Search Results (21,016)

Background/Objectives: Artificial Intelligence (AI) is increasingly being applied in otolaryngology, including cochlear implants (CIs). This study evaluates the accuracy and completeness of ChatGPT-4 and Microsoft Copilot in determining the appropriate implantation side based on audiological and radiological data, as well as the presence of tinnitus. Methods: Data from 22 CI patients (11 males, 11 females; 12 right-sided, 10 left-sided implants) were used to query both AI models. Each patient’s audiometric thresholds, hearing aid benefit, tinnitus presence, and radiological findings were provided. The AI-generated responses were compared to the clinician-chosen sides. Accuracy and completeness were scored by two independent reviewers. Results: ChatGPT had a 50% concordance rate for right-side implantation and a 70% concordance rate for left-side implantation, while Microsoft Copilot achieved 75% and 90%, respectively. Chi-square tests showed significant associations between AI-suggested and clinician-chosen sides for both AI (p < 0.05). ChatGPT outperformed Microsoft Copilot in identifying radiological alterations (60% vs. 40%) and tinnitus presence (77.8% vs. 66.7%). Cronbach’s alpha was >0.70 only for ChatGPT accuracy, indicating better agreement between reviewers. Conclusions: Both AI models showed significant alignment with clinician decisions. Microsoft Copilot was more accurate in implantation side selection, while ChatGPT better recognized radiological alterations and tinnitus. These results highlight AI’s potential as a clinical decision support tool in CI candidacy, although further research is needed to refine its application in complex cases. Full article

Background/Objectives: Neoadjuvant radiochemotherapy and perioperative chemotherapy are both well-established treatment strategies for locally advanced adenocarcinoma of the esophagus (EAC) and the esophagogastric junction (AEGJ). However, recent knowledge controversially discusses whether neoadjuvant radiotherapy or perioperative chemotherapy represents superior therapeutic options to prolong survival or cause less toxicity. Methods: We retrospectively analyzed 76 patients with locally advanced EAC or AEGJ treated at our tertiary cancer center between January 2015 and March 2023. Patients received either perioperative FLOT chemotherapy (n = 36) or neoadjuvant radiochemotherapy following the CROSS protocol (n = 40), followed by surgical resection and standardized follow-up. We compared survival outcomes, toxicity profiles, treatment compliance, and surgical results between the two groups. Results: There were no statistically significant differences between FLOT and CROSS treatments in five-year loco-regional controls (LRC: 61.5% vs. 68.6%; p = 0.81), progression-free survival (PFS: 33.9% vs. 42.8%; p = 0.82), overall survival (OS: 60.2% vs. 63.4%; p = 0.91), or distant controls (DC: 42.1% vs. 56.5%; p = 0.39). High-grade hematologic toxicities did not significantly differ between groups (p > 0.05). Treatment compliance was lower in the FLOT group, with 50% (18/36) not completing all the planned chemotherapy cycles, compared to 17.5% (7/40) in the CROSS group. All the patients in the CROSS group received the full radiotherapy dose. Surgical outcomes and post-surgical tumor status were comparable between the groups. Conclusions: Although perioperative chemotherapy with FLOT has recently become a standard of care for locally advanced EAC and AEGJ, neoadjuvant radiochemotherapy per the CROSS protocol remains a well-tolerated alternative. In appropriately selected patients, both approaches yield comparable oncological outcomes. Full article

