Search Results (3,961)

In today’s rapidly advancing healthcare landscape, integrating Artificial Intelligence (AI) and Machine Learning (ML) has the potential to significantly improve patient care and streamline medical processes. The utilization of confidential patient data to train and develop these technologies, however, raises significant concerns regarding authenticity, security, and privacy. In this study, we introduce MediChainAI, a safe and practical framework that allows patients full ownership over their own health data by integrating Self-Sovereign Identity (SSI), Blockchain, and sophisticated cryptography techniques. By clearly outlining the goals and parameters of this access, MediChainAI allows patients to safely and selectively share data with healthcare providers and researchers. While SSI guarantees that patients have ownership of their data, the framework uses Blockchain technology to keep things transparent and secure. Further, MediChainAI makes use of Merkle trees, which provide verified access to subsets of data without jeopardizing the privacy of the whole dataset. The encryption mechanism, which is based on smart contracts, is a distinctive feature of the framework that allows researchers and medical practitioners controlled and secure access to patient data. In order to improve the accuracy and reliability of medical diagnoses and treatment, this strategy makes sure that only confirmed, legitimate data is utilized to train medical models. A significant step toward safer and more personalized healthcare, MediChainAI encourages ethical and patient-focused innovation by effectively resolving essential issues regarding data security and patient privacy. Full article

Women with endometriosis often experience insufficient knowledge and support regarding their condition within the healthcare system. Women use social media to obtain information, share personal experiences, and establish connections with others. This study examined how women with endometriosis-like symptoms use Reddit to seek support and acquire knowledge for self-management, with three research questions guided by the Information–Motivation–Behavioural skills model. A total of 194 threads were analysed from the r/endo subreddit, and a reflexive thematic analysis was conducted. Three overarching themes were identified (information, motivation, and behavioural skills) and six subthemes emerged from the data (endometriosis experience, endometriosis medical care, personal life impacts, social existence impacts, management strategies negative, and management strategies positive). Findings highlight that Reddit functions as a source of shared knowledge, symptom validation, emotional support, supplementing gaps in traditional healthcare services. This study provides insights into how healthcare systems and professionals can support women with endometriosis, including timely diagnosis and management strategies, in addition to a framework for an endometriosis Information–Motivation–Behavioural skills model. Future research could expand on study findings by implementing this conceptualised model in a mixed-methods context to gain insight into women’s endometriosis experiences within healthcare systems to understand how they can be empowered and supported. Full article

Background/Objectives: Maintaining independent mobility among older adults requires complex cognitive and physical health and is influenced by various health-related factors. This study sought to examine the relationship between health-related factors and driving among community-dwelling older adults by comparing the health status of currently driving individuals and those who have ceased driving. Methods: A secondary data analysis was conducted using the 2023 Korean Elderly Survey, collected between 4 September and 12 November 2023. A total of 4114 individuals aged 65 years or older were included. Statistical analyses were performed using chi-square tests, independent t-tests, and weighted binary logistic regressions via IBM SPSS for Windows. Results: Significant health-related factors for driving cessation included having ≥2 chronic diseases (OR = 1.22, p = 0.041), diagnosed depression (OR = 3.64, p = 0.030), Instrumental Activities of Daily Living dependency (OR = 1.67, p = 0.001), visual discomfort (OR = 1.18, p = 0.048), depression risk (OR = 1.34, p = 0.015), suspected cognitive impairment (OR = 1.73, p < 0.001), and poor self-rated health (OR = 1.21, p = 0.029). None of the participants with Parkinson’s were currently driving, whereas polypharmacy (≥5 medications) was not statistically significant (OR = 0.77, p = 0.222). Chronic diseases that may affect driving were also not statistically significant. Conclusions: This study highlights the fact that older drivers may have difficulty recognizing health-related risks that affect driving. To support safe mobility, it is essential to implement a health-centered assessment of driving fitness, including an appropriate evaluation cycle, and promote continuous education to raise awareness among older adults. Full article

