Search Results (1,247)

Background and Clinical Significance: The Coronary Sinus Reducer (CSR) is a percutaneous therapeutic option for patients with refractory angina who are unsuitable for further myocardial revascularization. The procedure has a generally favorable safety profile, with a low rate of reported procedural complications. To our knowledge, major atrioventricular (AV) conduction disturbances during CSR implantation have not been previously described. This case highlights a rare but clinically relevant intraprocedural complication; Case Presentation: A 71-year-old man with multivessel coronary artery disease and previous coronary artery bypass grafting was referred for CSR implantation because of refractory angina despite optimal medical therapy and lack of further revascularization options. The procedure was performed via a right jugular venous approach. Baseline electrocardiography showed right bundle branch block and findings consistent with previous inferior myocardial infarction, without definite criteria for left anterior fascicular block. During coronary sinus cannulation, the patient developed transient complete AV block, resulting in an approximately 8–10-second ventricular pause without a stable ventricular escape rhythm. The conduction disturbance resolved after catheter withdrawal and repositioning. Given the severity of the event, a temporary transvenous pacemaker was inserted via the right femoral vein, allowing safe completion of CSR implantation. At three-month follow-up, angina had improved from Canadian Cardiovascular Society class III to class I, and no recurrent advanced AV block was documented; Conclusions: Transient complete AV block may occur during CSR implantation, particularly during coronary sinus manipulation and possibly in patients with pre-existing conduction disease. Careful catheter handling, prompt recognition of conduction disturbances, and immediate availability of temporary pacing support should be considered in selected high-risk patients undergoing CSR implantation. Full article

Background: Congenital heart defects (CHD) are the most common congenital malformations and often require complex, lifelong pharmacotherapy. In pediatric CHD populations, multidrug regimens targeting cardiac function and comorbidities predispose patients to polypharmacy. At the molecular level, concomitant drug use increases the risk of pharmacokinetic and pharmacodynamic interactions. Methods: This study aimed to characterize medication patterns and assess polypharmacy and potential drug–drug interactions in patients with CHD. A cross-sectional online survey was conducted in collaboration with the German National Register for Congenital Heart Defects (NRCHD) between November and December 2021. Patients aged 6–17 years with CHD were eligible for inclusion. Participants reported their current medications in open-ended questions. Drugs were categorized into pharmacological classes, and common drug combinations were evaluated for potential interactions. Results: Of 894 participants included in the analysis, 372 reported current medication use. Among these, 179 (48.1%) met criteria for polypharmacy (≥2 drugs). Polypharmacy was more frequent in patients with higher disease severity and comorbidity burden. Several drug combinations showed potential for clinically relevant pharmacokinetic and pharmacodynamic interactions, including mechanisms involving renal electrolyte handling, altered protein binding, cytochrome P450-mediated metabolism, and additive pharmacodynamic effects. Conclusions: Children with CHD are exposed to complex multidrug regimens with a considerable interaction risk, underscoring the need for systematic medication review and mechanistically informed pharmacological management in pediatric CHD care. Full article

Chronic kidney disease (CKD) remains a leading cause of premature mortality and global disease burden, yet the molecular mechanisms underlying its progression are still incompletely understood. Accumulating evidence highlights circadian disruption as an underappreciated driver of CKD that warrants systematic re-examination. The kidney harbors an autonomous circadian oscillator, principally regulated by the CLOCK:BMAL1 transcription factor complex, which coordinates glomerular filtration, tubular electrolyte handling, blood pressure rhythmicity, inflammatory tone, and cellular repair. In CKD, retained uremic toxins, sustained oxidative stress, and persistent NF-κB activation collectively suppress this clock machinery, generating a self-reinforcing cycle of renal injury and circadian dysregulation. CKD is also accompanied by progressive attenuation of nocturnal melatonin secretion, weakening a central hormonal cue for peripheral clock entrainment and cytoprotection. Melatonin acts both as a chronobiotic and as a pleiotropic cytoprotective molecule. Through MT1/MT2 receptors, the nuclear receptor RORα, and receptor-independent antioxidant pathways, it may enhance Nrf2/HO-1 signaling, restrain NF-κB and NLRP3 inflammasome activity, suppress TGF-β1/Smad2/3-mediated fibrogenesis, preserve mitochondrial integrity, and engage SIRT1-linked clock regulation. Current clinical studies suggest that nightly melatonin supplementation can improve sleep quality and selected oxidative or circadian surrogate endpoints in hemodialysis patients; however, whether melatonin slows CKD progression or preserves renal function remains unproven. This review synthesizes the molecular interface between circadian dysregulation and CKD progression and articulates a rationale for adequately powered clinical trials evaluating melatonin as a candidate chronotherapeutic adjunct rather than an established renoprotective therapy. Full article

