Search Results (6,443)

Background/Objectives: Reduced spontaneous swallowing frequency (SSF) may reflect dysphagia. In this study, SSF was evaluated using a neck-worn electronic stethoscope (NWES), certified as a medical device in Japan, with artificial intelligence support in patients undergoing tracheostomy. Methods: This single-center observational study included tracheotomy patients who underwent swallowing assessment with an NWES between August 2024 and July 2025. Several variables were evaluated, including tracheostomy cannula cuff status and dietary status, assessed using the Functional Oral Intake Scale (FOIS). The Mann–Whitney U-test was applied, with SSF (/min) measured over 10 min using an NWES as the primary objective variable. Furthermore, Spearman’s correlation analysis was performed to examine the relationship between SSF (/min) and the pharyngeal saliva retention grade, which was determined using the Hyodo score during fiberoptic endoscopic evaluation of swallowing (FEES). Results: Eighteen patients who underwent tracheotomies were included in this study. SSF (/min) increased significantly when the tracheostomy cannula cuff was deflated (p = 0.049) and when the feeding status was FOIS ≥ 3 (p = 0.032) or FOIS ≥ 4 (p = 0.014). Spearman’s correlation analysis revealed a negative correlation between SSF (/min) and the pharyngeal saliva retention grade (ρ = −0.68, p = 0.0019). Conclusions: SSF measured with an NWES tended to increase with improved swallowing function, which is consistent with the outcomes of previous reports. The SSF measurement method used in this study may prove to be a useful clinical tool. Full article

Urinary stone disease is common, recurrent, and increasingly managed through imaging-driven pathways, yet standard-dose CT of the kidneys, ureters, and bladder (CT KUB) raises concerns about cumulative radiation exposure and the limited use of quantitative imaging information for risk stratification. This review synthesizes contemporary evidence on dose-optimized CT, advanced spectral technologies, and artificial intelligence (AI)-enabled analytics that are reshaping diagnosis, treatment selection, and triage. This review summarizes data supporting low-dose and ultra-low-dose CT protocols that preserve diagnostic accuracy while substantially reducing dose, and discusses how dual-energy CT, photon-counting CT, and radiomics facilitate noninvasive stone characterization and extraction of imaging biomarkers beyond size and location. It also reviews AI approaches for automated detection, segmentation, and volumetric quantification across CT, KUB, and ultrasounds, highlighting their potential to standardize stone-burden metrics. It further examines predictive models, including logistic regression, nomograms, and machine learning, for perioperative infectious complications, emergency department admission or intervention, procedure success, and long-term recurrence, and outlines reporting and validation frameworks and implementation considerations, including software as a medical device regulation and human oversight. In contrast to prior reviews that consider imaging and AI separately, this review integrates dose reduction, spectral characterization, and AI-driven analytics within real-world clinical pathways to distinguish established clinical applications from those that remain investigational. Integrating advanced CT and AI outputs into well-validated prediction models embedded in real-world workflows may enable safer imaging, more consistent triage, and more personalized follow-up for urinary stone disease. Full article

Background and Objectives: Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality worldwide and is frequently associated with multiple comorbidities. Bioelectrical impedance analysis (BIA) provides additional information on body composition and may contribute to the multidimensional assessment of patients with COPD. This study aimed to explore the relationship between BIA-derived parameters and clinical characteristics in hospitalized patients with COPD. Materials and Methods: A cross-sectional analysis of baseline data from a prospective cohort was conducted. A total of 72 hospitalized patients with COPD were included, according to predefined inclusion and exclusion criteria. All patients underwent multifrequency BIA using the InBody 380 device. Sociodemographic, clinical, and paraclinical data were collected and analyzed in relation to BIA-derived parameters. Results: Among the bioimpedance-derived parameters, phase angle (PhA) showed a significant correlation with clinical indices of disease severity, including the body mass index, airflow obstruction, dyspnea, and exercise capacity (BODE) index and the modified Medical Research Council (mMRC) dyspnea scale. Hydration-related parameters reflecting extracellular fluid distribution were associated with the presence of heart failure as a comorbidity. In addition, the evaluation of body fat using bioimpedance identified a higher number of patients with excess body fat compared with obesity defined according to the classical body mass index–based criteria. Conclusions: BIA may provide clinically relevant information on body composition and fluid distribution in patients with COPD. These findings support the potential role of BIA as a complementary tool in the multidimensional evaluation of multimorbid patients with COPD, although further studies are needed to clarify its prognostic value and clinical applicability. Full article

