Search Results (4,561)

Background/Objectives: Achieving renal access is a key step in percutaneous nephrolithotomy (PNL), with transpapillary access considered the safest anatomical approach. This prospective pilot study aimed to compare the effectiveness of freehand ultrasound-guided (F-UG) versus fluoroscopy-guided (FG) punctures in achieving anatomically accurate transpapillary access during supine PNL, confirmed by endoscopic visualization. Perioperative and postoperative outcomes were also evaluated. Methods: Forty-three patients undergoing supine PNL for renal pelvic or lower calyceal stones were prospectively enrolled and assigned to either the FG group (n = 23) or F-UG group (n = 20). Following renal access, intraoperative flexible ureteroscopy confirmed the anatomical nature of the puncture (transpapillary vs. nonpapillary). The puncture time, fluoroscopy time, operative time, complications (Clavien–Dindo classification), transfusion requirement, hospital stay, and one-month stone-free rates were recorded. Results: Transpapillary access was achieved in 95.7% of FG cases and 55.0% of F-UG cases (p = 0.003). Radiation exposure was significantly lower in the F-UG group (p < 0.001). Complication (15.0% vs. 0.0%) and transfusion rates (10.0% vs. 0.0%) were higher in the F-UG group but not statistically significant (p = 0.092 and p = 0.210, respectively). Other outcomes, including the operative time, hospital stay, and stone-free rates, were similar between groups. Conclusions: FG puncture is more effective for achieving transpapillary access, while F-UG significantly reduces radiation exposure. The endoscopic confirmation method may provide a reference for future comparative studies on access techniques in PNL. Full article

Background: Pelvic fractures are complex injuries often associated with significant morbidity and mortality, requiring multidisciplinary management. This case series highlights the presentation, management strategies, and outcomes of patients with pelvic fractures treated at our institution. Methods: The medical records of 13 patients diagnosed with pelvic fractures from 1 January 2020 through 31 December 2023 were retrospectively reviewed. Demographic data, mechanism of injury, fracture pattern, associated injuries, treatment modalities, and outcomes were analyzed. Results: A total of 13 patients were included in the study, with ages ranging from 18–95 years. Six of the patients were male and seven were female. The most common mechanisms of injury were falls and pedestrians struck by vehicles. Associated injuries included traumatic brain injury (TBI), fractures including extremities, ribs, and vertebrae, visceral injury, and spinal cord injury. Treatment strategies ranged from conservative, non-surgical management to operative intervention, including interventional radiology embolization, external traction, open reduction and internal fixation (ORIF), and percutaneous screw stabilization. Additional interventions included chest tube placement, exploratory laparotomy, and craniectomy. Two patients died while in the hospital, one was discharged to a shelter, and the remaining 10 were discharged to various inpatient rehab facilities. Conclusions: Pelvic fractures pose significant clinical challenges due to their complexity and associated injuries. This case series underscores the importance of multidisciplinary intervention and treatment strategies in optimizing outcomes. Further studies should focus on the effectiveness of interventions, utilization of new technology, and multidisciplinary team planning. Full article

Objective—To identify effective data analytics and machine learning solutions that can help in the decision-making process in the medical domain and contribute to the understanding of COVID-19 disease. In this study, we analyze data from anonymized electronic medical records of 4711 patients with COVID-19 disease admitted to hospital in Atlanta. Methods—We used random forest, LightGBM, XGBoost, CatBoost, KNN, SVM, logistic regression, and MLP neural network models in this work. The models are evaluated depending on the type of prediction by relevant metrics, especially accuracy, F1-score, and ROC AUC score. Another aim of the work was to find out which factors most affected severity and mortality risk among the patients. To identify the important features, different statistical methods were used, as well as LASSO regression, and explainable artificial intelligence (XAI) method SHAP values for model explainability. The best models were implemented in a web application and tested by medical experts. The model for prediction of mortality risk was tested on a validation cohort of 45 patients from the Department of Infectiology and Travel Medicine, L. Pasteur University Hospital in Košice (UNLP). Results—Our study shows that the best model for predicting COVID-19 disease severity was the LightGBM model with accuracy of 88.4% using all features and 89.5% using the eight most important features. The best model for predicting mortality risk was also the LightGBM model, which achieved a ROC AUC score of 83.7% and a classification accuracy of 81.2% using all features. Using a simplified model trained on the 15 most important features, the ROC AUC score was 83.6% and the classification accuracy was 80.5%. We deployed the simplified models for predicting COVID-19 disease severity and for predicting the risk of COVID-19-related death in a web-based application and tested them with medical experts. This test resulted in a ROC AUC score of 83.6% and an overall prediction accuracy of 73.3%. Full article