Medication dispensing errors remain a significant concern in healthcare systems, particularly in elderly care and long-term medication management, where incorrect medication delivery may compromise patient safety and treatment outcomes. This study presents the design and experimental validation of a cyber–physical medication dispensing platform integrating robotic manipulation, edge AI-based visual verification, distributed motion control, and cloud synchronization. The platform combines a rotary medication storage mechanism, vacuum-based pill handling, a Klipper-based control framework, and a YOLOv8 perception subsystem deployed on a Hailo AI accelerator for real-time edge inference. Experimental evaluation was conducted under controlled laboratory conditions. Using an environment-specific validation dataset, the perception subsystem achieved a precision of 0.627, recall of 0.739, and mAP@0.5 of 0.786. An adaptive verification strategy was subsequently evaluated to improve dispensing verification under varying pill occupancy conditions. End-to-end system testing comprising 80 dispensing trials achieved an overall dispensing success rate of 86.25%, with no incorrect dispensing events observed. The results demonstrate the feasibility of integrating edge AI verification, distributed control, and cloud connectivity within a cyber–physical medication dispensing platform. The presented system provides a foundation for future research on perception-assisted medication dispensing, long-term deployment, and clinical validation in smart healthcare environments. Full article

Background: Missing data, particularly progression-driven dropout, introduces substantial bias in longitudinal oncology studies, directly impacting response classification based on RECIST criteria. While machine learning-based imputation methods are increasingly used, their performance is rarely evaluated in a clinically interpretable framework centered on patient-level endpoints such as Best Overall Response (BOR). Methods: We propose a clinically grounded evaluation framework based on RECIST 1.1 focused on patient-level Best Overall Response classification. Longitudinal tumor trajectories were simulated for 270 patients (1:1, HER2+ and HER2−) across nine follow-up visits using both Gompertz and Stein–Fojo growth models, resulting in 2700 patient-visit observations. Realistic missingness was introduced through a combination of random mechanisms and progression-driven dropout. Three machine learning imputation models, long short-term memory (LSTM), MissForest, and Multiple Imputation (MI) were evaluated under both direct (MAR-based) and non-responder imputation strategies. Performance was assessed using BOR classification metrics, including accuracy and Cohen’s kappa. Result: Across both simulation frameworks, imputation substantially improved BOR classification performance. Under the Gompertz model, accuracy increased from 0.84–0.89 with direct imputation to 0.94–0.99 with non-responder imputation, with corresponding kappa improvements from 0.73–0.82 to 0.90–0.99. Similar trends were observed under the Stein–Fojo model (accuracy: 0.82–0.84 vs. 0.91–0.96; kappa: 0.69–0.72 vs. 0.86–0.94). Across all evaluated methods, NRI improved classification performance by approximately 10 percentage points in accuracy and up to 17 percentage points in kappa. The improvement was observed consistently across both tumor growth models and different missingness scenarios, demonstrating the robustness of the findings. Conclusions: This study demonstrates that successful handling of missing data depends not only on the imputation method itself, but also on the choice of a clinically meaningful endpoint and appropriate estimand strategies aligned with the underlying missing data assumptions. In the METABRIC-derived simulations, clinically informed handling of progression-related missingness substantially improved RECIST-based BOR classification across all evaluated methods, suggesting that appropriate endpoint selection and the corresponding estimand strategy for missing data handling may have a greater influence on classification performance than the choice among the imputation models applied. Full article