Background/Objectives: Orbital reconstruction remains one of the most demanding procedures in maxillofacial surgery. It requires not only precise anatomical knowledge but also poses multiple intraoperative challenges. Limited surgical visibility—especially in transconjunctival or transcaruncular approaches—demands exceptional precision from the surgeon. At the same time, the complex anatomical structure of the orbit, its rich vascularization and innervation, and the risk of severe postoperative complications—such as diplopia, sensory deficits, impaired ocular mobility, or in the most serious cases, post-traumatic blindness due to nerve injury or orbital compartment syndrome—necessitate the highest level of surgical accuracy. In this context, patient-specific implants (PSIs), commonly fabricated from zirconium oxide or ultra-high-density polyethylene, have become invaluable. Within CAD-based reconstructive planning, especially for orbital implants, critical factors include the implant’s anatomical fit, passive stabilization on intact bony structures, and non-interference with orbital soft tissues. Above all, precise replication of the orbital dimensions is essential for optimal clinical outcomes. This study compares the morphological accuracy of orbital structures based on anthropometric measurements from 3D models generated from fan-beam computed tomography (FBCT) and cone-beam computed tomography (CBCT). Methods: A cohort group of 500 Caucasian patients aged 8 to 88 years was analyzed. 3D models of the orbits were generated from FBCT and CBCT scans. Anthropometric measurements were taken to evaluate the morphological accuracy of the orbital structures. The assessed parameters included orbital depth, orbital width, the distance from the infraorbital rim to the infraorbital foramen, the distance between the piriform aperture and the infraorbital foramen, and the distance from the zygomatico-orbital foramen to the infraorbital rim. Results: Statistically significant differences were observed between virtual models derived from FBCT and those based on CBCT in several key parameters. Discrepancies were particularly evident in measurements of orbital depth, orbital width, the distance from the infraorbital rim to the infraorbital foramen, the distance between the piriform aperture and the infraorbital foramen, and the distance from the zygomatico-orbital foramen to the infraorbital rim. Conclusions: The statistically significant discrepancies in selected orbital dimensions—particularly in regions of so-called thin bone—demonstrate that FBCT remains the gold standard in the planning and design of CAD/CAM patient-specific orbital implants. Despite its advantages, including greater accessibility and lower radiation dose, CBCT shows limited reliability in the context of orbital and infraorbital reconstruction planning. Full article

Multiple sclerosis (MS) is a chronic, immune-mediated disorder of the central nervous system (CNS) characterized by inflammation, demyelination, axonal degeneration, and gliosis. Its pathophysiology involves a complex interplay of genetic susceptibility, environmental triggers, and immune dysregulation, ultimately leading to progressive neurodegeneration and functional decline. Although significant advances have been made in disease-modifying therapies (DMTs), many patients continue to experience disease progression and unmet therapeutic needs. Drug repurposing—the identification of new indications for existing drugs—has emerged as a promising strategy in MS research, offering a cost-effective and time-efficient alternative to traditional drug development. Several compounds originally developed for other diseases, including immunomodulatory, anti-inflammatory, and neuroprotective agents, are currently under investigation for their efficacy in MS. Repurposed agents, such as selective sphingosine-1-phosphate (S1P) receptor modulators, kinase inhibitors, and metabolic regulators, have demonstrated potential in promoting neuroprotection, modulating immune responses, and supporting remyelination in both preclinical and clinical settings. Simultaneously, artificial intelligence (AI) is transforming drug discovery and precision medicine in MS. Machine learning and deep learning models are being employed to analyze high-dimensional biomedical data, predict drug–target interactions, streamline drug repurposing workflows, and enhance therapeutic candidate selection. By integrating multiomics and neuroimaging data, AI tools facilitate the identification of novel targets and support patient stratification for individualized treatment. This review highlights recent advances in drug repurposing and discovery for MS, with a particular emphasis on the emerging role of AI in accelerating therapeutic innovation and optimizing treatment strategies. Full article

Background and Objectives: Transcatheter heart valve (THV) selection is challenging as self-expanding valves (SEVs) are associated with lower post-procedural mean aortic gradients, while balloon-expandable valves (BEVs) have lower rates of paravalvular leak (PVL) and permanent pacemaker implantation (PPI). We aimed to compare the 30-day and 1-year outcomes following Myval BEV (Meril Life Sciences, Vapi, Gujarat, India) and intra-annular Portico SEV (Abbott, St. Paul, MN, USA) implantation. Materials and Methods: We retrospectively analyzed the data from the all-comer TAVI registry of the University Medical Centre Ljubljana, Slovenia, from October 2017 to August 2023. Safety and efficacy outcomes following Myval BEV and Portico SEV implantation were compared overall and after propensity score matching. Results: Of the total 1152 THVs implanted, 97 patients (8%) received a Myval BEV and 47 (4%) a Portico SEV. After propensity score matching, there were no significant differences between the two patient cohorts regarding 30-day (Myval 0.0% vs. Portico 2.9%, p = 1.000) and 1-year mortality (Myval 0.0% vs. Portico 5.9%, p = 0.492). Likewise, the rates of new PPI, device failure (mean aortic gradient and more than mild PVL), and periprocedural in-hospital complications were comparable between the two groups. Conclusions: In this retrospective analysis of two intra-annular THVs, the Myval BEV was associated with comparable short- and mid-term outcomes as the Portico SEV. Full article