Objective: To evaluate the clinical, radiological, and bronchoscopic features of pediatric patients admitted to the pediatric intensive care unit (PICU) with suspected foreign body aspiration (FBA), and to compare the diagnostic performance of chest radiography (CXR) and computed tomography (CT). Methods: We retrospectively analyzed 71 children admitted to the PICU of Kayseri City Training and Research Hospital for suspected tracheobronchial FBA between January 2020 and December 2024. Demographic data, clinical presentations, imaging findings, bronchoscopic results, and outcomes were recorded. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of CXR and CT were calculated using bronchoscopy as the reference standard. Results: The mean age was 2.61 ± 3.59 years, and 66.1% were male. Organic materials were the most commonly aspirated objects, especially in children aged 0–3 years. The right main bronchus was the most frequently affected site. CXR had a sensitivity of 94.9% (95% CI: 83.1–98.6) and a specificity of 71.0% (95% CI: 53.4–83.9), while CT had a sensitivity of 63.2% (95% CI: 41.0–80.9) and a specificity of 100% (95% CI: 87.5–100.0). Bronchoscopy revealed no foreign body in 45.1% of cases. Most patients (94.4%) fully recovered; complications included two deaths, one lobectomy, and one case of hypoxic sequelae. Conclusion: FBA remains a critical pediatric emergency, particularly in young children. CXR is a highly sensitive and accessible screening tool, while CT offers high specificity but lower sensitivity. Prompt diagnosis and bronchoscopy by experienced teams ensure favorable outcomes. Full article

Background: Trichosporon spp. are opportunistic fungi, capable of causing infection, especially in critically ill individuals who often use broad-spectrum antibiotics, invasive devices, and have comorbidities. Objectives The aim of this study was to analyze individuals’ clinical characteristics, evaluate tolerance to biocides, as well as biofilm formation and efflux pump activity in isolates of Trichosporon asahii. Methods: Clinical isolates of T. asahii collected between 2020 and 2023 from both hospitalized and non-hospitalized individuals, of both sexes, regardless of age, were tested for tolerance to sodium hypochlorite, hydrogen peroxide, benzalkonium chloride, and ethyl alcohol. Efflux pump activity was also assessed using ethidium bromide, and biofilm formation was measured with the Safranin test. Clinical parameters such as outcomes, source, and length of hospitalization were analyzed through electronic medical records. Results: A total of 37 clinical isolates of T. asahii were identified. Thirty-three (83.8%) isolates were from hospitalized individuals, with 81.82% collected in ICUs, an average hospital stay of 35 days, and a mortality rate of 51.6%. The tested strains displayed the largest mean inhibition zone for 2% sodium hypochlorite, indicating lower tolerance. A high level of efflux pump expression was detected among clinical isolates. Biofilm formation was detected in 25/67.5% of the isolates. Conclusions: These findings highlight the clinical relevance of T. asahii, particularly in critically ill individuals, and underscore the pathogen’s ability to tolerate biocides, express efflux pumps, and form biofilms, all of which may contribute to its persistence and pathogenicity in hospital environments. Enhanced surveillance and effective microbial control measures are essential to mitigate the risks associated with T. asahii infections. Full article