Placebo, nocebo, and lessebo effects are very frequent in patients with both neurological and psychiatric disorders. Interestingly, the neural mechanisms underlying placebo effects have been found to be the same as or similar to mechanisms targeted by active pharmaceutical interventions for many of these disorders. In the case of functional neurological disorders (FNDs), there are shared neural substrates between the central nervous system “placebo network” and the dysfunctional networks implicated in the pathophysiology. These networks are primarily involved in emotion regulation, stress responses, and the sense of self-agency. Therefore, placebo effects have also been discussed as therapeutic interventions in FNDs. Such an approach, however, has a variety of ethical implications evolving around informed consent, autonomy, nonmaleficence, beneficence, and justice. In this paper, we discuss the use of placebo, nocebo, and lessebo in FNDs as well as related ethical issues. Overall, the use of placebo in FNDs is currently still considered controversial both for diagnostic as well as therapeutic purposes. Although it is a safe and almost unique intervention, its use violates the core principles of medical ethics and doctor–patient interactions involving autonomy or openness in the therapeutic relationship. Full article

Introduction: Rheumatic diseases, including spondyloarthritis, systemic lupus erythematosus, Takayasu’s nonspecific aortoarteritis, Behcet’s disease, and Kawasaki disease, are more prevalent among Asian populations. The indigenous Sakha people, who live in the harsh conditions of the North and the Arctic regions, exhibit a unique pattern of health issues. AIM: The objective of the study is to characterize the ethnic characteristics of juvenile idiopathic arthritis (JIA) among children from the indigenous population of the Republic of Sakha (Yakutia) and compare them with Caucasians (Russians) living in the same region. This comparison aims to inform the development of tailored diagnostic and treatment strategies. Methods: The comprehensive, single-center, retrospective cohort study included medical data of all Sakha (n = 168) and Russian ethnic patients (n = 48) with JIA who were examined and treated at the Pediatric Center’s Cardiorheumatology Department at the Republican Hospital No. 1–M.E. Nikolaev National Center of Medicine—between 2016 and 2023. The ethnicity was self-reported. The standard clinical procedures and laboratory assessments, as well as the current treatment regimen, were thoroughly reviewed. Results: It was found that children of Sakha descent had a later onset of juvenile idiopathic arthritis (JIA), which was associated with the enthesitis-related arthritis (ERA) categories (51.2% vs. 18.3%, p = 0.0002). They also exhibited higher prevalence of enthesitis (19% vs. 2.0%, p = 0.003), sacroiliitis (23.8% vs. 2.0%, p = 0.0003), and HLA-B27 antigen positivity (46.3% vs. 14.6%, p = 0.00005). The Sakha population exhibited a notably higher prevalence (41.7%) of ERA, compared to the Russian population (33.3%; p = 0.0003), and they initiated biologic therapy at a later stage. However, remission rates were lower among Sakha children (29.2%) than among Russian children (72.2%, p = 0.002), as was their likelihood of achieving remission (Log-Rank test, p = 0.005), regardless of the JIA categories (p = 0.008). Sakha children had a 64.4% reduced chance of achieving remission on the first bDMARD, compared to Russian children (HR = 0.36, 95% CI: 0.18–0.71, p = 0.004). Conclusions: Distinct variations in the progression and treatment outcomes of JIA were observed between Sakha children and Caucasians. A tailored approach to the care of JIA patients is essential, considering their ethnic background. Full article

Background/Objectives: Smoking is an established cofactor for cervical carcinogenesis, but evidence on how Smoking Pattern Changes around cohort entry relate to risk in Japan is limited. We quantified cervical cancer risk by baseline smoking status and by changes between two routine health checkups in a nationwide cohort. Methods: We used the Japan Medical Data Center claims–checkup database between January 2005 and July 2022. Women with ≥2 pre-index checkups were included; the index date was the second checkup. Self-reported smoking at each visit defined never, former (quit), new (initiated), and current (persistent) smokers; checkup pairs >36 months apart were excluded. Incident cervical cancer required ICD-10 C53 plus cancer-directed treatment (surgery, radiotherapy, or systemic antineoplastic therapy). Multivariable Cox models estimated hazard ratios (HRs) with 95% CIs, adjusting for age, BMI, alcohol, exercise, hypertension, diabetes, cerebrovascular and cardiovascular disease, and cholangitis. Results: Among 1,330,797 women, incidence rates (per 100,000 person-years) were 151.4 in never smokers and 244.9 in ever smokers. Ever versus never smoking was associated with higher risk (HR 1.53, 95% CI 1.43–1.62). A graded risk was observed across Smoking Pattern Change categories versus never: former HR 1.44 (1.15–1.79), new HR 1.51 (1.20–1.90), current HR 1.54 (1.44–1.64). By age, HRs were 1.58 (1.47–1.70) for <50 years and 1.35 (1.17–1.55) for 50–64 years; ≥65 years was not statistically significant (HR 0.69, 0.30–1.59). Conclusions: Smoking was associated with substantially higher cervical cancer risk, with a clear risk gradient from former to new to current smoking. The rapid elevation in new smokers and residual risk after quitting support integrating proactive cessation and initiation prevention into risk-stratified screening and routine health-check programs in Japan. Full article

