Search Results (78)

Background: Wide-awake local anesthesia with no tourniquet (WALANT) carpal tunnel release (CTR), performed in the clinic setting, has emerged as a safe, efficient, and cost-effective alternative to traditional operating room (OR)-based decompression. With increasing adoption in clinic settings, WALANT CTR offers the potential to improve access, reduce costs, and maintain excellent patient outcomes. Purpose: This clinical practice update provides an evidence-based summary of clinic-based WALANT CTR, including patient selection, procedural setup, safety profile, cost implications, and system-level considerations for implementation. Recent Findings: Multiple prospective and retrospective studies confirm the safety of WALANT CTR in the clinic setting, with complication rates comparable to OR-based procedures and no increase in surgical-site infections when field sterility is used. Cost analyses report a 70–85% reduction in facility costs per operative case, and patient satisfaction remains consistently high, even among those with anxiety disorders or psychiatric conditions. Adjunctive interventions such as virtual reality technology devices and noise-canceling headphones further enhance the awake surgical experience. Institutional adoption remains variable, with barriers including sterility concerns, billing uncertainty, and credentialing logistics. This clinical update offers detailed, practical guidance on implementing WALANT CTR for surgeons and staff, covering scheduling, staff training, clinical integration, billing, and compliance considerations. Summary: Clinic-based WALANT CTR is a high-value, patient-centered approach supported by a growing body of literature. With appropriate patient selection, streamlined workflows, and institutional support, this model can optimize surgical care delivery in both resource-rich and limited environments. Full article

Battery electric vehicles (BEVs) are gaining market share, yet range anxiety and sparse charging still create demand for hybrids with combustion-engine range extenders. Range-extender vehicles face high customer expectations for noise, vibration, and harshness (NVH) due to their direct comparability with fully electric vehicles. Key challenges include the vibrations of the internal combustion engine, especially from vehicle-induced starts, and the discontinuous operating principle. A technological concept to reduce vibrations in the drivetrain and on the engine mounts, called “FEVcom,” relies on rolling moment compensation. In this concept, a counter-rotating electric machine is coupled to the internal combustion engine via a gear stage to minimize external mount forces. However, due to high speed fluctuations of the crankshaft, the gear drive tends to rattle, which is perceived as disturbing and must be avoided. As part of this work, the rolling moment compensation system was examined regarding its vibration excitation, and an extension to prevent gear rattling was simulated and optimized. For the simulation, the extension, based on a chain or belt drive, was set up as a multi-body simulation model in combination with the range extender and examined dynamically at different speeds. Variations of the extended system were simulated, and recommendations for an optimized layout were derived. This work demonstrates the feasibility of successful rattling avoidance in a range-extender drivetrain with full utilization of the rolling moment compensation. It also provides a solid foundation for further detailed investigations and for developing a prototype for experimental validation based on the understanding gained of the system. Full article

There is growing evidence regarding non-pharmacological therapies such as music as a supportive approach for the treatment of various clinical conditions in humans. Physiological and neurobiological research suggests that music exposure is related to endorphin, endocannabinoid and dopamine release, favourable effects on autonomic nervous system functioning and is associated with decreased pain perception and reduced stress response. Further evidence in humans demonstrates a beneficial role of music application during the perioperative period by improving various outcome measures, such as the perioperative stress and anxiety levels, the sedation or general anaesthetic requirements, the pain levels, the analgesic requirements and other parameters related to patient prognosis, without reported side effects. Accordingly, such interventions have been considered as a method of environmental enrichment for animal welfare enhancement, by masking potentially disturbing background noises and by ameliorating anxiety or aggressive behaviours in different stressful settings in dogs and cats. Furthermore, research has been lately extended to the potential music’s effect in these species during the perioperative period, considered a stressful setting, as well. This review presents the existing evidence of music application focusing on the perioperative period of dogs and cats, as part of a multimodal approach, to improve their surgical outcome and welfare. Full article

