Background/Objectives: Healthcare-associated infections (HAIs), including sepsis, represent a major challenge in clinical practice owing to their impact on patient outcomes and healthcare systems. Large language models (LLMs) offer a potential solution by analyzing clinical documentation and providing guideline-based recommendations for infection management. This study aimed to evaluate the performance of LLMs in extracting and assessing clinical data for appropriateness in infection prevention and management practices of patients admitted to an infectious disease ward. Methods: This retrospective proof-of-concept study analyzed the clinical documentation of seven patients diagnosed with sepsis and admitted to the Infectious Disease Unit of San Bortolo Hospital, ULSS 8, in the Veneto region (Italy). The following five domains were assessed: antibiotic therapy, isolation measures, urinary catheter management, infusion line management, and pressure ulcer care. The records, written in Italian, were anonymized and paired with international guidelines to evaluate the ability of LLMs (ChatGPT-4o) to extract relevant data and determine appropriateness. Results: The model demonstrated strengths in antibiotic therapy, urinary catheter management, the accurate identification of indications, de-escalation timing, and removal protocols. However, errors occurred in isolation measures, with incorrect recommendations for contact precautions, and in pressure ulcer management, where non-existent lesions were identified. Conclusions: The findings underscore the potential of LLMs not merely as computational tools but also as valuable allies in advancing evidence-based practice and supporting healthcare professionals in delivering high-quality care.

Background: The Patient Satisfaction with Nursing Care Quality Questionnaire (PSNCQQ) is one of the most widely used international instruments for assessing patient‐perceived nursing care quality. However, no validated Italian version is currently available. Aim: To evaluate the psychometric properties of the Italian version of the PSNCQQ in a large sample of hospitalized adult patients. Methods: A multicenter cross‐sectional study was conducted in five public hospitals in Italy. The PSNCQQ was translated and culturally adapted according to international guidelines. The total sample ( N = 698) was randomly divided into two independent subsamples for exploratory factor analysis and confirmatory factor analysis. Models were estimated using robust weighted least squares with adjustment for hospital clustering. Competing factorial models were tested. Internal consistency was assessed using Cronbach’s alpha and McDonald’s omega, whereas convergent and construct validity were examined through average variance extracted, composite reliability, and correlations with four global satisfaction indicators. Results: Exploratory factor analysis supported a two‐factor structure distinguishing core nursing care, comprising 14 items, from continuity‐of‐care and discharge‐related processes, comprising five items. Confirmatory factor analysis showed that the correlated two‐factor model provided a better fit than the strictly unidimensional model, whereas the bifactor model was not retained. Internal consistency was excellent for core nursing care ( ω = 0.964), continuity of care ( ω = 0.894), and the total scale ( α = 0.95; ω = 0.95). Average variance extracted and composite reliability values supported convergent validity. PSNCQQ scores were positively associated with global satisfaction indicators ( r = 0.45–0.88; p < 0.001), with the strongest associations observed for the core nursing care dimension. Conclusions: In the Italian context, patient satisfaction with nursing care is best represented by two related but distinct domains. The Italian PSNCQQ demonstrated robust measurement properties and supports the interpretation of both subscale and total scores for evaluating patient experience in hospital settings. Implications for Nursing Management: The PSNCQQ can provide nurse managers with a reliable patient‐reported indicator for monitoring nursing‐sensitive quality across hospital units. Its separate assessment of core nursing care and continuity‐related processes may support benchmarking, quality‐improvement planning, and targeted organizational interventions in bedside care, discharge preparation, and care coordination.

Background/Objectives: Foreign-body aspiration (FBA) is a common and largely preventable pediatric emergency, yet current safety standards and risk assessments rely predominantly on object size and on anecdotal descriptions and bronchoscopy findings. We propose a clinically oriented proof-of-concept workflow that combines high-resolution three-dimensional (3D) scanning and calibrated two-dimensional (2D) imaging of retrieved objects with radiomic shape descriptors and large language model (LLM) reasoning to support aspiration risk assessment and guide prevention. Methods: Objects were obtained from the Susy Safe registry and historical series from the University Clinical Centre Tuzla. Each object was digitized with 3D scanning and photographed with a ruler. Morphometric descriptors—including volume, surface area, sphericity, elongation, flatness, curvature and convexity—were computed from stereolithography (STL) meshes; silhouette area, perimeter and Feret diameters were extracted from 2D photographs. Normative airway dimensions from radiographic and computed tomography (CT) studies provided anatomical context. A sharp, irregular metallic object recovered from a child’s laryngo-tracheal tract served as an illustrative case. Results: The object’s major axis approximated the anteroposterior glottic diameter, suggesting potential traversal when longitudinally oriented, whereas its irregular shape increased the likelihood of mucosal laceration and lodging. LLM-based synthesis provided a structured narrative interpretation consistent with a high-risk profile and highlighted preventive implications. Conclusions: Combining 2D/3D morphometry with LLM reasoning provides objective assessment of FBA hazards and may support safer product design, injury-prevention policies, and caregiver education.