Background/Objectives: The calcaneus is the most commonly injured tarsal bone, potentially resulting in long-term functional deficiencies and disability. The type of treatment mainly depends on fracture type and morphology. Treatment of these fractures can be challenging due to a limited soft tissue envelope and is frequently associated with complications. The aim of this study was to classify fracture types and identify factors associated with in-hospital complications. Methods: Patients with calcaneal fractures treated at our level I trauma center between 1997 and 2017 were included. Demographic data, comorbidities, fracture characteristics, type of treatment, complications and revisions, compliance and accompanying injuries were evaluated. Results: A total of 238 patients (m = 163, f = 75) at a mean age of 40 years sustaining either uni- or bilateral calcaneal fracture resulting in a total of 288 calcaneal fractures. Concomitant injuries were present in 103 patients (35.9%). Traumatic spine lesions were present in 21.9%. Complications were recorded in 59 fractures (20.5%). Open fractures were more likely to develop complications (76.0% vs. 15.2%, p < 0.001). Significant complication (33% vs. 14%, p < 0.001) and wound complication rates (29% vs. 10%, p < 0.001) were found in multiple-injured patients. All open fractures were surgically treated on the day of admission. In calcaneal fractures with a Böhler angle below 0 degrees, more complications were seen (33% vs. 17%, p < 0.05). Conclusions: High complication rates following calcaneal fractures were detected, with an increased likelihood in open fractures and in patients with multiple injuries. A negative Böhler angle was associated with worse outcomes. Full article

Electroencephalogram (EEG) analysis is essential for diagnosing neurological disorders but typically requires expert interpretation and significant time. Purpose: This study aims to automate the classification of normal and abnormal EEG recordings to support clinical diagnosis and reduce manual workload. Automating the initial screening of EEGs can help clinicians quickly identify potential neurological abnormalities, enabling timely intervention and guiding further diagnostic and treatment strategies. Methodology: We utilized the Temple University Hospital EEG dataset to develop a DenseNet-based deep learning model. To enable a fair comparison of different EEG representations, we used three input types: signal images, spectrograms, and scalograms. To reduce dimensionality and simplify computation, we focused on two channels: T5 and O1. For interpretability, we applied Local Interpretable Model-agnostic Explanations (LIME) and Gradient-weighted Class Activation Mapping (Grad-CAM) to visualize the EEG regions influencing the model’s predictions. Key Findings: Among the input types, spectrogram-based representations achieved the highest classification accuracy, indicating that time-frequency features are especially effective for this task. The model demonstrated strong performance overall, and the integration of LIME and Grad-CAM provided transparent explanations of its decisions, enhancing interpretability. This approach offers a practical and interpretable solution for automated EEG screening, contributing to more efficient clinical workflows and better understanding of complex neurological conditions. Full article

Background and Objectives: Clostridioides difficile infection (CDI) poses a major public health problem worldwide. Materials and Methods: In this retrospective study, we included 274 patients with CDI, who were hospitalized in Internal Medicine Departments in Evangelismos General Hospital in Athens, Greece, during the past decade. Demographic, clinical and laboratory parameters of the patients were recorded. Statistical analysis revealed an association between older age and mortality as well as heart failure and mortality among patients with CDI. Results: Notably, WBC (white blood count), neutrophils, NLR (neutrophil-to-lymphocyte ratio), dNLR (derived NLR), SII (systemic immune–inflammation index) and hs-CRP (high-sensitivity C-reactive protein) demonstrated a positive association with mortality, whereas serum albumin levels and PNR (platelet-to-neutrophil ratio) exhibited an inverse relationship with mortality. We propose that the aforementioned biomarkers may be used as prognostic parameters regarding mortality from CDI. Conclusions: Large scale studies among patients with CDI with the advent of AI (artificial intelligence) may incorporate demographic, clinical and laboratory features into prognostic scores to further characterize the global CDI threat. Full article