Temporomandibular disorders (TMDs) encompass a heterogeneous group of musculoskeletal and neuromuscular conditions affecting the temporomandibular joint (TMJ) and masticatory system. Due to academic stress and parafunctional habits, dental students may be particularly vulnerable to TMD. Objective: To determine the prevalence of TMD symptoms and their psychosocial and functional correlates among students at the Faculty of Dental Medicine, UMPh Iasi, Romania, using the diagnostic criteria for TMD (DC/TMD) self-report axis and axis II instruments. Methods: In this cross-sectional survey, 356 volunteer students (66.0% female; mean age, 22.9 ± 3.6 years) out of a total population of 1874 completed an online DC/TMD–based questionnaire. Axis I assessed orofacial pain, joint noises, and mandibular locking. Axis II instruments included the Graded Chronic Pain Scale (GCPS), Jaw Functional Limitation Scale (JFLS-20), Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and Oral Behaviors Checklist (OBC). Descriptive statistics summarized frequencies, means, and standard deviations; χ² tests and t-tests compared subgroups by sex; Pearson correlations explored relationships among continuous measures (α = 0.05). Results: A total of 5% of respondents reported orofacial pain in the past 30 days; 41.6% observed TMJ noises; 19.7% experienced locking episodes. Mean JFLS score was 28.3 ± 30.5, with 4.8% scoring > 80 (severe limitation). Mean PHQ-9 was 5.96 ± 5.37 (mild depression); 15.5% scored ≥ 10. Mean GAD-7 was 5.20 ± 4.95 (mild anxiety); 16.0% scored ≥ 10. Mean OBC score was 12.3 ± 8.5; 30.1% scored ≥ 16, indicating frequent parafunctional habits. Symptom prevalence was similar by sex, except temporal headache (43.4% females vs. 24.3% males; p = 0.0008). Females reported higher mean scores for pain intensity (2.09 vs. 1.55; p = 0.0013), JFLS (32.5 vs. 18.0; p < 0.001), PHQ-9 (6.43 vs. 5.16; p = 0.048), and OBC (13.9 vs. 9.7; p = 0.0014). Strong correlation was observed between PHQ-9 and GAD-7 (r = 0.74; p < 0.001); moderate correlations were observed between pain intensity and PHQ-9 (r = 0.31) or GAD-7 (r = 0.30), between JFLS and pain intensity (r = 0.33), and between OBC and PHQ-9 (r = 0.39) (all p < 0.001). Conclusions: Nearly half of dental students reported TMD symptoms, with appreciable functional limitation and psychosocial impact. Parafunctional behaviors and psychological distress were significantly associated with pain and dysfunction. These findings underscore the need for early screening, stress-management interventions, and interdisciplinary care strategies in the dental student population. Full article

High-pitched noise generated by dental air turbine handpieces (ATHs) causes discomfort and anxiety, discouraging dental visits. Understanding the time-dependent noise generation mechanism associated with compressed airflow in ATHs is crucial for effective noise reduction. However, the direct investigation of airflow dynamics within ATHs is challenging. The transient-state modeling of computational fluid dynamics (CFD) simulations remains unexplored owing to the complexities of high rotational speeds and air compressibility. This study develops a novel CFD framework for transient (time-dependent) modeling under high-speed rotational conditions. Simulations were performed using a three-dimensional model reconstructed from a commercial ATH. Simulations were conducted at 320,000 rpm using a novel framework that combines the immersed boundary and building cube methods. A fine 0.025 mm mesh spacing near the ATH, combined with supercomputing resources, enabled the simulation of hundreds of millions of cells. The simulation results were validated using experimental noise measurements. The CFD simulation revealed transient airflow and aeroacoustic behavior inside and around the ATH that closely matched the prominent frequency peaks from the experimental data. This study is the first to simulate the transient airflow of ATHs. The proposed CFD model can accurately predict aeroacoustics, contributing to the future development of quieter and more efficient dental devices. Full article