Background: Surgical correction of severe degenerative Mitral Regurgitation (DMR) is indicated in the presence of symptoms and signs of left ventricular (LV) dysfunction. However, conventional clinical and resting echocardiographic parameters may underestimate myocardial impairment. Cardiopulmonary exercise testing (CPET) and exercise stress echocardiography (ESE) may provide a more complete functional and haemodynamic assessment. Objectives: To characterize preoperative CPET and ESE findings in patients with severe DMR and to explore, in a hypothesis-generating analysis, their association with early functional and left ventricular outcomes after surgery. Methods: We included patients with severe DMR who underwent CPET and ESE before surgery. Functional improvement was defined as an improvement of at least one NYHA class from the preoperative baseline to early follow-up. LV function was evaluated as the continuous change in LVEF from discharge to early follow-up (Delta LVEF = follow-up LVEF − discharge LVEF). Baseline parameters were compared between patients who did and did not improve functionally. Random forest analyses were used only as an exploratory secondary analysis to assess whether baseline variables showed any non-linear signal of association with the outcomes and to document the instability of variable-importance rankings. Results and Conclusions: We included 60 patients, of whom 72% were in NYHA class II and all had preserved LV function. At CPET, rest and peak oxygen uptake were 6 +/− 1.5 and 17.2 +/− 5 mL/kg/min, respectively; the VE/VCO₂ slope was 33 +/− 8.9 and the Oxygen Uptake Efficiency Slope was 1.6 (1.3–1.9). At ESE, LVOT-VTI increased from 18.3 +/− 3.9 cm at rest to 24.5 +/− 4.9 cm at peak; stroke volume from 51.0 (43.0–60.0) mL to 72.5 +/− 21.6 mL; and cardiac output from 3.8 (3.2–5.1) L/min to 9.0 +/− 3.2 L/min. No baseline clinical, CPET or ESE parameter significantly distinguished patients who improved functionally from those who did not, and early Delta LVEF was negligible. Random forest analyses did not discriminate above chance and variable-importance rankings were unstable. Patients with severe DMR and preserved LVEF showed objectively abnormal exercise responses despite mild symptoms, supporting the use of CPET and ESE for preoperative functional and haemodynamic characterization; larger prospective studies are required before any predictive or decision-support use can be proposed.

BACKGROUND Pectus excavatum (PE) is the most common congenital chest wall deformity, corrected during adolescence using minimally invasive techniques (MIRPE). Cryoanalgesia has emerged as a valuable adjunct in reducing pain, opioid consumption, and hospital stay. Since recovery trajectories vary widely among patients, we hypothesized that integrating clinical and wearable-derived digital data may allow early identification of recovery patterns and functional improvement following MIRPE. OBJECTIVE This study was a proof of concept to test the hypothesis that continuous pre- and post-operative parameters collected via wearable devices may provide a personalized approach for identifying recovery patterns or early signs of complications. METHODS We designed a feasibility randomized controlled trial in patients undergoing MIRPE, assigned to either cryoanalgesia or thoracic epidural analgesia. All patients were invited to wear a Fitbit Sense 2 device, and digital data were recorded continuously and stored in a dedicated database. Clinical data were entered in REDCap electronic data capture tools by clinicians or through the MyCap mobile app by patients. The study aimed to assess patient compliance with wearing the device and the feasibility of integrating wearable-derived biometric data with clinical variables in adolescents undergoing MIRPE with cryo- or epidural analgesia. Reporting follows the CONSORT 2010 extension to randomized pilot and feasibility trials. RESULTS Patients in the cryoanalgesia group demonstrated higher compliance with wearing their devices during the day and at night throughout the study period, and higher average step counts, compared to the epidural group. Differences between groups were not statistically significant (P values > .05) regarding the Pediatric Quality of Life Inventory (PedsQL™). By the end of the study both groups followed similar recovery trends. Occurrence of complications was early detected by digital data through wearable devices. CONCLUSIONS This proof-of-concept trial confirms that retention and compliance are crucial for the success of the second trial phase. Leveraging Fitbit-derived data may enable a personalized pain management approach with early detection of complications. The benefits of cryoanalgesia in terms of health-related quality of life, as assessed by subjective scales, did not differ significantly from those of the standard of care (epidural–based analgesia); however, the present sample size does not allow a formal claim of equivalence. Continuous biometric data provided a more personalized follow-up. CLINICALTRIAL Ethical approval was obtained from the Institutional Review Board at Istituto Giannina Gaslini (approval number: 278/2021 – DB id 11421; NCT number: NCT0520182041). All procedures were conducted in accordance with the Declaration of Helsinki.