Contemporary medical education is shifting from traditional, teacher-centred anatomy instruction toward interactive, student-centred, and clinically integrated approaches. The Jigsaw Method aligns with this shift by fostering collective competence, which is vital for effective clinical practice. This study aimed to introduce the jigsaw model to medical students and explore its perceived effectiveness in teaching anatomy. A phenomenological qualitative design was employed to explore the experiences of second-year medical students (n = 120) at the Faculty of Health-Care Sciences, Eastern University, Sri Lanka. Open-ended questions were used to elicit students’ reflections on the effectiveness of jigsaw learning. Thematic analysis was conducted using NVivo software (ver.14). Students reported generally favourable perceptions of the jigsaw method. Four major themes emerged: two described the positive impact of the approach—enhanced understanding through peer learning and improved interpersonal and communication skills; the remaining themes addressed challenges in implementation and suggestions for refinement. Participants appreciated the structured collaboration and positive interdependence fostered by the method. Moreover, students viewed the jigsaw technique as well-aligned with student-centred learning principles. The jigsaw method was perceived as an effective cooperative learning strategy that enhanced engagement, promoted active participation, and fostered teamwork in anatomy education. These findings support the integration of structured peer-based approaches into medical curricula to enrich students’ learning experiences. Full article

Aim: This study was conducted to determine the drug use behaviors of patients applying to primary healthcare centers and the factors affecting these behaviors. Material and method: This cross-sectional, analytic study included 913 individuals applying to family health centers for various reasons in Kayseri, Türkiye. All subjects completed a questionnaire that asked about sociodemographic characteristics and attitudes towards drug use via the Morisky Medication Adherence Scale and the Adult Health Literacy Scale. Data were analyzed using descriptive statistics. Results: A total of 913 individuals, comprising 288 (31.5%) men and 625 (68.5%) women, participated in this research. The average age of the participants was 41.79. Of the 913 subjects included, 23% reported that they would wait for recovery from a disease without any treatment attempt, while 53.5% reported that they visited a doctor, and 63.5% reported that they initially consulted a family health center. A total of 38.5% reported that they self-medicated without consulting a doctor. In addition, 79% of the subjects reported that they used medicine without a prescription. Conclusions: It was observed that age, gender, social insurance, educational status, level of health literacy, and presence of chronic diseases affect drug use behaviors. A weak, negative correlation was found between Morisky Medication Adherence scores and health literacy. Additionally, it was determined that only checking the expiration date before using a drug had an impact on drug adherence. Full article

Background: Pediatric oncological diagnoses and treatments pose complex biopsychosocial challenges for both patients and their families. These experiences can significantly disrupt daily life, evoke intense emotional responses, and raise concerns about the future, often leading to long-term psychological implications. Objective: This study aimed to assess the emotional functioning of children undergoing cancer treatment and to explore the lasting psychological effects reported by young adult survivors of pediatric cancer. Methods: A mixed-methods approach was employed. In total, 52 minors and their caregivers were recruited from two pediatric oncology units in Italy (Turin and Bari), while 18 young adults diagnosed during childhood were recruited from clinical and community settings in Ancona and Bari. Standardized instruments were used to evaluate emotional symptoms and broader psychological functioning in the pediatric sample, while self-report measures assessed psychological well-being and quality of life in the young adult group. To complement these data, semi-structured interviews were conducted with the young adult survivors to investigate the long-term psychosocial and psychological impacts of pediatric cancer. Results: The quantitative results indicate generally low levels of psychological distress in both groups. However, the qualitative findings reveal the complexity of post-cancer identity, highlighting experiences of resilience, emotional ambivalence, and redefinition of self. Conclusions: These results underscore the importance of addressing the psychological well-being of pediatric oncology patients and young adult survivors beyond the medical treatment phase, with a focus on long-term psychosocial support and individualized care. Full article