Background: Acute kidney injury (AKI) is a frequent and prognostically important complication of cardiac surgery, yet early risk stratification remains challenging. The purpose of this prospective exploratory study was to determine whether preoperative vitamin levels differ in patients who develop cardiac surgery-associated AKI. Methods: Consecutive patients scheduled for cardiac surgery due to coronary artery disease and/or severe aortic stenosis between October 2024 and July 2025 were included. Fourteen patients (16.1%) had preoperative eGFR below 60 mL/min. Preoperative serum levels of vitamin A (retinol), vitamin E (α-tocopherol), and vitamin D (25-hydroxyvitamin D3) were measured. Results: A total of 87 patients (72 males (82.8%) with a median (Q1–Q3) age of 66 (61.5–71) years) were included in the study. Cardiac surgery-associated AKI occurred in 36 (41.4%), as a mild and transient impairment, with only two patients with a more severe stage requiring temporary renal replacement therapy. Patients who developed AKI had significantly higher preoperative retinol levels (p = 0.046). Retinol concentrations correlated positively with preoperative creatinine (Spearman’s rho 0.321, p = 0.002), postoperative day 0 creatinine (Spearman’s rho 0.333, p = 0.002), and postoperative day 1 creatinine (Spearman’s rho 0.268, p = 0.012), and negatively with preoperative eGFR (Spearman’s rho −0.288, p = 0.007). Tocopherol and 25(OH)D3 did not differ significantly between subgroups. No difference in vitamin levels was observed between patients with and without diabetes. Conclusions: Increased preoperative retinol levels were associated with cardiac surgery-associated AKI and correlated with perioperative renal dysfunction. Retinol may reflect impaired kidney handling of retinol and identify increased renal vulnerability in cardiac surgery patients. Retinol may represent a hypothesis-generating biomarker of cardiac surgery-associated AKI risk that warrants confirmation in larger cohorts. Full article

Objectives: This study proposes an implementation-oriented design framework for multimodal conversational agents handling patient-generated health data and reports an exploratory experiment evaluating its instantiation in hypertension self-monitoring, focusing on user experience of conversational data-entry workflows. Methods: The framework operationalizes four complementary dimensions (social intelligence, communication style, anthropomorphic characteristics, and technological mapping) and was instantiated in two agents integrated into an eHealth platform. Each agent supports users by providing prompts, interpreting responses, checking data plausibility, and confirming submission. A three-arm, single-session feasibility experiment ($n=18$, $n=6$ per group) compared a conventional app interface with text-based and voice-based conversational agents. Evaluation triangulated three sources of evidence: open-ended qualitative responses analyzed through descriptive content analysis, session-level researcher observation notes, and the User Experience Questionnaire (UEQ) reported descriptively with one-way ANOVA and ${\eta }^2$ effect sizes. Results: All three modalities were acceptable to participants and produced UEQ scores in the positive range. Hesitation was observed in 2 of 6 Control participants, 1 of 6 Text participants, and 3 of 6 Voice participants, with self-reports indicating that voice-related difficulties were modality-specific (diction, command phrasing) and resolved within the session. Qualitative themes of acceptability and innovation, perceived effort, and modality-specific facilitators emerged across the corpus. Between-group ANOVAs did not reach statistical significance ($p>0.05$), as expected for an underpowered design, yet ${\eta }^2$ values were medium for Attractiveness, Efficiency, Dependability, and Pragmatic Quality and large for Stimulation and Hedonic Quality, converging with the qualitative innovation and engagement signal in the conversational conditions. Conclusions: The framework and feasibility experiment provide preliminary, hypothesis-generating evidence on the potential of multimodal conversational interfaces in healthcare. However, no clinical, behavioral, or longitudinal outcomes were assessed. The four design dimensions can be tentatively associated with themes recognizable in user discourse, and the observed effect-size pattern motivates adequately powered longitudinal studies that incorporate behavioral and clinical endpoints alongside user experience measures. Full article