Background: Electrocardiograms (EKGs) are essential tools in emergency medicine, often used to evaluate chest pain, dyspnea, and other symptoms suggestive of cardiac dysfunction. Yet, EKGs are not universally administered to all emergency department (ED) patients. Understanding and predicting which patients receive an EKG may offer insights into clinical decision making, resource allocation, and potential disparities in care. This study examines whether integrating structured clinical data with free-text patient narratives can improve prediction of EKG utilization in the ED. Methods: We conducted a retrospective observational study to predict electrocardiogram (EKG) utilization using data from 13,115 adult emergency department (ED) visits in the nationally representative 2021 National Hospital Ambulatory Medical Care Survey–Emergency Department (NHAMCS-ED), leveraging both structured features—demographics, vital signs, comorbidities, arrival mode, and triage acuity, with the most influential selected via Lasso regression—and unstructured patient narratives transformed into numerical embeddings using Clinical-BERT. Four supervised learning models—Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF) and Extreme Gradient Boosting (XGB)—were trained on three inputs (structured data only, text embeddings only, and a late-fusion combined model); hyperparameters were optimized by grid search with 5-fold cross-validation; performance was evaluated via AUROC, accuracy, sensitivity, specificity and precision; and interpretability was assessed using SHAP values and Permutation Feature Importance. Results: EKGs were administered in 30.6% of adult ED visits. Patients who received EKGs were more likely to be older, White, Medicare-insured, and to present with abnormal vital signs or higher triage severity. Across all models, the combined data approach yielded superior predictive performance. The SVM and LR achieved the highest area under the ROC curve (AUC = 0.860 and 0.861) when using both structured and unstructured data, compared to 0.772 with structured data alone and 0.823 and 0.822 with unstructured data alone. Similar improvements were observed in accuracy, sensitivity, and specificity. Conclusions: Integrating structured clinical data with patient narratives significantly enhances the ability to predict EKG utilization in the emergency department. These findings support a personalized medicine framework by demonstrating how multimodal data integration can enable individualized, real-time decision support in the ED. Full article

This comprehensive review examines the role of septoplasty in the pediatric population, emphasizing its therapeutic significance in relieving nasal obstruction and facilitating normal craniofacial growth. Despite the evident advantages of septoplasty, its application in young patients remains a subject of ongoing debate. This issue is primarily characterized by concerns regarding the still-developing immaturity of nasal cartilage, potential intraoperative and postoperative risks, and the current absence of robust data on long-term outcomes following septoplasty. Common complications such as bleeding, septal perforation, saddle nose deformity, and persistent nasal obstruction are reported in the literature; however, many studies lack long-term follow-up data on the incidence of these adverse events and revision rates, which may be higher compared to adult populations, often leading to the need for secondary surgical interventions. Strict inclusion criteria and comprehensive patient selection are paramount to maximize therapeutic success while minimizing complications. Current evidence suggests that appropriately indicated septoplasty can improve airway patency, support optimal facial development, and reduce the risk of secondary sinonasal pathology. There is a significant necessity for additional prospective, large-scale studies to establish standardized therapeutic guidelines and management strategies for this specific population, thereby ensuring effective and evidence-based pediatric otolaryngologic care. Full article