Background: Restless legs syndrome (RLS) is a prevalent neurological sleep disorder that often impairs sleep maintenance. This single-arm, open-label study evaluated the efficacy, safety, and tolerability of extended-duration tonic motor activation (XD-TOMAC) in adults with RLS who experience frequent awakenings with symptoms. Methods: The study comprised three stages: Stage 1 (2 weeks of no intervention), Stage 2 (8 weeks XD-TOMAC), and Stage 3 (2 weeks of no intervention). XD-TOMAC consisted of bilateral high-frequency peroneal nerve stimulation programmed to 180 min duration and administered nightly at bedtime. Nineteen adults with moderate–severe RLS were enrolled, each reporting at least three nights per week of RLS symptoms causing increased awakenings or interfering with returning to sleep after waking. Results: The intent-to-treat analysis population included all patients who began Stage 2 (n = 15). After 8 weeks of XD-TOMAC, the mean change in International RLS Study Group Rating Scale (IRLS) score was −10.6 points (p < 0.001), and the mean change in Medical Outcomes Study Sleep Problems Index II (MOS-II) was −29.5 points (p < 0.001). The mean change in the number of nocturnal awakenings was −1.1 per night (p = 0.009), and the mean change in sleep efficiency was +8.5% (p = 0.001). The mean change in time awake with RLS symptoms after sleep onset was −28.1 min (p = 0.009). Each of these improvements was sustained at the end of Stage 3 (p < 0.01). There were no serious or severe device-related adverse events. Conclusions: Compared with prior 30 min TOMAC studies, XD-TOMAC demonstrated greater efficacy and similar tolerability, supporting its potential as a nonpharmacological therapy for RLS patients whose symptoms frequently disrupt sleep. Full article

Background: Shared decision-making (SDM) is particularly relevant in rheumatoid arthritis (RA), where multiple treatment options with distinct benefit–risk profiles require alignment with patient values and preferences. This study describes the development of a web-based PtDA to support treatment decision-making in RA and represents the first structured, standards-aligned PtDA in the Greek healthcare context. Methods: Guided by the Ottawa Decision Support Framework and the International Patient Decision Aid Standards, a multistage, user-centered methodology was applied, including evidence synthesis, iterative prototyping, and alpha and beta testing. Qualitative methods, including focus group discussions, semi-structured interviews, and think-aloud protocols, were used, while usability was assessed with the System Usability Scale (SUS). Methodological quality was evaluated using IPDASi v3 and UCD-11 criteria. Results: The final PtDA provides a three-step pathway supporting values clarification, comparison of medication options, and reflection on decisional confidence. It was developed as a publicly accessible, web-based tool compatible with multiple devices, with core elements also available in printable format. The tool showed good usability (mean SUS: 75.93) and strong alignment with IPDASi (83.3/100), and user-centered design criteria (11/11). Conclusions: Developing digital PtDAs is inherently complex, underscoring the importance of established methodological frameworks. The findings demonstrate acceptable usability and alignment with established standards within this early-stage development study. Further research is required to examine the tool’s impact on decision-making processes, value–choice concordance, and longer-term clinical outcomes. Full article

