University of Ragusa

Prolonged monitoring with implantable cardiac monitors (ICMs) effectively detects subclinical atrial fibrillation (SCAF) in patients with cryptogenic stroke (CS). Understanding SCAF progression to higher burdens can affect decisions regarding oral anticoagulant (OAC) and antiarrhythmic therapies. This analysis aimed to quantify initial SCAF burden, its progression, and predictors of progression in CS patients. This multicenter project collected demographics, stroke characteristics, and SCAF daily burden in CS patients implanted with ICM. SCAF progression was defined as an increase in daily burden from initial detection, categorized as: 5 min to 1 h, 1-6 h, 6-24 h, 24 h for < 7 days, and 24 h for ≥ 7 days. Of 593 patients (70.0 ± 11.3 years, 42% female, median CHA2DS2-VASc score 4.7 ± 1.4) monitored over a median of 24.6 months, 32.7% had SCAF detected. While initial SCAF daily burden was < 1 h in 38.7% of SCAF patients, 53.3% progressed to a higher SCAF daily burden, with 30.6% reaching the 24 h burden by 36 months. Higher CHA2DS2-VASc scores and stroke severity were associated with SCAF progression. OAC therapy was initiated in 91.2% patients with a maximum SCAF daily burden < 1 h, while in 98.0% of those with a maximum daily burden ≥ 1 h (p = 0.042). Over half of CS patients with SCAF progressed to a higher burden, and about one-third reached a 24 h SCAF daily burden. These findings highlight the importance of continuous monitoring in CS patients for early SCAF detection and personalized therapy, considering SCAF burden progression and the patient's risk profile.

Airway management remains a critical aspect of anesthesia, intensive care and emergency medicine, particularly when facing difficult airways. Traditional methods, such as endotracheal intubation via direct laryngoscopy, have evolved with the introduction of advanced tools designed to enhance oxygenation and facilitate airway control. This narrative review presents 10 essential tips for safe up-to-date airway management, emphasizing the importance of a patient-centered, oxygen-focused and strategic approach rather than a purely device-oriented one. By incorporating strategies for assessment, prediction and timely interventions and transition, healthcare professionals can improve patient outcomes and minimize complications during airway management.

Background/Objectives: The aim of this study was to assess NB CE-Chirps for diagnosing Superior Semicircular Canal Dehiscence Syndrome (SSCDS) with cervical and ocular vestibular evoked myogenic potentials (cVEMPs and oVEMPs), and to compare them with Tone Bursts (TBs). Methods: Nine subjects diagnosed with SSCDS were included (four men/five women, median = 61 years, range = 31-79 years). Intensity thresholds at 500 Hz were investigated with both stimuli. A response was also sought when NB CE-Chirps and TBs were delivered at 4000 Hz for c and oVEMPs. Results: Both 500 Hz TBs and 500 Hz NB CE-Chirps significantly differentiated affected ears from healthy ears for cVEMPs (p < 10-3 in both cases) and oVEMPs (p < 10-3 in both cases). Furthermore, we observed significantly lower intensity thresholds in SSCDS ears with 500 Hz NB CE-Chirps than with 500 Hz TBs for both cVEMPs (p < 10-3) and oVEMPs (p = 0.036). Regarding the response rate at 4000 Hz, only TBs consistently showed a response in 100% of cases for the affected ears, with no response in healthy ears for both cVEMPs and oVEMPs. However, there was no significant difference between the response rates obtained at 4000 Hz using TBs and NB CE-Chirps in affected ears (p = 1.000 for cVEMPs and p = 1.000 for oVEMPs). Conclusions: Searching for intensity thresholds with NB CE-Chirps 500 Hz in cVEMPs and oVEMPs is an effective method for diagnosing SSCDS, likely with better frequency specificity than with 500 Hz TBs. Stimulation at 4000 Hz with both TBs and NB CE-Chirps appears to be a promising test for easily screening this syndrome, reducing both sound exposure and the duration of the examination. The possibility to reduce rise time in 4000 Hz TBs may favor this stimulus over NB CE-Chirps at this frequency for this disease. These results should be confirmed in larger cohorts including patients with more severe forms.