Background/Objectives: As part of China’s efforts to build a high-quality and efficient integrated healthcare delivery system, tightly knit urban medical groups (TKUMGs) have emerged as a key model for promoting inter-institutional collaboration. While existing studies have focused on organizational outcomes, limited empirical evidence is available regarding the personal benefits experienced by healthcare professionals within TKUMGs. Methods: This study evaluated 2200 healthcare professionals’ perceived benefits from TKUMG participation in six pilot medical groups across two Chinese cities to identify factors associated with variations in career development outcomes. Results: Three distinct latent classes were identified: (1) A Limited Growth Group (32.4%), with minimal improvement across all dimensions; (2) a Skill Recognition Group (35.6%), with improvements in recognition and expertise utilization but limited gains in compensation and promotion; and (3) a Comprehensive Growth Group (32.0%), with comprehensive improvements in all six areas. Higher levels of participation and more positive attitudes toward TKUMG construction were significantly associated with inclusion in the more advanced development groups. Other significant factors included age, educational attainment, institutional role (leading vs. member), and departmental affiliation. TKUMG construction has generated heterogeneous benefits for healthcare professionals. Active engagement and institutional environments play critical roles in shaping individual development trajectories. Conclusions: Despite limitations related to this study’s cross-sectional design and self-reported data, these findings offer valuable insights for policymakers aiming to design incentive mechanisms, optimize human resource allocation, and enhance the sustainability of integrated healthcare models in urban China. Full article

Background: Rheumatoid arthritis (RA) is a chronic autoimmune disease that substantially impairs health-related quality of life (HRQoL). Comorbid mental health conditions, particularly depression and anxiety, may further exacerbate this burden, yet evidence from large, population-based studies remains limited. Therefore, this study examined the association between comorbid depression and anxiety and HRQoL among adults with RA using nationally representative data from the United States. Methods: Data were drawn from the 2017–2022 Medical Expenditure Panel Survey. Adults aged ≥18 years with self-reported RA were included. HRQoL was assessed using the Veterans RAND 12-Item Health Survey (VR-12) physical (PCS) and mental (MCS) component summary scores. Multiple linear regression models were used to evaluate associations between depression, anxiety, and HRQoL, adjusting for sociodemographic, behavioral, and health-related covariates. Results: Comorbid depression and anxiety were significantly associated with lower HRQoL scores compared with RA alone. Participants with both conditions exhibited the poorest PCS and MCS scores, indicating a disease burden. Lower income, unemployment, and limited physical activity were also linked to poorer HRQoL, whereas better self-rated health and physical activity were positive predictors. Conclusions: Depression and anxiety independently and jointly contribute to poorer HRQoL among adults with RA, even after controlling for key confounders. These findings highlight the importance of integrated care models that address both psychological and physical health, alongside interventions promoting physical activity to enhance overall well-being. Full article

Medical image segmentation, driven by the intrinsic fractal characteristics of biological patterns, plays a crucial role in medical image analysis. Recently, universal image segmentation, which aims to build models that generalize robustly to unseen anatomical structures and imaging modalities, has emerged as a promising research direction. To achieve this, previous solutions typically follow the in-context learning (ICL) framework, leveraging segmentation priors from a few labeled in-context references to improve prediction performance on out-of-distribution samples. However, these ICL-based methods often overlook the quality of the in-context set and struggle with capturing intricate anatomical details, thus limiting their segmentation accuracy. To address these issues, we propose VG-SAM, which employs a multi-scale in-context retrieval phase and a visual in-context guided segmentation phase. Specifically, inspired by the hierarchical and self-similar properties in fractal structures, we introduce a multi-level feature similarity strategy to select in-context samples that closely match the query image, thereby ensuring the quality of the in-context samples. In the segmentation phase, we propose to generate multi-granularity visual prompts based on the high-quality priors from the selected in-context set. Following this, these visual prompts, along with the semantic guidance signal derived from the in-context set, are seamlessly integrated into an adaptive fusion module, which effectively guides the Segment Anything Model (SAM) with powerful segmentation capabilities to achieve accurate predictions on out-of-distribution query images. Extensive experiments across multiple datasets demonstrate the effectiveness and superiority of our VG-SAM over the state-of-the-art (SOTA) methods. Notably, under the challenging one-shot reference setting, our VG-SAM surpasses SOTA methods by an average of $6.61\%$ in DSC across all datasets. Full article