Background/Objectives: High-quality cardiopulmonary resuscitation (CPR) is essential for improving clinical outcomes in patients experiencing cardiac arrest. Feedback devices designed to guide CPR must offer real-time feedback on chest compression quality for use by both medical personnel and laypersons. To describe the impact of using an infrared-based device to provide feedback on chest compression quality during CPR performed by healthcare personnel. Methods: A before-and-after study conducted in a simulated hospital from February 2019 to February 2020 evaluated the difference in the percentage of adequate chest compressions in depth and rate. This was assessed by comparing the number of adequate compressions to the total performed in one minute, both with and without the use of a feedback device. Results: A total of 90 participants were recruited, with an average age of 31.2 years (SD: 8.86), of which 60% (54/90) were women. In infants and schoolchildren/adults, high-quality compressions improved by 66% (85% vs. 19%; p < 0.001) and 54% (79% vs. 25%; p < 0.001), respectively, when guided by the GA compared to the control group. In participants without training and experience in CPR, the use of the Guardian Angel achieved high-quality compressions of 45% (10/22) and 66% (25/42), respectively, when evaluating depth for the schoolchildren/adults group. The use of the device during CPR, even in situations of moderate or severe fatigue, resulted in an improvement in high-quality compressions in terms of frequency, reaching 73% (16/22) in infants and 68% (15/22) in schoolchildren/adults. Conclusions: The Guardian Angel improves both the frequency and depth of compressions in participants without previous CPR experience or training. Additionally, the device demonstrated notable improvements in compression frequency, even in situations of moderate or severe fatigue. Full article

Background: The aim of this study was to evaluate treatment satisfaction and decision regret in patients undergoing minimally invasive surgical therapies (MISTs) for lower urinary tract symptoms (LUTS) due to benign prostatic hyperplasia (BPH). Materials and Methods: We analyzed prospectively collected data from consecutive patients undergoing MISTs across five Italian primary care urology centers. All patients underwent a comprehensive clinical assessment, including detailed medical history and physical examination. Preoperative, perioperative, and postoperative variables were recorded. Decision regret was assessed using validated questionnaires, with significant regret defined as a score >25%. Results: A total of 155 patients were included, with a median age of 64 years (IQR 58–66) and a median IPSS of 23 (IQR 18–26). Among them, 90 patients (51%) underwent Aquablation, 21 (12%) received a temporary implantable nitinol device (iTIND), 26 (15%) underwent water vapor thermal therapy (WVTT), and 37 (21%) were treated with prostatic urethral lift (PUL). The overall median decision regret score was 0 (IQR 0–15), with 23 patients (15%) reporting significant regret (>25%). Higher regret rates were observed in patients treated with PUL and WVTT compared to those undergoing iTIND and Aquablation. None of the evaluated variables—including age, BMI, prostate volume, preoperative Qmax, or preoperative IPSS—were significantly associated with treatment regret. However, although not reaching statistical significance, a prostate volume >60 cc was associated with higher regret in patients undergoing WVTT (OR = 3.33) and PUL (OR = 4.2). Conclusions: Among patients undergoing MISTs, treatment regret is not negligible and appears higher when patient selection is suboptimal. Larger studies are warranted to better identify predictors of decision regret and optimize patient selection for these procedures. Full article

Compared to antennas bearing a single port, MIMO antennas with several ports enable higher data throughput by exploiting spatial diversity. This capability is essential for next-generation implantable medical devices, where high channel capacity is a key requirement. A quad-element implantable MIMO antenna is designed and practically validated at 1420 MHz in this paper. It occupies a compact volume of $7\times 8\times 0.1 {\mathrm{mm}}^3$ ($5.6 {\mathrm{mm}}^3$). The compactness is realized by combining high-permittivity substrate (Rogers 3010 with relative permittivity of 10.2) with meandered radiator paths, which increase the effective current length while maintaining a small physical size. All antennas have very small mutual coupling with isolation of more than $31.78$ dB, which is mainly due to the spacing of 1 mm between the elements and the substrate, which is thin. The peak realized gain for each antenna element is $-27.3$ dBi. The simulation is performed within a capsule-like structure, which is embedded in the stomach tissue model. The experimental verification is carried out by embedding antenna within minced meat. The ECC, channel capacity, and link margin are also evaluated and found to be satisfactory. The proposed antenna ensures reliable communication performance, with the transmission range being as high as $2.5$ m, link margin being 15 dB, and the data rate being 120 Mb/s. The proposed antenna ensures a good level of ECC, which is less than $0.1$. The SAR is $52.3$ W/kg at 1420 MHz. This design is favorable for implants because of the small size, good impedance matching, high isolation, low correlation, good level of gain, and good link performance. Full article