The Annali Italiani di Chirurgia (ISSN/eISSN: 0003-469X/2239-253X) is the oldest national surgery journal in Italy. It covers all aspects of surgery, elective, including emergency and experimental surgery, as well as problems involving technology, teaching, organization, and forensic medicine. Annali Italiani di Chirurgia supports the publication of articles in English, and all manuscripts published in Annali Italiani di Chirurgia are freely available for reading. Annali Italiani di Chirurgia is currently indexed in MEDLARS and MEDLINE (PubMed), ISI Master Journal List, Science Citation Index Expanded, and Scopus (Elsevier). More information about the Annali Italiani di Chirurgia.

Critically ill patients receiving continuous renal replacement therapy (CRRT) face distinct nutritional challenges requiring specialized parenteral nutrition (PN) strategies. This review synthesizes current evidence with clinical expertise to provide a comprehensive nutritional framework for this population. Key findings reveal that CRRT significantly impacts nutrient homeostasis through daily losses of amino acids (14–22 g), water-soluble vitamins, and trace elements via the extracorporeal circuit. Results from observational studies demonstrate that higher protein targets (1.8–2.5 g/kg/day) are necessary to achieve positive nitrogen balance, while energy prescriptions must subtract “hidden” calories from citrate anticoagulation (3–4 kcal/mmol) and propofol (1.1 kcal/mL). Clinical outcome data, though primarily observational, indicate that achieving nutritional adequacy correlates with reduced ICU stays (average reduction 2.1–3.4 days), shorter mechanical ventilation duration, and improved functional recovery. Evidence supports that early PN prescription when indicated, coupled with systematic consideration of therapy modality, extracorporeal losses, oral intake capacity, and mobilization status, optimizes nutritional support. We conclude that successful implementation requires: (1) dynamic adjustment based on CRRT parameters, (2) integration with enteral nutrition when feasible, (3) regular metabolic monitoring, (4) multidisciplinary collaboration, and (5) structured protocols. Future research using point-of-care analysis and AI-driven support systems is needed to establish evidence-based guidelines in this specialized population.

This study aims to compare the evaluation of obstructive sleep apnea (OSA) by ten super-experts using responses from a 10-question survey answered by 3 different artificial intelligence chatbots, Chat GPT-3.5, Chat GPT-4.0, Gemini, and a panel of 100 otolaryngologists specialized in sleep medicine. A 10-question survey regarding OSA management was answered by Chat GPT-3.5, Chat GPT-4.0, Gemini, and a panel of 100 otolaryngologists. The responses were assessed by ten super-experts in sleep medicine for their agreement with expert consensus, using a Likert scale. Statistical analyses were performed to evaluate the level of agreement and significance. Expert consensus had the highest mean score (4.5 ± 0.9), significantly outperforming all AI models. ChatGPT-3.5 was the best among AI systems, with a score of 4.1 ± 1.2 (p=0.003), followed by ChatGPT-4 with 3.9 ± 1.4 (p<0.001) and Gemini with 3.6 ± 1.5 (p<0.001). Perfect agreement with expert consensus was achieved in specific scenarios, particularly regarding indications for bariatric surgery and lateral pharyngoplasty. However, there were significant differences in complex clinical scenarios that required integration of multiple factors, particularly in therapeutic management questions where the performance of AI models was significantly below that of expert consensus (p<0.01). Although AI models are promising in the management of OSA, especially for well-defined clinical scenarios, they at present serve best as complementary tools rather than replacements for expert clinical judgment. Most surprisingly, ChatGPT-3.5 outperformed its newer versions in many aspects, indicating that model updates with general capabilities may not always lead to better performance in specialized medical domains. These findings emphasize the potential of AI as a supportive resource while emphasizing the continuing need for human expertise in complex clinical decision-making.