Electrochemiluminescence (ECL) is a chemiluminescence phenomenon triggered by electrochemical reactions at the electrode surface, which has gradually become a high-sensitivity detection technology due to its low background, simple instrumentation, and high sensitivity. Therein, potential-resolved ECL refers to the generation of two or more ECL signals with distinct potentials and wavelengths during an electrochemical process. This unique capability enables simultaneous multi-signal outputs, making potential-resolved ECL particularly promising for self-calibration and multiplexed detection strategies. In this review, we focus on two critical aspects: on the one hand, the advancement of traditional ECL luminophores and potential-resolved ECL systems was reviewed, which were classified, respectively, into three categories to be introduced in detail (inorganic, organic and nanomaterial-based ECL luminophores or potential-resolved ECL of metal–organic complexes, layer-by-layer-modified electrodes, and nanomaterials). On the other hand, we summarized ECL detection strategies based on potential-resolved ECL systems and the application of these protocols in disease biomarker detection, which results in two categories (self-calibration strategies and multi-target strategies) for discussion. In this work, we aim to inspire investigators to explore novel ECL luminophores and design detection strategies with high performance, which could provide strong support for precision medicine, personalized assessment, portable medical devices, and the digital transformation of healthcare. Full article

Worldwide less than half of adults with hypertension are diagnosed and treated (only 42%), in addition one in five adults with hypertension (21%) has the condition under control. In the American continent, cardiovascular diseases (CVD) are the leading cause of death and high blood pressure (hypertension) is responsible for 50% of CVD deaths. Only a few countries show a population hypertension control rate of more than 50%. In this experimental study, we trained 15 regression-type machine learning algorithms, including traditional and ensemble methods to assess their effectiveness in estimating arterial pressure using noninvasive photoplethysmographic (PPG) signals extracted from 110 study subjects, to identify the risk of hypertension and its correlation with arteriosclerosis. We analyzed the performance of each algorithm using the metrics MSE, MAE, RMSE, and r². A 10-fold cross-validation showed that the best algorithms for hypertension risk identification were LR, KNN, SVR, RF, LR Baggin, KNNBagging, SVRBagging, and DTBagging. On the other hand, the best algorithms for arterioclesrosis risk identification were LR, KNN, SVR, RF, LR Bagging, and DTBagging. These results suggest that this research is promising and offers valuable information on the acquisition and processing of PPG signals. However, as this is an experimental study, the effectiveness of our model needs to be validated with a larger database. On the other hand, this model represents a support tool for healthcare specialists in the early detection of cardiovascular health, allowing people to self-manage their health and seek medical attention at an early stage. Full article

Objectives: Pelvic organ prolapse (POP) disorders are a significant problem with a society-wide dimension, affecting the quality of life of many women around the world. The purpose of this study is to assess the influence of sociodemographic factors on health-preserving behaviors in relation to pelvic organ prolapse in women of reproductive age. Method: The survey was conducted using a questionnaire made available electronically and a paper questionnaire distributed to female patients of the Gynecology and Obstetrics Clinical Hospital of the Karol Marcinkowski Medical University in Poznan. In total, 160 women aged 15–49 years voluntarily participated in the study. The distribution of variables was assessed using the Shapiro–Wilk test. The Mann–Whitney U and Kruskal–Wallis ANOVA tests were used for comparisons between groups. Comparisons between assessment scores and self-assessment of knowledge were made using Wilcoxon’s paired rank order test and the Chi2 NW (highest reliability) test. A p-value < 0.05 was considered statistically significant. Results: The level of knowledge about POP prevention and conservative treatment methods is low. The group with a higher level of knowledge was characterized by younger age, higher education, and living in areas with a large population. Conclusions: The results suggest only a partial understanding of the topic of pelvic organ prolapse, while lacking full awareness of prevention. Full article