Background and Objectives: Risk stratification in acute heart failure (AHF) remains challenging, particularly in settings where biomarker availability is limited. Echocardiography offers valuable hemodynamic insights, but no single parameter fully captures the complexity of biventricular dysfunction and pressure overload. This study aimed to evaluate a novel echocardiographic index (ViRTUE Index–VTI-RVRA-TAPSE Unified Evaluation) integrating a peak systolic gradient between the right ventricle and right atrium (RV-RA gradient), tricuspid annular plane systolic excursion (TAPSE), the velocity–time integral in the left ventricular outflow tract (VTI LVOT), NT-proBNP (N-terminal pro–B-type Natriuretic Peptide) levels, and in-hospital mortality among patients with AHF. Materials and Methods: We retrospectively analyzed 123 patients admitted with AHF. Echocardiographic evaluation at admission included TAPSE, VTI LVOT, and the RV-RA gradient. An index was calculated as ${\displaystyle \frac{RV-RA gradient }{TAPSE x VTI LVOT}}$. NT-proBNP levels and in-hospital outcomes were recorded. Statistical analysis included correlation, logistic regression, and ROC curve evaluation. Results: The proposed index showed a significant positive correlation with NT-proBNP values (r = 0.543, p < 0.0001) and good discriminative ability for elevated NT-proBNP (AUC = 0.79). It also correlated with in-hospital mortality (r = 0.193, p = 0.032) and showed moderate prognostic performance (AUC = 0.68). Higher index values were associated with greater mortality risk. Conclusions: This novel index, based on standard echocardiographic measurements, reflects both systolic dysfunction and pressure overload in AHF. Its correlation with NT-proBNP and in-hospital mortality highlights its potential as a practical, accessible bedside tool for early risk stratification, particularly when biomarker testing is unavailable or delayed. Full article

Background: Various predisposing factors contribute to the emergence and dissemination of the multidrug-resistant (MDR) phenotype in Escherichia coli and Klebsiella pneumoniae. Understanding these factors is crucial for guiding appropriate antimicrobial therapy and infection control strategies. This study investigated the predisposing factors contributing to the MDR characteristics of E. coli and K. pneumoniae isolated in a community hospital in northeastern Thailand. Methods: This case–control study utilized retrospective data from bacterial culture, as well as demographic, clinical, and antibiotic susceptibility records collected during 5 years (January 2016–December 2020). E. coli and K. pneumoniae isolates were analyzed from various clinical samples, including blood, urine, pus, sputum, and other body fluids. Data were analyzed using descriptive statistics and univariate logistic regression. Results: In total, 660 clinical isolates were analyzed (421 E. coli and 239 K. pneumoniae). Blood was the most common source of the detection of E. coli (63.0%) and sputum was the most common source of K. pneumoniae (51.0%). The median ages of patients were 67 and 63 years for E. coli and K. pneumoniae, respectively. E. coli cases were significantly associated with prior antibiotic use (OR = 1.79, 95% CI: 1.17–2.74 p = 0.008). MDR was observed in 50.1% of E. coli and 29.7% of K. pneumoniae (p < 0.001). E. coli compared to K. pneumoniae had lower resistance to third-gen cephalosporins (64.9% versus 95.8%) and carbapenems (8.0% versus 6.9%). ICU admission was the only factor significantly associated with MDR E. coli (OR = 2.40, 95% CI: 1.11–5.20 p = 0.026). No significant differences were observed in gender, age, or comorbidities between MDR cases. Antibiotic usage patterns also differed, with E. coli more likely to receive third-gen cephalosporins compared to carbapenems (OR = 3.02, 95% CI:1.18–7.74 p = 0.021). Conclusions: The use of third-generation cephalosporin may drive MDR E. coli more than K. pneumoniae. Prior antibiotic exposure was linked to E. coli bloodstream infections, while MDR E. coli showed greater clinical severity. These findings highlighted the need for improved antibiotic stewardship in rural hospitals. Full article