The acoustic environment of dental clinics plays a critical role in shaping patient experience, staff performance, and overall clinical effectiveness. This comprehensive review, supported by systematic search procedures, investigates how soundscapes in dental settings influence psychological, physiological, and operational outcomes. A total of 60 peer-reviewed studies were analyzed across dental, healthcare, architectural, and environmental psychology disciplines. Findings indicate that mechanical noise from dental instruments, ambient reverberation, and inadequate acoustic zoning contribute significantly to patient anxiety and professional fatigue. The review identifies emerging strategies for acoustic optimization, including biophilic and sustainable design principles, sound-masking systems, and adaptive sound environments informed by artificial intelligence. Special attention is given to the integration of lean management and circular economy practices for sustainable dental architecture. A design checklist and practical framework are proposed for use by dental professionals, architects, and healthcare planners. Although limited by the predominance of observational studies and geographic bias in the existing literature, this review offers a comprehensive, interdisciplinary synthesis. It highlights the need for future clinical trials, real-time acoustic assessments, and participatory co-design methods to enhance acoustic quality in dental settings. Overall, the study positions sound design as a foundational element in creating patient-centered, ecologically responsible dental environments. Full article

Individuals with Autism Spectrum Disorder (ASD) often experience sensory hyperreactivities that interfere with daily life activities. White noise, characterized by its uniformity and its ability to mask environmental sounds, may serve as a tool to improve sensory and emotional regulation in children with ASD. The primary objective was to evaluate the response to white noise in improving self-regulation in minors with ASD. As a secondary objective, the study assessed whether there were differences in the response to white noise between patients with ASD and those with ASD and Intellectual Disability (ID). This study was conducted in the Child and Adolescent Psychiatry and Psychology Department of Hospital Clínic of Barcelona. A total of 54 patients, aged between 7 and 17 years, were included. The patients were divided into two groups: Group 1 consisted of patients diagnosed with ASD (n = 21), and Group 2 included patients diagnosed with ASD and ID (n = 33). White noise was offered to the patients, and their response was evaluated before and after the exposure using the Conners Teacher Rating Scale. Overall, the response to white noise in the sample was positive, with a significant difference in scores on the Conners Teacher Rating Scale (p < 0.001). When dividing the sample into the ASD group and the ASD + ID group, it was observed that the ASD + ID group tolerated white noise better and had a longer exposure time, although both groups showed improved scores on the Conners Teacher Rating Scale. White noise may be a valuable tool to enhance well-being in individuals with ASD, reduce motor restlessness, and increase attention span and emotional stability. However, its effectiveness varies across individuals. It is recommended to tailor its use to individual needs and to extend future research by incorporating physiological measures and larger sample sizes. Full article

Background/Objectives: Patients with headache experience depression, anxiety, and reduced quality of life, which are individually associated with pain intensity and painkiller use, but their comprehensive combined effect remains unclear. Methods: Comprehensive patient groups were formed based on unsupervised clustering using machine learning algorithms, and their associations were analyzed via ordinary least square regression. K-means and t-distributed stochastic neighbor embedding (t-SNE) combined with hierarchical density-based spatial clustering of applications with noise (HDBSCAN) were applied for clustering. Results: A total of 813 patients were subdivided via K-means clustering (2 clusters) and t-SNE + HDBSCAN clustering (4 clusters). In the K-means clustering, Cluster 1 showed significantly lower peak pain intensity (coefficient [95% CI]: −0.7 [−1 to −0.4]) and frequency of painkiller use (−2.3 [−3.4 to −1.3]) compared to Cluster 0. In the t-SNE + HDBSCAN clustering, Clusters 2 and 3 showed higher peak pain intensity (1.1 [0.5–1.7] and 1.6 [1.0–2.2], respectively) and more frequent painkiller use (2.5 [0.4–4.5] and 4.4 [2.2–6.7], respectively) than Cluster 1. Conclusions: The clustering approach successfully generated groups that reflected a comprehensive profile of depression-, anxiety-, and headache-related quality of life. The clusters demonstrated significant differences which can help better characterize patients based on their psychological and functional impact. Full article

