Search Results (13,937)

Background. Rheumatoid arthritis (RA) is a chronic autoimmune disease frequently accompanied by cardiovascular, respiratory, skeletal, psychiatric, and neoplastic comorbidities that are associated with higher morbidity and poorer health-related quality of life (HRQoL). This study evaluated the associations between comorbidities and patient-reported physical health, emotional distress, daily functioning, and social relationships in adults with RA and explored patient-reported unmet needs relevant to integrated care. Methods. We conducted a cross-sectional survey among 286 adults with physician-confirmed RA, using a structured questionnaire (ICRA-Q) administered between June and July 2025 via online platforms and in-hospital supervised completion. The survey captured demographics, patient-reported physician-diagnosed comorbidities (current and/or past), perceived disease impact, functional limitations, emotional and social consequences, access to treatment, financial burden, and support needs. Analyses included descriptive statistics, χ² tests, t-tests/ANOVA, effect sizes (Cramer’s V and standardized mean differences), and multivariable logistic regression to explore predictors of high HRQoL impact and high difficulty in disease management. An exploratory classification into high-risk phenotypes was performed using predefined clinical, psychological, and socioeconomic criteria. Results. Most participants (98.6%) reported at least one comorbidity, most commonly hypertension, osteoporosis, and cardiovascular disease. Higher comorbidity burden and depression/anxiety were strongly associated with higher pain, reduced mobility, emotional distress, and financial strain. Exploratory high-risk phenotypes (severe somatic multimorbidity, high psychological vulnerability, high socioeconomic burden, and a composite very high-risk profile) were associated with poorer HRQoL indicators. Younger age, shorter disease duration, and higher perceived social support were associated with lower perceived burden. Conclusions. In this cross-sectional, patient-reported study, comorbidity burden—particularly psychological comorbidity—was strongly associated with poorer HRQoL and greater management difficulty in RA. These findings support the need for multidisciplinary, integrated care pathways; however, subgroup phenotypes should be considered exploratory and require external validation. Full article

Background: Locally advanced rectal cancer is traditionally managed with neoadjuvant chemoradiotherapy followed by total mesorectal excision, but radical surgery entails substantial morbidity, including bowel, urinary, and sexual dysfunction as well as permanent stomas. Organ-preserving strategies such as total neoadjuvant therapy (TNT) followed by a watch-and-wait (WW) approach aim to reduce morbidity while maintaining oncologic safety. A recent study from the FOREST cohort confirmed favorable survival outcomes with WW but did not assess the patient-centered impact. Methods: This retrospective observational study included locally advanced rectal cancer patients treated at a tertiary hospital. Following TNT, patients who achieved a complete clinical response entered WW, while others underwent radical surgery (RS). Patient-reported outcomes were assessed using an 18-item questionnaire grouped into domains and transformed to a 0–100 scale according to EORTC scoring methodology. All patients underwent a shared decision-making process. Comparisons between groups used Pearson chi-square tests for clinical and demographics associations and Mann–Whitney U tests for ordinal outcomes. The protocol was integrated into Quirónsalud’s value-based healthcare framework. Results: Clinical and demographics characteristics did not differ between WW and RS groups. PROMs favored WW in multiple domains: Symptoms/Complications (87 vs. 66; p < 0.001), Psychosocial adaptation (90 vs. 66; p < 0.001), Mental health (90 vs. 78; p = 0.006), and Global quality of life (80 vs. 67; p = 0.011). Bowel and sexual functions were similar between groups, and Care satisfaction was very high for both. Conclusions: TNT plus WW appears to be oncologically safe and confers significant quality-of-life benefits across several domains. These findings support the theory that WW is a value-based, patient-centered strategy for rectal cancer, and this warrants validation in larger, randomized cohorts. Full article

Non-communicable diseases (NCDs) impose an overwhelming burden on global health systems. Prevailing healthcare for NCDs remains largely hospital-centered, episodic, and reactive, rendering them poorly suited to address the long-term, heterogeneous, and multifactorial nature of NCDs. Rapid advances in digital technologies, artificial intelligence (AI), and precision medicine have catalyzed the development of an integrative framework for digital-intelligent precision health management, characterized by the functional integration of data, models, and decision support. It is best understood as an integrated health management framework operating across three interdependent dimensions. First, it is grounded in multidimensional health-related phenotyping, enabled by continuous digital sensing, wearable and ambient devices, and multi-omics profiling, which together allow for comprehensive, longitudinal characterization of individual health states in real-world settings. Second, it leverages intelligent risk warning and early diagnosis, whereby multimodal data are fused using advanced machine learning algorithms to generate dynamic risk prediction, detect early pathological deviations, and refine disease stratification beyond conventional static models. Third, it culminates in health management under intelligent decision-making, integrating digital twins and AI health agents to support personalized intervention planning, virtual simulation, adaptive optimization, and closed-loop management across the disease continuum. Framed in this way, digital-intelligent precision health management enables a fundamental shift from passive care towards proactive, anticipatory, and individual-centered health management. This Perspectives article synthesizes recent literature from the past three years, critically examines translational and ethical challenges, and outlines future directions for embedding this framework within population health and healthcare systems. Full article