Objectives: Surface-Guided Radiation Therapy (SGRT) has been widely adopted in breast cancer radiotherapy, particularly for improving setup accuracy and motion management. Recently, its application in lung cancer has attracted growing interest due to similar needs for precision. This study investigates the feasibility and clinical utility of SGRT in lung cancer treatment, focusing on its effectiveness in patient setup and real-time motion monitoring under frameless immobilization conditions. Materials and Methods: A total of 204 treatment records from 17 patients with primary lung cancer who underwent radiotherapy at Korea University Guro Hospital between October 2024 and April 2025 were retrospectively analyzed. Patients were initially positioned using the Identify system (Varian) in the CT suite, with surface data transferred to the treatment room system. Alignment was performed to within ±1 cm and ±2° across six degrees of freedom. Cone-beam CT (CBCT) was acquired prior to treatment for verification, and treatment commenced when the Distance to Correspondence Surface (DCS) was ≤0.90. Setup deviations from the Identify system were recorded and compared with CBCT in three translational axes to evaluate positioning accuracy and PTV displacement. Results and Conclusions: The Identify system was shown to provide high setup accuracy and reliable real-time motion monitoring in lung cancer radiotherapy. Its ability to detect patient movement and automatically interrupt beam delivery contributes to enhanced treatment safety and precision. In addition, even though the maximum longitudinal (Lng) shift reached up to −1.83 cm with surface-guided setup, and up to 1.78 cm (Lat) 5.26 cm (Lng), 9.16 cm (Vrt) with CBCT-based verification, the use of Identify’s auto-interruption mode (±1 cm in translational axes, ±2° in rotational axes) allowed treatment delivery with PTV motion constrained within ±0.02 cm. These results suggest that, due to significant motion in the longitudinal direction, appropriate PTV margins should be considered during treatment planning. The Identify system enhances setup accuracy in lung cancer patients using a surface-guided approach and enables real-time tracking of intra-fractional errors. SGRT, when implemented with systems such as Identify, shows promise as a feasible alternative or complement to conventional IGRT in selected lung cancer cases. Further studies with larger patient cohorts and diverse clinical settings are warranted to validate these findings. Full article

Background: The surge in COVID-19 cases during the pandemic created a disease burden. An epidemiological study on COVID-19 is required as not much is known about the impact of containment and mitigation on health. We aimed to compare the epidemiological features during the years of the COVID-19 pandemic in the Vidarbha region in Maharashtra, India, to understand the epidemiology changes throughout the pandemic’s progression. Method: All of the cases reported at our testing centers in Nagpur and its periphery during the three years of the pandemic (i.e., from February 2020 to December 2022) were included. Descriptive analyses of variables of interest and statistical measures were compared. Results: There were 537,320 tests recorded during the study period. Of these, 13,035 (13.29%), 42,909 (13.70%), and 19,936 (15.91%) tested positive in 2020, 2021, and 2022, respectively. Hospitalization decreased from 2020 to 2022. An age group shift from 45 to 16–30 years over the pandemic was noticed. Seasonally, positivity peaked in September (27.04%) in 2020, in April (43.4%) in 2021, and in January in 2022 (35.30%). The estimated case fatality ratio was highest in 2021 (36.68%) over the three years in the hospital setting. Conclusion: Understanding the changing epidemiology of SARS-CoV-2 strengthens our perceptive of this disease, which will aid in improving the healthcare system in terms of both controlling and preventing the spread of COVID-19. Full article