Background: Many older Australian adults with cochlear implants (CI) lack funding for replacement sound processors, risking complete device failure and reduced quality of life. The need for replacement CI devices for individuals with obsolete sound processors and no access to funding poses an increasing public health challenge in Australia and worldwide. We aimed to investigate the clinical and cost-effectiveness of upgrading obsolete CI sound processors in older adults. Methods: Alongside an Australian Government-funded upgrade program, a prospective, mixed-methodology design study was undertaken. Participants were aged 65 and over, with obsolete Cochlear™ sound processors and no funding for replacements. This study compared speech perception in noise, as well as self-reported outcome measures, including cognition, listening effort, fatigue, device benefit, mental well-being, participation, empowerment and user experiences, between upgraded and obsolete hearing aid processors. The economic impact of the upgrade was evaluated using two state-transition microsimulation models of adults using CIs. Results: The multi-site study ran from 20 May 2021 to 21 April 2023, with recruitment from June 2021 to May 2022. A total of 340 Cochlear™ sound processors were upgraded in 304 adults. The adults’ mean age was 77.4 years (SD 6.6), and 48.5% were female. Hearing loss onset occurred on average at 30 years (SD 21.0), with 12 years (SD 6.2) of CI use. The outcomes show significant improvements in speech understanding in noise and reduced communication difficulties, self-reported listening effort and fatigue. Semi-structured interviews have revealed that upgrades alleviated the anxiety and fear of sudden processor failure. Health economic analysis found that the cost-effectiveness of upgrades stemmed from preventing device failures, rather than from access to newer technology features. Conclusions: Our study identified significant clinical and self-reported benefits from upgrading Cochlear™ sound processors. Economic value came from avoiding scenarios where a total failure of device renders its user unable to access sound. The evidence gathered can be used to inform policy on CI processor upgrades for older adults. Full article

Background: Recent advancements in machine learning (ML) have significantly influenced the analysis of brain signals, particularly electroencephalography (EEG), enhancing the detection of complex neural patterns. ML enables large-scale data processing, offering novel opportunities for diagnosing and treating mental disorders. However, challenges such as data variability, noise, and model interpretability remain significant. This study reviews the current limitations of EEG-based anxiety detection and explores the potential of advanced AI models, including transformers and VAE-D2GAN, to improve diagnostic accuracy and real-time monitoring. Methods: The paper presents the application of ML algorithms, with a focus on convolutional neural networks (CNN) and recurrent neural networks (RNN), in identifying biomarkers of anxiety disorders and predicting therapy responses. Additionally, it discusses the role of brain–computer interfaces (BCIs) in assisting individuals with disabilities by enabling device control through brain activity. Results: Experimental EEG research on BCI applications was conducted, focusing on motor imagery-based brain activity. Findings indicate that successive training sessions improve signal classification accuracy, emphasizing the need for personalized and adaptive EEG analysis methods. Challenges in BCI usability and technological constraints in EEG processing are also addressed. Conclusions: By integrating ML with EEG analysis, this study highlights the potential for future healthcare applications, including neurorehabilitation, anxiety disorder therapy, and predictive clinical models. Future research should focus on optimizing ML algorithms, enhancing personalization, and addressing ethical concerns related to patient privacy. Full article