Buttock claudication after endovascular aneurysm repair (EVAR) impairs recovery and quality of life, yet individualized preoperative risk tools are scarce. We conducted a retrospective dual-center cohort study of consecutive EVAR patients from Fuxing and Xuanwu Hospitals. The endpoint was new-onset postoperative buttock claudication. Missingness was quantified for each predictor and handled using complete-case analysis or model-based single imputation according to the extent of missingness. Data were split into training and held-out test sets at a 70:30 ratio with outcome stratification. Predictor screening, preprocessing, and hyperparameter tuning were performed within the training/resampling framework to minimize data leakage. Ten algorithms were tuned using stratified 10-fold cross-validation, and test set performance was assessed using discrimination, threshold-based metrics, calibration plots, calibration intercept/slope, Brier score, and decision-curve analysis. SHapley Additive exPlanations (SHAP) provided model-agnostic explanations. A web calculator was deployed. Among 272 patients, 71 (26.1%) developed claudication. Independent risk factors included aneurysm with iliac involvement (adjusted OR 4.04), male sex (3.26), unilateral (3.86) and bilateral internal iliac artery embolization (8.61), and hyperlipidemia (5.66); >2 distal internal iliac branches was protective (0.15). On the test set, the neural network achieved the highest AUROC (test ROC), with the highest sensitivity (0.810) and top F1 (0.557) at balanced specificity (0.617); CatBoost maximized accuracy (0.790) and specificity (0.900). Calibration was acceptable, and DCA showed positive net benefit across clinically plausible thresholds. SHAP confirmed physiologic directions and enabled case-level interpretation. An explainable machine learning framework accurately stratifies risk of buttock claudication after EVAR, highlighting the roles of internal iliac embolization, iliac involvement, and distal branch anatomy. The publicly available Shiny tool supports perfusion-aware planning and shared decision-making. Full article

Background/Objectives: Tourette syndrome and other chronic tic disorders are neurodevelopmental conditions characterized by intermittent motor/phonic tics and frequent behavioral comorbidity. Poor sleep quality is often reported by patients with tic disorders; however, little is known about the prevalence and clinical correlates of disruption in sleep physiology. Methods: We conducted a systematic literature review of clinical studies evaluating sleep using at least one validated sleep outcome (questionnaire, polysomnography, or coded clinical diagnosis). Results: Despite high heterogeneity in age ranges, diagnostic formulations, outcome measures, and confounder handling, converging evidence across designs indicated a significantly higher prevalence of sleep disturbance in patients with Tourette syndrome and other chronic tic disorders compared to controls. Specifically, registries showed significantly greater insomnia rates (aOR 6–7); case–control studies revealed a 9-fold increase in night-waking, bedtime resistance, parasomnias, and daytime drowsiness; polysomnography studies demonstrated sleep fragmentation, with decreased efficiency, longer latency, and more awakenings. Conclusions: Sleep disorders are relatively common in patients with Tourette syndrome and other chronic tic disorders, with clinical implications for both arousal instability and sleep initiation/maintenance issues. Further research is needed to better understand the complex interplay between altered sleep patterns and tic expression, as well as the impact of behavioral comorbidities. Our findings highlight a need for personalized treatment interventions focusing on sleep problems in the context of tic disorders. Full article

Effective diabetes management heavily relies on appropriate insulin administration, which strongly depends on the correct administration strategy. In this sense, insulin administration plays a fundamental role, as its use depends on the patient’s clinical condition and diabetes type. Traditional syringe-based methods require proper training to ensure that insulin is successfully delivered into the subcutaneous tissue, where it can be absorbed and metabolized; however, it is desirable to develop an insulin applicator that does not require training for its appropriate use. Aiming to provide support solutions that help patients to develop a correct administration technique, a biodesign-based methodology, coupled with biomimetic concepts, is employed to design a device that assists the user in creating a stable skin fold and guiding needle orientation during injection without requiring exhaustive training for device usage. A three-step approach is employed for the design, where computational fluid dynamics (CFD) and finite element analysis (FEA) methods are employed to ensure that the device produces a laminar insulin flow and the device strength is tested. It should be pointed out both methods are required since complications produced by sudden flows must be avoided, with CFD allowing assessment of the device mechanical properties in terms of the device strength. Initial functional evaluation indicates that the proposed approach does not require extensive training or complex operational procedures, facilitating its integration into everyday use. The device design is validated from the results obtained for the CFD analysis, as no turbulent flow is produced, whereas the FEA indicates that the geometrical form can handle the stresses produced by the folding generation without generating excessive deformations. Moreover, an infrared thermography analysis is also carried out to find out if the folding force generation is located in the zone of interest, the results of which indicate that the device operates in the desired physical zone. Full article