Background/Objectives: Non-invasive hemodynamic monitoring technologies are being developed to support clinical decisions while reducing risks from invasive procedures. Usability evaluation is essential to assess safety and effectiveness before commercial release. This study examined the usability of a novel patch-type ultrasound-based system (CW10) designed for continuous monitoring in perioperative settings. Methods: A summative evaluation was conducted following IEC 62366-1 with 15 anesthesiologists. Potential hazards were identified via the FDA MAUDE database (Code: DQK) to inform test scenarios. Participants were stratified by clinical experience (1–<5, 5–<10, and ≥10 years) to observe potential variations in operation. In a simulated operating room, users performed 9 clinical scenarios (49 tasks). Metrics included task success rates, subjective satisfaction (5-point Likert scale), and the System Usability Scale (SUS). Results: The overall task success rate was 98.2%. No statistically significant differences were observed across groups in performance, subjective ratings, or SUS scores (p > 0.05). The mean SUS score was 78.5, corresponding to a “Good” usability level. While some use errors occurred in tasks like probe orientation, root cause analysis suggested these were likely due to negative transfer from prior device experience rather than interface complexity. Conclusions: The results suggest the system demonstrates acceptable usability and consistent operation across experience levels. Integrated automated features and the patch design may contribute to reducing inter-user variability for continuous monitoring. This study provides usability evidence that may inform the development of similar non-invasive technologies. Full article

Background/Objectives: Preterm and critically ill neonates in neonatal intensive care units (NICUs) require multiple medical devices, including incubators, radiant warmers, phototherapy systems, and patient monitors. The coexistence of standalone devices without interoperability increases cognitive and operational burdens for healthcare providers and leads to spatial inefficiency. This study aimed to develop and evaluate a multi-functional neonatal incubator integrating these core functions into a single platform, using user-centered design (UCD) and usability engineering principles. Methods: By synthesizing and analyzing international standards (ISO 13485, IEC 62366-1, IEC 62366-2, and ISO 9241-210), a four-phase design process was established. Following the development of the monitoring system, the design was iteratively refined and validated through repeated formative usability evaluations. A summative usability evaluation was then conducted with 20 NICU clinicians in a simulated NICU environment, using 13 scenarios comprising 39 tasks. Outcome measures included task success rate, the After-Scenario Questionnaire (ASQ), the NASA Task Load Index (NASA-TLX), and the System Usability Scale (SUS). Results: The overall task success rate was 95.64%. When analyzed by function, success rates were 94.63% for incubator-related tasks, 98.33% for patient monitoring, 96.67% for radiant warmer tasks, and 98.33% for phototherapy tasks. The mean SUS score was 78.63, exceeding the benchmark score of 68 that indicates good usability. In addition, no statistically significant differences were observed in workload (NASA-TLX) or usability (SUS) scores according to clinical role or length of clinical experience. Conclusions: The multi-functional neonatal incubator developed in this study demonstrated high usability despite the integration of multiple medical device functions. The findings suggest that this integrated system has the potential to enhance clinical workflow efficiency, optimize spatial utilization, and improve patient safety in NICU settings. Full article