Background: This study aimed to develop a model for understanding stress-induced sleep disturbances and to explore the potential interactions between sleep disturbances and mood disturbances. Methods: The chronic unpredictable mild stress (CUMS) group was established using the CUMS method, while the CUMS+Noise group was subjected to an additional 8-h exposure to noise in conjunction with the CUMS protocol. Each group was tested for anxiety and depressive-like behavior using the open-field, elevated plus maze, tail suspension, and forced swimming tests in male C57BL/6J mice. Subsequently, we assessed sleep status using sleep recordings and a standardized scoring system alongside the pentobarbital sodium-induced sleep test. Results: The mice in both model groups exhibited anxiety-like behavior. Sleep disturbances observed in the CUMS+Noise group were characterized by disruptions in sleep duration and circadian rhythm. This observation was supported by a marked reduction in multiple sleep time intervals and single sleep duration, as well as a significant increase in sleep duration at the final time interval of ZT23-24. To further investigate the potential mechanisms of interaction, we conducted an analysis of hub genes present in the hippocampal sequencing data utilizing weighted gene co-expression network analysis (WGCNA). Pearson correlation analysis revealed a significant association between the hub genes Alb, P2rx1, and Npsr1 and key phenotypic traits. However, PCR experiments indicated that only Alb showed a significant difference, which aligns with the sequencing results. Conclusions: Albumin is a crucial transporter protein for thyroid hormones and plays a vital role in their metabolism. The interaction between sleep disorders and anxiety-like behavior may be closely linked to the dysfunctional transportation of thyroid hormones by albumin. Full article

Feather pecking (FP) is a significant welfare and economic problem in laying hen husbandry. While there is growing evidence that the glutamatergic system plays a crucial role in regulating FP behavior, the biological mechanisms remain unclear, largely due to the limited uptake of peripheral glutamate across the blood–brain barrier (BBB). Here, we applied a multi-omics approach combined with physiology assays to answer this question from the perspective of the gut–brain axis. A total of 108 hens were randomly assigned to two groups (treatment and control) with six replicates each, and the treatment group was subjected to chronic environmental stressors including re-housing, noise, and transport. We found that chronic exposure to environmental stressors induced severe FP, accompanied by reduced production performance and increased anxiety- and depression-related behaviors, compared to controls. In addition, the immune system was potentially disrupted in FP chickens. Notably, gut microbiota diversity and composition were significantly altered, leading to decreased microbial community stability. Non-targeted metabolomic analysis identified a variety of differential metabolites, primarily associated with arginine and histidine biosynthesis. A significant increase in glutamate levels was also observed in the hippocampus of FP chickens. Transcriptome analysis revealed the upregulated expressions of glutamate-related receptors GRIN2A and SLC17A6 in the hippocampus. Correlation analysis indicated that GRIN2A and SLC17A6 are positively associated with arginine levels in the duodenum, while Romboutsia in the duodenum is negatively correlated with arginine. These findings suggest that intestinal bacteria, including Romboutsia, may influence FP behavior by altering plasma arginine and histidine levels. These changes, in turn, affect glutamate levels and receptor gene expression in the hippocampus, thereby regulating the glutamatergic system. Our research offers insights into novel strategies for mitigating harmful behaviors in poultry farming, with potential benefits for animal performance and welfare. Full article

Chronic pain leads to not only physical discomfort but also psychological challenges, such as depression and anxiety, which contribute to a substantial healthcare burden. Pain detection and assessment remains a challenge due to its subjective nature. Current clinical methods may be inaccurate or unfeasible for non-verbal patients. Consequently, Electroencephalography (EEG) has emerged as a promising non-invasive tool for pain detection. However, EEG-based pain detection faces challenges such as noise, volume conduction effects, and high inter-subject variability. Deep learning (DL) models have shown potential in overcoming these challenges by extracting nonlinear and discriminative patterns. Despite advancements, these models often require a subject-dependent approach and lack of interpretability. To address these limitations, we propose a threefold DL-based framework for coding EEG-based pain detection patterns. (i) We employ the Kernel Cross-Spectral Gaussian Functional Connectivity Network (KCS-FCnet) to code pairwise channel dependencies for pain detection. (ii) Furthermore, we introduce a frequency-based strategy for class activation mapping to visualize pertinent pain EEG features, thereby enhancing visual interpretability through spatio-frequency patterns. (iii) Further, to account for subject variability, we conduct cross-subject analysis and grouping, clustering individuals based on similar pain detection performance, functional connectivity patterns, sex, and age. We evaluate our model using the Brain Mediators of Pain dataset and demonstrate its robustness through subject-dependent and cross-subject generalization tasks for pain detection on non-verbal patients. Full article