Background/Objectives: Clinical surveillance of infectious diseases caused by viruses, such as SARS-CoV-2, is important for effective intervention and preventing potential epidemics or pandemics. The development of cost-effective whole genome sequencing technologies has facilitated worldwide efforts to sequence viral genomes. The array of sequence data generated across the globe offers diverse opportunities to study SARS-CoV-2 evolutionary dynamics and serves as a foundation for different research questions in the future. Even though bioinformatics tools are rapidly developed for accessing and analyzing large-scale data from public repositories, surveillance labs lack streamlined pipelines to handle high sample volumes and efficiently identify mutations for variant reporting with minimal computational expertise. Methods: We have developed a SARS-CoV-2 mutational analysis pipeline using Workflow Description Language (WDL), which is open-source and combines various steps in an analysis workflow with human-readable syntax. Thus, users with minimal informatics background can easily adapt the workflow while creating a local data repository within their institution. The pipeline processes input FASTA files and quality control files from Ion Torrent S5, performs clade and variant assignments, integrates patient metadata, and stores the results into a REDCap database. Results: In this framework, REDCap acts as the core data backbone for run-level tracking and result storage. To further enhance the utility of our REDCap-based data capture system, we have developed an intuitive interactive dashboard. This interface seamlessly connects with the REDCap data sources, providing real-time monitoring, interactive visualization, and the ability to create a consolidated variant report. Conclusions: Our overall approach streamlines processes in managing complex genomic data and offers easy adaptation to empower other molecular labs. Full article

Background: Additive manufacturing (AM) has gained increasing attention in prosthetics and orthotics (P&O), yet real-world evidence on its clinical and operational value remains limited, particularly across both prosthetic and orthotic device classes within tertiary hospital practice. This study evaluated the comparative performance of AM in transtibial prosthetic sockets and ankle-foot orthoses (AFOs) within Singapore’s public healthcare setting. Methods: Two comparative clinical evaluations were conducted. The transtibial socket component used a prospective two-period cross-over design across two P&O departments in NHG Health hospitals, comparing digitally fabricated Multi Jet Fusion (MJF) sockets against conventionally laminated sockets. The AFO component compared posterior cut-out MJF AFOs against conventional polypropylene AFOs within a tertiary hospital P&O service. Patient-reported outcomes were assessed using the Prosthesis Evaluation Questionnaire (PEQ) and Socket Comfort Score (SCS) for sockets, and the Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0) for AFOs. Workflow time and cost outcomes were also examined. Results: No statistically significant differences were identified between 3D-printed and conventional transtibial sockets across PEQ domains or SCS measures. Of 15 participants contributing preference data, 9 preferred the 3D-printed socket. The digitally enabled socket workflow reduced technician time and total man-hours but increased total cost because of higher consumables costs. In the AFO cohort, overall QUEST scores did not differ significantly between the posterior cut-out MJF AFO and the conventional polypropylene AFO (mean 4.49 vs. 4.55; p = 0.432). Digital fabrication reduced clinician handling time from 60 to 27 min per device. A unilateral MJF AFO design was discontinued because of biomechanical insufficiency. Conclusions: AM demonstrated comparable short-term patient-reported outcomes to conventional fabrication in selected transtibial socket and AFO applications, although the study was not designed to prove clinical equivalence. Operational benefits were conditional and depended on workflow maturity, design suitability, and service context. Full article

Hypertension frequently remains uncontrolled despite pharmacological therapy, supporting interest in complementary nutritional strategies. This narrative review evaluates human clinical evidence and mechanistic pathways for minerals, polyphenols, omega-3 fatty acids, probiotics, coenzyme Q10, and L-arginine in blood pressure regulation. Across these categories, antihypertensive effects appear to depend largely on post-ingestion metabolic biotransformation into bioactive metabolites that influence endothelial nitric oxide availability, vascular inflammation, renal sodium handling, and renin–angiotensin system activity. Randomized controlled trials and meta-analyses consistently demonstrate modest reductions in systolic blood pressure of approximately 2–8 mmHg, although most studies are short-term and frequently use supplementation models. The overall certainty of evidence is moderate due to consistent but heterogeneous randomized trials. Variability in response is partly explained by metabolic phenotype and gut microbiota composition, and combined dietary patterns targeting multiple mechanisms may produce additive effects. Overall, nutraceuticals function as adjunct physiological modulators that may contribute to cardiovascular risk reduction but are not intended to replace pharmacological therapy. The present review integrates post-ingestion metabolism, microbiota-derived mediators, and clinical trial evidence into a unified physiological framework explaining why consistent but modest blood pressure reductions occur across heterogeneous interventions. Nutritional strategies remain underutilized in routine clinical practice despite reproducible physiological effects. Incorporating evidence-based nutraceutical approaches alongside pharmacological management may facilitate patient engagement with lifestyle modification, as dietary interventions are often perceived as more achievable than isolated behavioral recommendations. A holistic management model integrating medical therapy, nutrition, and patient education may therefore enhance long-term adherence to cardiovascular prevention strategies and support sustained risk reduction. Full article