Background/Objectives: Acute health events in institutionalized older adults often lead to avoidable hospital referrals, requiring rapid, accurate remote decision-making. Telemedicine has become a key tool to improve assessment and care continuity in nursing homes. This study aimed to evaluate outcomes associated with telemedicine-supported management of acute events in residential care facilities for older adults and to develop a deep learning model to classify episodes and predict hospital referrals. Methods: A quasi-experimental study analyzed 5202 acute events managed via a 24/7 telemedicine system in Vitalia nursing homes (January–October 2024). The dataset included demographics, comorbidities, vital signs, event characteristics, and outcomes. Data preprocessing involved imputation, normalization, encoding, and dimensionality reduction via Truncated SVD (200 components). Given the imbalance in referral outcomes (~10%), several resampling techniques (SMOTE, SMOTEENN, SMOTETomek) were applied. A deep feedforward neural network (256–128–64 units with Batch Normalization, LeakyReLU, Dropout, AdamW) was trained using stratified splits (70/10/20) and optimized via cross-validation. Results: Telemedicine enabled the resolution of approximately 90% of acute events within the residential setting, reducing reliance on emergency services. The deep learning model outperformed traditional algorithms, achieving its best performance with SMOTEENN preprocessing (AUC = 0.91, accuracy = 0.88). The proposed model achieved higher overall performance than baseline classifiers, providing a more balanced precision–specificity trade-off for hospital referral prediction, with an F1-score of 0.63. Conclusions: Telemedicine-enabled acute care, strengthened by a robust deep learning classifier, offers a reliable strategy to enhance triage accuracy, reduce unnecessary transfers, and optimize clinical decision-making in nursing homes. These findings support the integration of AI-assisted telemedicine systems into long-term care workflows. Full article

Introduction: Timely access to healthcare is essential for improving population health and reducing inequities. Immigrants often experience unique cultural, linguistic, and systemic barriers that delay care-seeking and service utilization. Despite the rapid growth of the Nepalese community in Canada, there is limited empirical evidence examining their healthcare access. This study aimed to assess the prevalence and determinants of delays in accessing healthcare among Nepalese immigrants. Methods: A community-based participatory research (CBPR) framework guided a cross-sectional survey conducted between January and June 2019. The research process was co-led by academic investigators, community scholars, and local Nepalese organizations to ensure cultural and contextual relevance. A snowball sampling strategy was used to recruit 401 Nepalese adults. Data were analyzed using descriptive statistics and multivariable logistic regression to examine sociodemographic and health-related factors associated with delayed healthcare access. Results: Of the 401 respondents, 66.3% (n = 266) reported experiencing a delay in accessing healthcare within the preceding 12 months. Delays were more common among participants aged 26–45 years, those who were married, employed, or had an undergraduate degree or lower. After adjusting for covariates, older age, lower education, having a family doctor, higher income (≥$26,000), and one or more chronic conditions were associated with increased odds of delay. Family size and the number of years living in Canada have had little effect on care delay. Conclusions: Delays in accessing healthcare are common among Nepalese immigrants in Calgary, reflecting the intersection of individual, cultural, and systemic determinants. These findings underscore the importance of community-engaged, culturally responsive strategies to address barriers and promote equitable healthcare access for immigrant populations. Strengthening partnerships between health systems and immigrant communities may enhance trust, navigation, and continuity of care. Full article

Background/Objectives: The long-term impact of intubation during infancy or early childhood on later childhood or adolescence remains unclear. This study investigates the association between early-life intubation and subsequent mental health outcomes. Methods: We conducted a retrospective cohort study using nationwide data on children born in Korea between 2002 and 2005. Those who underwent intubation (exposed cohort) were compared with 1:10 matched unexposed controls who did not undergo intubation. Results: The exposed cohort (n = 18,799) had a significantly higher incidence rate of mental health disorders than controls (28.2 vs. 13.9 per 1000 person-years; HR 1.82, 95% CI 1.74–1.93). Autism spectrum disorder (HR 3.09) and attention-deficit/hyperactivity disorder (HR 1.61) increased in early childhood, while bipolar disorders (HR 2.36), schizophrenia spectrum disorders (HR 2.27), depressive disorders (HR 1.94) and anxiety disorders (HR 1.84) increased in adolescence. Higher incidence was noted in females, children not admitted to intensive care units, and those without congenital heart disease or bronchopulmonary dysplasia (p < 0.05). Hospitalization length correlated with mental health outcomes (p < 0.001), but ventilator duration did not (p = 0.694). Conclusions: Early-life intubation is associated with an increased risk of mental health disorders, highlighting the need for long-term follow-up and support for these children. In particular, increased clinical awareness is needed during follow-up care for patients at higher risk, such as females, children without congenital heart disease or bronchopulmonary dysplasia, those intubated at an older age, and those with longer hospitalizations. Full article