Background: Catheter ablation of the arrhythmogenic substrate has emerged as a promising therapeutic strategy for symptomatic Brugada syndrome (BrS). However, high-quality comparative evidence against conventional implantable cardioverter-defibrillator (ICD)-based management remains limited. Objectives: This meta-analysis aimed to evaluate the efficacy of catheter ablation in reducing ventricular fibrillation (VF) recurrence in symptomatic BrS compared to standard therapy. Methods: Medline, Cochrane Library, and Scopus were systematically searched through 1 June 2025. Study selection, data extraction, and quality assessment were independently conducted by three reviewers. Random-effects meta-analyses were used to pool risk estimates. Results: Three studies (two randomized controlled trials, one observational cohort; 130 symptomatic BrS patients) were included. Over a median follow-up of 3.9 years, catheter ablation was associated with a significantly lower risk of VF recurrence compared to standard therapy [risk ratio (RR) = 0.19, 95% confidence interval (CI) = (0.06, 0.60); I² = 36%, p for heterogeneity = 0.21], with no deaths reported in any group. A sensitivity analysis restricted to randomized trials confirmed similar findings in favor of ablation. Conclusions: Catheter ablation was associated with reduced VF recurrence compared to ICD therapy alone, supporting its potential role as first-line treatment in symptomatic BrS or as an alternative for patients who decline ICD implantation. Full article

If we do not urgently educate current and future medical professionals to critically evaluate and distinguish credible AI-assisted diagnostic tools from those whose performance is artificially inflated by data leakage or improper validation, we risk undermining clinician trust in all AI diagnostics and jeopardizing future advances in patient care. For instance, machine learning models have shown high accuracy in diagnosing Parkinson’s Disease when trained on clinical features that are themselves diagnostic, such as tremor and rigidity. This study systematically investigates the impact of data leakage and feature selection on the true clinical utility of machine learning models for early Parkinson’s Disease detection. We constructed two experimental pipelines: one excluding all overt motor symptoms to simulate a subclinical scenario and a control including these features. Nine machine learning algorithms were evaluated using a robust three-way data split and comprehensive metric analysis. Results reveal that, without overt features, all models exhibited superficially acceptable F1 scores but failed catastrophically in specificity, misclassifying most healthy controls as Parkinson’s Disease. The inclusion of overt features dramatically improved performance, confirming that high accuracy was due to data leakage rather than genuine predictive power. These findings underscore the necessity of rigorous experimental design, transparent reporting, and critical evaluation of machine learning models in clinically realistic settings. Our work highlights the risks of overestimating model utility due to data leakage and provides guidance for developing robust, clinically meaningful machine learning tools for early disease detection. Full article

Cefepime-enmetazobactam is a novel β-lactam/β-lactamase inhibitor combination showing good activity against multidrug-resistant (MDR) Gram-negative bacteria producing a variety of β-lactamases. In this systematic review, we aimed to evaluate the available data on resistance to this drug. We performed a thorough search of four databases (Embase, PubMed, Scopus, and Web of Science), as well as backward citation searching, to identify studies containing data on resistance to cefepime-enmetazobactam. The data were extracted and analyzed according to the breakpoints established by the European Committee on Antimicrobial Susceptibility Testing (EUCAST) and the Food and Drug Administration (FDA), or the specific breakpoints reported by the authors of the respective studies. Analysis based on the type of lactamases produced by the isolates was also performed. Ten studies reported in vitro susceptibility testing and mechanisms of antimicrobial resistance. The total number of isolates was 15,408. The activity of cefepime-enmetazobactam against β-lactamase-producing isolates was variable. The resistance of the studied extended-spectrum β-lactamase (ESBL)-producing and ampicillin C β-lactamase (AmpC)-producing isolates was low (0–2.8% and 0%, respectively). The resistance was higher among oxacillinase-48 β-lactamase (OXA-48)-producing and Klebsiella pneumoniae carbapenemase (KPC)-producing isolates (3.4–13.2% and 36.7–57.8%, respectively). High resistance was noted among metallo-β-^lactamase (MBL)-producing isolates (reaching 87.5% in one study), especially those producing New Delhi metallo-β-lactamase (NDM) and Verona integron-encoded metallo-β-lactamase (VIM), which had the highest rates of resistance. The high activity of cefepime-enmetazobactam against Enterobacterales and selected lactose non-fermenting Gram-negative pathogens, including ESBL-producing and AmpC-producing isolates, makes it a potential carbapenem-sparing agent. The drug should be used after in vitro antimicrobial susceptibility testing in patients with infections caused by OXA-48, KPC, and MBL-producing isolates. Full article

