performance, with an AUROC of 0.94, AUPRC of 0.952, accuracy of 0.868, precision of 0.906, recall of 0.822, F1 score of 0.855, Matthews Correlation Coefficient (MCC) of 0.744, and Brier score of 0.131. SHAP analysis revealed coagulopathy, rapid access to antibiotics, septic shock, SOFA score, platelet count, C-reactive protein (CRP) level, and time-related parameters as the most important predictive features. Conclusion: The LightGBM model showed promising results in predicting mortality in ICU patients. This model may support early intervention and assist in complex end-of-life decisions. This study was registered at ClinicalTrials.gov( https://clinicaltrials.gov/ct2/show/NCT06167083 )

Purpose: Mucormycosis is a rapidly progressive angioinvasive fungal infection with limited large-scale outcome data. We aimed to describe the epidemiology, clinical spectrum, treatment strategies, and predictors of outcomes in adult patients with proven mucormycosis in Türkiye. Methods: We conducted a nationwide, retrospective study of 280 adults diagnosed with proven mucormycosis between 2004 and 2024 across 27 tertiary centers. Case definitions were applied according to the European Organization for Research and Treatment of Cancer and the Mycoses Study Group Education and Research Consortium. Clinical characteristics, antifungal management, surgical interventions, and outcomes were systematically analyzed. Results: The median age of the cohort was 60 years, and diabetes mellitus, frequently complicated by ketoacidosis, was the most common underlying condition. Rhino-orbital-cerebral disease represented the predominant clinical form, whereas pulmonary, gastrointestinal, and disseminated presentations were less frequent but carried less favorable prognoses. Liposomal amphotericin B was the main first-line therapy, often combined with surgery, although antifungal treatment was initiated at a median of five days after symptom onset. Ninety-day mortality was 42.1% by Kaplan–Meier estimation (crude 49.3%) and reached 49.3% (crude 55.0%) at 365 days. Crude mortality was lowest in patients who did not undergo surgery; however, this association was not significant in the time-dependent Cox regression analysis, suggesting confounding by baseline severity. Poor outcomes were associated with corticosteroid exposure, prolonged neutropenia, and neurological manifestations, while a history of sinusitis appeared to be associated with improved survival. Conclusion: In this multicenter study, survival was mainly determined by host-related factors rather than the choice of antifungal agent. Corticosteroid exposure, prolonged neutropenia, and neurological involvement independently predicted poor outcomes, whereas a prior history of sinusitis was linked to improved survival, likely reflecting earlier diagnosis and intervention. These findings reinforce the need for heightened clinical awareness, rapid recognition, and prompt multidisciplinary management to improve outcomes in patients with mucormycosis.

This multicentre retrospective study investigated the epidemiology, clinical characteristics, and fluconazole resistance rates of Candida species in osteoarticular infections across Turkey as well as the factors influencing complete recovery. Data were gathered from 73 adult patients diagnosed with proven or probable Candida-associated osteoarticular infections between 2015 and 2025 from 20 healthcare centres. The most common clinical presentation was spondylodiscitis, followed by the involvement of phalangeal bones in the hands and feet. Non-albicans Candida species accounted for 37/73 cases (50.7%), with Candida parapsilosis being the most frequent. Fluconazole resistance was low among Candida albicans isolates (3%) but higher among non-albicans yeasts (27%). Bacterial co-infection, predominantly Gram-positive bacteria, was detected in 52.1% of cases. Diabetes was present in 50/73 patients (68.5%), particularly insulin-dependent diabetes, and was a prominent comorbidity that may have also contributed as a predisposing factor. Radiological detection of osteomyelitis was achieved in 69.9% of patients. Fluconazole was the most commonly used antifungal agent (74%) with a median treatment duration of 90 days. Multivariate analysis revealed that surgical debridement was significantly associated with a higher odds of clinical recovery (adjusted odds ratio [aOR], 5.764; 95% confidence interval [CI], 1.360–24.434; p = 0.017), whereas diabetes mellitus was significantly associated with a lower odds of total recovery (aOR, 0.205; 95% CI, 0.053–0.792; p = 0.022). In conclusion, this multicentre study provides epidemiological data and fluconazole resistance rates of Candida species causing osteoarticular infections in Turkey, highlights the occurrence of C. auris in this cohort, identifies surgical intervention and diabetes mellitus as factors significantly associated with recovery.

Introduction: The fibrous capsule around cardiac implantable electronic device (CIED) generators represents avascular tissue that could be colonized and provides the nidus for latent infection. The purpose of the study is to evaluate the effects of incision of the capsule floor at the lower and/or medial part at the time of generator replacement on the CIED infection and hematoma formation.Methods: This observational study with retrospective analysis of prospectively collected data included patients who underwent CIED generator replacement between January 2013 and January 2024. A total of 1059 consecutive patients were compared according to the incision of the capsule floor at the lower and/or medial part: 448 patients without (group 1) and 611 patients with an incision on the capsule floor (group 2).Results: Fifteen patients with CIED infection after generator replacement were identified. There were no significant differences between the two groups, except for a higher percentage of patients with number of previous procedures on pocket ≥ 2 (35% vs. 19.6%, p < 0.001), and NOAC use (10.6% vs. 6.7%, p = 0.027) in group 2. There was a lower infection rate in group 2 compared to group 1 (0.7% vs. 2.5%, p = 0.014). In multivariate analysis, independent predictors of CIED infection after generator replacement were replacement without an incision of the capsule floor (OR 4.384, 95% CI [1.355–14.189]; p = 0.014), and age< 65 years (OR 3.259, 95% CI [1.133–9.378]; p = 0.028).Conclusion: Generator replacement without incision of the capsule floor during generator replacement was associated with increased CIED infection risk. To minimize CIED infection risk, capsule floor incision could be considered during generator replacement.