Mesothelioma of the tunica vaginalis testis (MTVT) is an exceedingly rare tumor. We performed a registry-based study on MTVT patient management and survival in Italy. Cases were extracted from the dataset of the Italian National Mesothelioma Registry. A descriptive analysis of patient characteristics, including asbestos exposure, clinical presentation, diagnostic work-up and therapeutic management, was performed. Overall survival was evaluated. We calculated hazard ratios (HR) and 95% confidence intervals (CI) for selected variables by fitting univariate and multivariable Cox models. Overall, 104 patients with MTVT were included. Median age was 72 years (range 17-92). Epithelioid histotype was the most frequent. Previous asbestos exposure was identified in two thirds of cases. Data on diagnostic and therapeutic management were available for 74 patients (71%). The most frequent presentations were scrotal swelling/mass, hydrocele and inguinal pain. All patients underwent surgery, mostly with orchi-funicolectomy. Adjuvant therapy was administered to 15 patients (20%). Overall median survival was 26.2 months (95% CI 22.1-52.1); 3-, 5- and 10-year survival was 49%, 30% and 18%. Older age at diagnosis and presence of distant metastasis (HR 1.91, CI: 0.85-4.26) were negative prognostic factors. Adjuvant therapy was associated with higher mortality (HR 2.54, CI: 1.25-5.15), indicating a more advanced stage at diagnosis. Surgery remains the mainstay of treatment for MTVT; adjuvant therapy in our study did not improve outcome. Data from cancer registries are essential for rare cancers, but they should be integrated routinely with additional diagnostic and therapeutic information.

Abstract. Dense Mediterranean vegetation often conceals archaeological features in LiDAR data, posing a significant challenge for archaeological analysis. This paper presents a novel machine learning pipeline for semi-automated vegetation classification in drone-based archaeological LiDAR point clouds, which were captured to survey the Mediterranean landscape of Sicily, Italy. Our approach integrates an extensive feature engineering stage with a multi-layer stacked ensemble classifier and a RandLA-Net deep learning model. The pipeline was trained on a semantically annotated drone-based LiDAR dataset from the site of Kamarina. It achieved high accuracy in distinguishing vegetation from ground points (0.99 overall accuracy, weighted macro F1 ≈ 0.93). To evaluate generalizability, we tested the model on a secondary site (Heloros) with different vegetation characteristics, obtaining an F1 of ~0.70. Qualitative inspection of results confirms that our model effectively removes vegetation while preserving archaeological structures. Our results demonstrate the potential of ensemble learning and 3D deep neural networks in archaeological remote sensing, enabling more efficient visualization and mapping of hidden archaeological features.

Security compliance constitutes a significant source of concern for many corporate decision-makers due to its complexity and cost. These may be due, first and foremost, to the style of juridical language, which is often challenging to translate into concrete operational procedures. To facilitate such a translation and ultimately optimise the compliance effort, this article presents “NIS2Onto”, an Web Ontology Language (OWL) ontology designed to translate the Network and Information Security Directive version 2 (NIS 2) into an ontological format aimed to favour unambiguous understanding and security operations of cybersecurity professionals, legal experts, and all organisational stakeholders. Through the semantic representation of the NIS 2 entities, relationships, and security measures, NIS2Onto enables automated compliance verification, streamlined risk assessments, and effective policy implementation. Our evaluation employs both metrical and qualitative analysis through a real case study to witness the robustness and practical applicability of NIS2Onto. The ontology not only supports the accurate interpretation of complex legal texts but also aids in systematically enforcing cybersecurity measures. Furthermore, the extensibility of NIS2Onto allows for integration with other regulatory frameworks, thereby fostering a comprehensive and unified approach to cybersecurity governance.