Background: Sounds that cause disturbances and perturbations to the vestibular (inner ear organ responses) and visual (acute oculomotor responses) systems can impact postural stability. The purpose of this study was to assess the impact of different types of sounds and noises on both static and dynamic PS. Methods: A total of 20 participants (12 females and 8 males; age: 21.35 ± 1.79 years; height: 170.7 ± 9.3 cm; mass: 66.725 ± 14.1 kg) were tested using the limits of stability (LOS) test on the BTrackS™ balance plate and a Timed Up and Go (TUG) test, when exposed to four different sounds and occupational noises [construction noise (CN), white noise (WN), sirens (SRs), and nature sounds (NAs)] in a randomized order with a no sounds (NSs) control performed initially (intensity range of 70–80 dB). The center of pressure (COP) total sway area (cm²) from the LOS and the time to completion of the TUG (seconds) were analyzed using a one-way repeated measures of analysis of variance at an alpha level of 0.05. Results: The observations demonstrated significant differences between the sounds and noises for the TUG (p < 0.001) but not for the LOS test (p = 0.406). Pairwise comparisons for the significant main effect for the TUG revealed that NSs demonstrated significantly slower time to completion compared to CN, WN, and SRs but not NAs. Conclusions: The findings suggest that the different sounds and noises did not impact static PS during the LOS test, which involved the voluntary excursion of the COP while maintaining the same base of support (BOS). However, during dynamic PS with a changing BOS while walking in the TUG, exposure to CN, SRs, and WN demonstrated a faster completion time than NSs or NAs. This finding may be attributed to the anxiety induced by the noise immersion and perception of sounds, compared to calm NAs and no sounds. The findings can aid in better understanding the impact of different occupational noises on PS and emphasize the need for better noise protection and reduction in loud work environments. Full article

Introduction: Patients in intensive care units (ICUs) face factors that cause anxiety, fear, pain, depression, and adverse health behaviors. This qualitative study aims to determine patients’ experiences when transferred from the ICU to the ward. Methods: Thirteen individuals who were transferred from the ICU to the ward were included in this study. Interviews were conducted using a face-to-face method in the patient’s room. The interviews were recorded with a voice recorder with the consent of the patients. Codes, categories, and themes were created, and content analysis and descriptive analysis were carried out after the audio recordings were converted into text. Results: Patients reported receiving adequate physical and personal care in the ICU and were satisfied with its continuity. They felt safe due to the close attention of healthcare professionals and continuous treatment. Although they received psychological and social support from nurses, they were negatively affected by constant lights, patient noises, and nursing conversations. Patients experienced anxiety about not knowing the health status and time of day, about their relatives, their homes, and other critically ill patients in intensive care. Some patients reported fear of not being able to leave the intensive care unit, relapse, disability, or death. Patients reported pain due to the cold environment, lighting, probes, drains, and positioning. Patients suggested that healthcare personnel communicate better with them, have a clock they can see, reduce noise, and have caregivers of the same gender. They emphasized the need for moral support. Conclusions: Constant light in the intensive care unit, sounds from other patients, nurses talking among themselves, not being able to see their relatives, not knowing what time of day it is, and wondering caused anxiety in the patients. It was determined that patients experienced pain due to catheter, drain, aspiration procedures, cold environment, and position in bed. Notably, patients reported that they needed moral support and wanted to receive care from caregivers of the same gender. Full article