Background: Identifying high-grade strictures (HGS) in patients with primary sclerosing cholangitis (PSC) relies upon subjective assessments of magnetic resonance cholangiopancreatography (MRCP). Quantitative MRCP (MRCP+) provides objective evaluation of MRCP examinations, which may help make these assessments more consistent and improve patient management and selection for intervention. We evaluated the impact of MRCP+ on clinicians’ confidence in diagnosing HGS in patients with PSC. Methods: Three expert abdominal radiologists independently assessed 28 patients with PSC. Radiological reads of MRCPs were performed twice, in a random order, three weeks apart, then a third time with MRCP+. HGS presence was recorded on semi-quantitative confidence scales. The cases where readers definitively agreed on presence/absence of HGS were used to assess inter- and intra-reader agreement and confidence. Results: When using MRCP alone, high intra-reader agreement was observed in identifying HGS within both intra- and extrahepatic ducts (64.3% and 70.8%, respectively), while inter-reader agreement was significantly lower for intrahepatic ducts (42.9%) than extrahepatic ducts (66.1%) (p < 0.01). Using MRCP+ in the third read significantly improved inter-reader agreement for intrahepatic HGS detection to 67.9% versus baseline reads (p = 0.02) and was comparable with extrahepatic ducts. Reader confidence tended to increase when supplemented with MRCP+, and inter-reader variability decreased. MRCP+ metrics had good performance in identifying HGS in both extra-hepatic (AUC:0.85) and intra-hepatic ducts (AUC:0.75). Conclusions: MRCP evaluation supported by quantitative metrics tended to increase individual reader confidence and reduce inter-reader variability for detecting HGS. Our results indicate that MRCP+ might help standardize MRCP assessment and subsequent management for patients with PSC. Full article

The Internet of Medical Things (IoMT) is revolutionizing healthcare by enabling continuous patient monitoring, early diagnosis, and personalized treatments. However, the het-erogeneity of IoMT devices and the lack of standardized protocols introduce serious security vulnerabilities. To address these challenges, we propose a hybrid BiLSTM-DNN intrusion detection system, named HBiLD-IDS, that combines Bidirectional Long Short-Term Memory (BiLSTM) networks with Deep Neural Networks (DNNs), leveraging both temporal dependencies in network traffic and hierarchical feature extraction. The model is trained and evaluated on the CICIoMT2024 dataset, which accurately reflects the diversity of devices and attack vectors encountered in connected healthcare environments. The dataset undergoes rigorous preprocessing, including data cleaning, feature selection through correlation analysis and recursive elimination, and feature normalization. Compared to existing IDS models, our approach significantly enhances detection accuracy and generalization capacity in the face of complex and evolving attack patterns. Experimental results show that the proposed IDS model achieves a classification accuracy of 98.81% across 19 attack types confirming its robustness and scalability. This approach represents a promising solution for strengthening the security posture of IoMT networks against emerging cyber threats. Full article

Background: Asprosin is a relatively recently discovered glucogenic adipokine secreted during fasting that plays an important role in various biochemical processes in the body, including those connected with obesity and insulin resistance. The aim of this exploratory study was to investigate the associations between selected hormonal, anthropometric, and lifestyle-related parameters and serum asprosin concentration. As studies concerning fertility and asprosin have so far been limited to men or women with PCOS, its role in the general female population remains largely unexplored. The direction of this exploration was thus pointed toward possible connections with female fertility. Methods: The case-control study group included 56 women of reproductive age (25–42 years), who were patients of the Reproductive Health Clinic and the Clinic of Endocrinology, Diabetology, and Internal Medicine of the Medical University of Białystok, Poland. The levels of selected hormones, including anti-Müllerian hormone (AMH), estradiol, sex hormone-binding globulin (SHBG), and testosterone, body composition parameters, and a lifestyle parameter—night fasting duration—were assessed to test their associations with serum asprosin concentration. Results: A weak negative correlation was found between AMH level and serum asprosin concentration, suggesting a potential link between asprosin and ovarian reserve. Furthermore, a moderate positive correlation was found between the percentage of total body water (TBW) and serum asprosin concentration. No significant associations were observed between the levels of the other tested hormones and serum asprosin concentration, or between body composition parameters or night fasting duration and serum asprosin concentration. The multivariate model designed in the study shows that AMH, TBW, and night fasting duration explain 23.4% of asprosin variability. Conclusions: Although the nature of the study is exploratory, the findings indicate that the role of asprosin in the female population—particularly its role in fertility—requires further research. Not only is the number of available studies on asprosin insufficient, but the results of this study partly contradict what is known about the hormone from previous studies, which were largely performed with male cohorts. In addition, the results of this study suggest that asprosin may indeed be involved in mechanisms related to female fertility, particularly those connected with ovarian reserve. Nevertheless, studies performed in larger, more homogeneous populations are necessary to confirm the role of asprosin in women, including its association with female fertility. Full article