Background/Objectives: Colorectal anastomotic leak (CAL) is one of the most severe postoperative complications in colorectal surgery, impacting patient morbidity and mortality. Current risk assessment methods rely on clinical and intraoperative factors, but no real-time predictive tool exists. This study aimed to develop an artificial intelligence model based on intraoperative laparoscopic recording of the anastomosis for CAL prediction. Methods: A convolutional neural network (CNN) was trained with annotated frames from colorectal surgery videos across three international high-volume centers (Instituto Português de Oncologia de Lisboa, Hospital das Clínicas de Ribeirão Preto, and Royal Liverpool University Hospital). The dataset included a total of 5356 frames from 26 patients, 2007 with CAL and 3349 showing normal anastomosis. Four CNN architectures (EfficientNetB0, EfficientNetB7, ResNet50, and MobileNetV2) were tested. The models’ performance was evaluated using their sensitivity, specificity, accuracy, and area under the receiver operating characteristic (AUROC) curve. Heatmaps were generated to identify key image regions influencing predictions. Results: The best-performing model achieved an accuracy of 99.6%, AUROC of 99.6%, sensitivity of 99.2%, specificity of 100.0%, PPV of 100.0%, and NPV of 98.9%. The model reliably identified CAL-positive frames and provided visual explanations through heatmaps. Conclusions: To our knowledge, this is the first AI model developed to predict CAL using intraoperative video analysis. Its accuracy suggests the potential to redefine surgical decision-making by providing real-time risk assessment. Further refinement with a larger dataset and diverse surgical techniques could enable intraoperative interventions to prevent CAL before it occurs, marking a paradigm shift in colorectal surgery. Full article

Background/Objectives: Maternal overweight and obesity are critical factors increasing the risk of various pregnancy complications. Maternal obesity can lead to fetal macrosomia and a heightened risk of intrauterine death, with long-term implications for the child’s health. This study aimed to analyze the incidence of obesity and its impact on pregnancy outcomes in women who delivered by cesarean section at the University Hospital “St. George”, Plovdiv. Methods: A single-center retrospective cohort study was conducted. The documentary method was used for gathering data. Records were randomly selected. The statistical methods used included mean values, confidence intervals (of mean), frequency, and the Kolmogorov–Smirnov test for normality of distribution. Data comparisons were performed using the Mann–Whitney test. Mean values of numerical variables were compared using the independent samples t-test. Results: In total, 46.36% of women in this study were affected by obesity to varying degrees, and the proportion of women who were overweight at the end of their pregnancy was 37.85%. In the studied cohort, 15.99% of women were affected by hypertensive complications. This significant prevalence of obesity highlights concerns regarding body weight among women of reproductive age. This study emphasized a strong correlation between maternal obesity, particularly severe obesity, and the occurrence of preeclampsia. Conclusions: In this study among women who delivered by cesarean section, a significant proportion of them were affected by overweight and obesity. Data for our country are insufficient, and a more in-depth study of this problem is needed. Future research should explore the long-term impacts of maternal obesity on the health of the mother and the newborn. Full article

Medication discrepancies at hospital admission are common and may lead to adverse outcomes. Medication reconciliation is a critical process for minimizing medication discrepancies and medication errors at the time of hospital admission. This study aimed to evaluate the role of clinical pharmacists in identifying pharmacotherapy-related issues upon patient admission in a low-resource setting. A prospective observational study was conducted at a university hospital between 1 March and 31 May 2023. Within 24 h of admission, a clinical pharmacist documented each patient’s pre-admission medication regimen and compared it with the medication history obtained by the admitting physician. Discrepancies and pharmacotherapy problems were subsequently identified. Among 65 patients, pharmacists documented 334 medications versus 189 recorded by physicians (p < 0.01). The clinical pharmacist identified 155 discrepancies, 112 (72.26%) of which were unintentional. The most frequent type was drug omission (91.07%), followed by incorrect dosage (4.46%), incorrect dosing interval (2.68%), and medications with unknown indications (1.79%). Most discrepancies were classified as errors without harm (53.57%), while 41.07% were potentially harmful. These findings underscore the importance of integrating clinical pharmacists into the healthcare team. Their active participation during hospital admission can significantly enhance medication safety and reduce preventable adverse drug events. Full article