Carotid artery stenosis remains a major cause of ischemic stroke worldwide, and its management continues to evolve in parallel with advances in surgical, endovascular, and medical therapies. Carotid endarterectomy (CEA) was established as the standard of care for symptomatic high-grade stenosis following landmark randomized trials, while carotid artery stenting (CAS) subsequently emerged as a less invasive alternative for appropriately selected patients. This review aims to summarize the historical evolution of carotid artery stenting, critically appraise evidence from major clinical trials comparing CAS and CEA, and examine contemporary practice patterns in the era of intensive medical therapy. A comprehensive review of randomized trials, registries, guideline statements, and recent literature was performed to synthesize current evidence regarding procedural outcomes, patient selection, and emerging technologies, including transcarotid artery revascularization (TCAR). Large, randomized trials have demonstrated comparable long-term composite outcomes between CAS and CEA in selected patients, although peri-procedural risk profiles differ, with higher stroke risk observed after CAS and higher myocardial infarction rates after CEA. Technological advancements in embolic protection devices, stent platforms, and alternative access strategies have further refined endovascular approaches. Concurrently, improvements in intensive medical therapy—including lipid-lowering, antiplatelet therapy, blood pressure control, smoking cessation, and lifestyle modification—have substantially reduced overall stroke risk, particularly in asymptomatic patients. In the contemporary era, optimal stroke prevention requires individualized, multidisciplinary decision-making that integrates symptom status, anatomical complexity, comorbid conditions, procedural expertise, and sustained long-term vascular risk factor management following revascularization. Full article

The Internet of Things (IoT) plays an increasingly central role in healthcare by enabling continuous patient monitoring, remote diagnosis, and data-driven clinical decision-making through interconnected medical devices and sensing infrastructures. Despite these advances, IoT healthcare systems remain constrained by persistent challenges related to data privacy, computational efficiency, scalability, and regulatory compliance. Federated learning (FL) reduces reliance on centralised data aggregation but remains vulnerable to inference-based privacy risks, while edge-oriented approaches are limited by device heterogeneity and restricted computational and energy resources; the deployment of large language models (LLMs) further exacerbates concerns surrounding privacy exposure, communication overhead, and practical feasibility. This study introduces Trustworthy Intelligence (TI) as a guiding framework for privacy-preserving distributed intelligence in IoT healthcare, explicitly integrating predictive performance, privacy protection, and deployment-oriented system design. Within this framework, split learning (SL) is examined as a core architectural mechanism and extended to support split-aware LLM integration across heterogeneous devices, supported by a structured taxonomy spanning architectural configurations, system adaptation strategies, and evaluation considerations. The study establishes a systematic mapping between SL design choices and representative healthcare scenarios, including wearable monitoring, multi-modal data fusion, clinical text analytics, and cross-institutional collaboration, and analyses key technical challenges such as activation-level privacy leakage, early-round vulnerability, reconstruction risks, and communication–computation trade-offs. An energy- and resource-aware adaptive cut layer selection strategy is outlined to support efficient deployment across devices with varying capabilities. A proof-of-concept experimental evaluation compares the proposed SL–LLM framework with centralised learning (CL), federated learning (FL), and conventional SL in terms of training latency, communication overhead, model accuracy, and privacy exposure under realistic IoT constraints, providing system-level evidence for the applicability of the TI framework in distributed healthcare environments and outlining directions for clinically viable and regulation-aligned IoT healthcare intelligence. Full article

The management of complex acute and chronic wounds remains a formidable challenge in modern medicine, underscoring the urgent need for advanced therapeutic strategies that accelerate healing, prevent infection, and promote functional tissue regeneration. Electrospun nanofibers have attracted considerable attention in the biomedical field due to their extracellular matrix-like architecture, high surface area, interconnected porosity, and tunable physicochemical composition, which drive advances in wound regeneration, tissue engineering, and biopolymer-based therapeutics. In wound healing, nanofibrous dressings composed of natural polymers such as chitosan, gelatin, collagen, and cellulose promote cell attachment and proliferation, support angiogenesis, and enable infection control while delivering bioactive agents, thereby addressing significant challenges related to inflammation, biocompatibility, and antimicrobial resistance. In tissue engineering, aligned and hierarchically organized scaffolds fabricated from biopolymers such as collagen, gelatin, chitosan, and cellulose enhance the guided orientation of cells, differentiation, and functional regeneration of neural, musculoskeletal, vascular, and skin tissues. In addition to their conventional regenerative applications, recent studies have demonstrated that electrospun biopolymer nanofibers can be used in multifunctional biomedical platforms, including smart and stimuli-responsive systems for drug delivery, biosensing, regenerative interfaces, and wearable medical technologies. The integrated constructs that incorporate diagnostic or therapeutic functionalities, hybrid fabrication approaches that combine 3D printing with electrospinning, and intelligent biopolymer frameworks that enable telemedicine, real-time physiological monitoring, and personalized regenerative therapies offer new opportunities for developing improved biomedical systems. Overall, these advances position electrospun nanofiber systems as promising biomaterials for next-generation biomedical innovation. This review summarizes recent progress in tissue-engineered scaffolds, wound dressings, fabrication strategies for integrative therapeutics, and wearable devices with transformative potential for biomedical applications. Finally, the review addresses significant challenges related to scalability and clinical translation. It offers perspectives on future directions, including the integration of artificial intelligence and the regeneration of complex skin appendages, which will shape the next generation of nanofiber-based wound-healing therapies. Full article