Background: Peritoneal metastases (PM) represent a common and challenging manifestation of several gastrointestinal and gynecologic malignancies. Bidirectional treatment—combining Pressurized Intraperitoneal Aerosol Chemotherapy (PIPAC) with systemic chemotherapy—has emerged as a strategy to enhance locoregional control while maintaining systemic coverage. Objective: This systematic review aimed to analyze the study design, characteristics, and timing of the treatments administered—including the type of systemic chemotherapy, intraperitoneal agents used in PIPAC, and interval between administrations—as well as the clinical outcomes, safety profile, and overall methodological quality of the available literature on bidirectional treatment for peritoneal metastases. Methods: A systematic literature search was conducted across the PubMed, Embase, and Cochrane Library databases up to April 2025. Studies were included if they reported clinical outcomes of patients undergoing bidirectional treatment. Data extraction focused on survival, response assessment (PRGS, PCI), adverse events, systemic and intraperitoneal regimens, treatment interval, and study methodology. Results: A total of 22 studies involving 1015 patients (742 treated with bidirectional therapy) were included. Median overall survival ranged from 2.8 to 19.6 months, with the most favorable outcomes observed in gastric and colorectal cancer cohorts. PRGS improvement after multiple PIPAC cycles was reported in >80% of evaluable cases. High-grade adverse events (CTCAE ≥ 3) occurred in up to 17% of patients in most studies, with only one study reporting treatment-related mortality. However, methodological quality was generally moderate, with considerable heterogeneity in treatment protocols, response criteria, systemic regimens, and toxicity attribution. Conclusions: Bidirectional therapy with PIPAC and systemic chemotherapy appears to be a feasible and potentially effective strategy for selected patients with peritoneal metastases. Despite encouraging outcomes, definitive conclusions are limited by the retrospective nature and heterogeneity of available studies. Prospective standardized trials are needed to confirm efficacy, clarify patient selection, and optimize treatment protocols. Full article

Biotechnological research increasingly focuses on developing new drugs to counter the rise of antibiotic-resistant strains in hospitals. This study aimed to create bacterial lysates from antibiotic-resistant pathogens isolated from patients and medical instruments across hospital departments. Identification was performed based on morphological, cultural, and biochemical characteristics, as well as 16S rRNA gene sequencing using the BLAST algorithm. Strain viability was assessed using the Miles and Misra method, while sensitivity to eight antibacterial drug groups and biosafety between cultures were evaluated using agar diffusion. From 15 clinical sources, 25 pure isolates were obtained, and their phenotypic and genotypic properties were studied. Carbohydrate fermentation testing confirmed that the isolates belonged to the genera Escherichia, Citrobacter, Klebsiella, Acinetobacter, Pseudomonas, Staphylococcus, Haemophilus, and Streptococcus. The cultures exhibited good viability (10⁹–10¹⁰ CFU/mL) and compatibility with each other. Based on prevalence and clinical significance, three predominant hospital pathogens (Klebsiella pneumoniae 12 BL, Pseudomonas aeruginosa 3 BL, and Acinetobacter baumannii 24 BL) were selected to develop a bacterial lysate consortium. Lysates were prepared with physical disruption using a French press homogenizer. The resulting product holds industrial value and may stimulate the immune system to combat respiratory pathogens prevalent in Kazakhstan’s healthcare settings. Full article