Background: The growing demand for versatile laboratory automation is exemplified in the context of liquid biopsy, where multi-analyte approaches are increasingly recognised for their potential to enhance diagnostic sensitivity in oncology. However, current practice often necessitates the use of dedicated instruments and workflows for the extraction of each analyte, posing financial and logistical barriers for automated multi-analyte liquid biopsy. Methods: Here, we present Robotic Centrifugal Microfluidics (RoCM), an all-in-one platform that combines the versatility of centrifugal microfluidics and operational flexibility of robotic liquid handling. This combination enables the automation of complex micro- and macrofluidic protocols, realised through the use of (1). exchangeable microfluidic cartridges and (2). programmable robotic operations such as in-rotation liquid supply, magnetic bead manipulation, or microfluidic valving. In-rotation robotic liquid manipulation maintains fluid control under centrifugal forces and reduces the cartridge footprint associated with pre-loaded liquid reservoirs. Platform applicability was demonstrated using two exemplary liquid biopsy workflows: the extraction of cell-free DNA (cfDNA) from blood plasma using RoCM-cfDNA slices and the extraction of extracellular vesicles (EVs) from blood plasma using RoCM-EV slices. Results: In a pilot study with patient samples from different cancer entities, the RoCM-cfDNA slices yielded comparable variant allele frequencies to a commercial bead-based instrument, while the RoCM-EV slices achieved a recovery of a greater diversity of EV subpopulations than semi-automated size-exclusion chromatography. Conclusions: By simply exchanging cartridges, RoCM enables the extraction of diverse analytes within a single automated system. Its application can be extended to further analytes, such as circulating tumour cells (CTCs), or to applications beyond liquid biopsies, where versatile micro- and macrofluidic protocols benefit from implementation in a single automation instrument. Full article

Eicosanoids and their receptors act as key regulators of inflammation, calcium homeostasis, mitochondrial function, and cardiomyocyte survival, thereby contributing to the onset and progression of cardiac dysfunction. This review aims to summarize the evidence to underscore the pivotal role of eicosanoids and their receptors in the pathophysiology of cardiomyopathy, analysing the potential protective activity of traditional and natural compounds to counteract cardiovascular disease onset and progression. Among eicosanoid receptors, prostaglandin E2 receptor 3 (EP3), prostaglandin E2 receptor 4 (EP4), chemoattractant receptor expressed on type 2 helper T cells (CRTH2), and thromboxane prostanoid (TP) emerge as critical modulators with distinct and often opposing effects on cardiac physiology. While EP3 and CRTH2 are predominantly associated with detrimental outcomes such as impaired contractility and enhanced apoptosis, EP4 signalling consistently demonstrates cardioprotective properties, including improved calcium handling and preservation of mitochondrial integrity. These findings highlight the therapeutic potential of selectively targeting eicosanoid receptor pathways to mitigate cardiac remodelling and dysfunction. In parallel, increasing attention has been directed toward natural bioactive compounds as complementary strategies for cardioprotection. Polyphenols, flavonoids, carotenoids, and other nutraceuticals exert beneficial effects through antioxidant, anti-inflammatory, and anti-apoptotic mechanisms, often intersecting with eicosanoid signalling pathways. Their ability to modulate oxidative stress and inflammatory responses suggests a promising role in preventing or attenuating cardiomyopathy, particularly in metabolic and drug-induced contexts. Future research should focus on well-designed clinical trials, a deeper characterization of receptor-specific signalling networks, and the development of targeted therapies that combine pharmacological and nutraceutical approaches. Overall, a better understanding of eicosanoid-mediated mechanisms may open new ways for cardiomyopathy prevention and treatment, ultimately improving patient outcomes and reducing the burden of cardiovascular disease. Full article