Droplet microfluidics has been widely used in biological, chemical, and medical research owing to its advantages of miniaturization, high throughput, and low reagent consumption. However, limited sensitivity and optical path length in on-chip absorbance detection remain major challenges for droplet-based microfluidic analysis. Traditional absorbance detection suffers from low sensitivity due to the extremely short optical path in microfluidic channels, while existing optical path extension methods have drawbacks such as complex fabrication, easy droplet rupture, or strict incident angle requirements. To address these issues, this study developed a droplet microfluidic absorbance detection platform integrating optical fibers, on-chip micromirrors, external fluidic actuation, and an absorbance detection module. Microchannel sidewalls filled with low-melting-point metal act as mirrors; the multi-reflection optical path, combined with optical fibers and micromirrors, compensates for insufficient light manipulation and effectively extends the absorption path length, improving sensitivity and accuracy. Using this method, the detection limit for methylene blue solution was 20 μM, and the sensitivity for Escherichia coli (E. coli) suspension was doubled compared with traditional Nanodrop OD600 measurement. This device features low fabrication difficulty and cost and stable detection, providing a proof-of-concept strategy for enhanced absorbance detection in droplet microfluidic systems. Full article

Coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI) are the two dominant revascularisation strategies for obstructive coronary artery disease, yet their relative roles continue to shift because they address coronary pathophysiology differently with ever-evolving techniques. PCI has advanced through iterative improvements, including balloon angioplasty, bare-metal stents, and drug-eluting stents, with contemporary outcomes increasingly driven by procedural optimisation using intracoronary imaging and physiology-guided lesion selection rather than device category alone. CABG has progressed through perioperative management, improvements in operative safety, and, critically, conduit durability. Recognition of progressive saphenous vein graft failure has underpinned a conduit-optimisation era in which the left internal mammary artery to left anterior descending artery remains the gold standard. Further, broader arterial grafting (including radial artery use, multiple arterial grafting, and selected total-arterial strategies) has been increasingly applied, albeit with deliverability and competing-risk constraints highlighted in randomised evidence. This perspective review reframes the CABG versus PCI comparison not as a binary contest, but as a context-dependent assessment in which the relative value of each strategy depends on the specific technologies, techniques, and conduits available at the time of comparison. We summarise comparative effectiveness where evidence is most consistent and where it remains sensitive to anatomy, comorbidity, and endpoint definitions. In diabetes with multivessel disease, trial data favour CABG for long-term survival and clinical outcomes despite higher stroke risk. In left main disease, outcomes depend on lesion pattern and overall complexity, with trial-era stent technology and composite endpoint definitions influencing conclusions. In ischaemic left ventricular dysfunction, a long-term survival benefit is established for CABG added to medical therapy, while multi-vessel PCI has not demonstrated comparable prognostic modification in contemporary data. We then examine hybrid coronary revascularisation as territory-specific allocation, highlighting its physiological rationale, program dependence, and limited, adequately powered randomised evidence. Finally, we outline how artificial intelligence (AI) and robotics may accelerate a precision revascularisation paradigm by standardising lesion assessment, supporting procedural planning, improving procedural reproducibility, and enabling more patient-specific selection among PCI, contemporary CABG with optimised conduits, and hybrid pathways. Full article