One of the challenges post-COVID-19 is reducing the negative impacts on quality of life, performance, and independence in activities of daily living. Assessing functional dependence in adults one year after acute infection can help to understand the long-term consequences, evaluate the impact on quality of life, plan rehabilitation and healthcare, identify the most vulnerable groups, measure the socioeconomic impact, and support public policies and clinical decisions. Objectives: The objectives of this study are as follows: (a) to assess the prevalence of functional dependence in Brazilian adults with COVID-19; (b) to analyze the association between the study variables; and (c) to determine the factors associated with functional dependence. Methods: This was an observational, cross-sectional study with 987 adults (18 to 59 years old) living in the State of Paraná (Brazil) hospitalized for COVID-19 between March and December 2020. Data were collected by telephone 12 months after the acute infection using an instrument to retrieve sociodemographic and health information, and a functional dependence scale to assess dependence before COVID-19 retrospectively (using participant recall information) and at the time of the interview. Data were analyzed using penalized logistic regression after imputing missing data. Data were analyzed using penalized logistic regression after imputing missing data. Results: Functional dependence after COVID-19 was 5.0% and was associated with low levels of education, not having a partner, living with someone, not owning a home, experiencing job changes, requiring care, obesity, smoking, multimorbidity, ICU admission in the acute phase, use of invasive ventilation, or having Long COVID. Individuals who required care or used invasive ventilation support were, respectively, 9.3 and 6.5 times more likely to develop dependence after COVID-19. Despite adjustment for multiple factors, the magnitude of the observed effects warrants cautious interpretation, as unmeasured or residual confounding effects may still be present. Sample recall bias due to collection after 12 months and the presence of the alpha variant without COVID-19 vaccination coverage may limit data generalization. Conclusions: The results highlight the need to emphasize the public health implications of identifying functional dependence. In this vein, it is necessary to implement preventive measures, identify and monitor more vulnerable groups, plan rehabilitation programs, and develop public health policies. Full article

Background/Objectives: Self-care is central to chronic illness management and is particularly relevant in osteoporosis to prevent complications and improve quality of life. Grounded in Riegel’s middle-range theory of self-care of chronic illness, the study sought to understand the contextual, emotional, and structural influences shaping self-care in people living with osteoporosis. Aim: The aim of this study was to explore patient-reported barriers and facilitators to self-care behaviors among individuals living with osteoporosis. Methods: A qualitative descriptive design was conducted using in-depth, semi-structured interviews with 20 patients with osteoporosis recruited via convenience sampling. Data were coded deductively and analyzed using Mayring’s qualitative content analysis with a deductive approach. Results: Participants identified several factors related to both barriers and facilitators of self-care behaviors. Four barrier sub-themes emerged: ineffective coping strategies, difficulties in osteoporosis management, inadequate physical activity, and ineffective self-efficacy. Six facilitator sub-themes were identified: self-care management strategies, osteoporosis management after a fracture, osteoporosis control, osteoporosis treatment, exercise, and confidence in one’s ability. Main barriers included fear of falling, ineffective self-efficacy, and poor care continuity, whereas key facilitators included support networks, motivation, and tailored care. Conclusions: Self-care behaviors in individuals with osteoporosis are influenced by emotional, contextual, and structural factors. Person-centered interventions integrating emotional and educational components may strengthen patients’ engagement and enhance self-care behaviors in osteoporosis. Identifying barriers and facilitators enables nurses to design empathetic, tailored strategies that enhance empowerment and disease management. Understanding these factors can improve autonomy for patients and adherence, promoting long-term health outcomes across clinical and community settings. Full article

Both obesity and chronic kidney disease (CKD) are increasingly recognized as global epidemics. Their escalating incidence and far-reaching health implications highlight the urgent need for comprehensive prevention and management strategies. This review aims to clarify how obesity interacts with end-stage kidney disease (ESKD) and how to improve the management of obese patients receiving kidney replacement therapy. It also explores underlying mechanisms, current treatments, future directions, and ongoing controversies. By highlighting this intricate relationship, the review seeks to enhance clinical practice and promote further research toward more personalized care for this vulnerable population. Obesity is frequent in dialysis patients and creates challenges related to body composition, metabolism, and treatment. While higher body mass index (BMI) may appear to improve survival, this paradox does not offset the cardiovascular and functional risks of visceral and sarcopenic obesity. Obesity also increases post-transplant complications and can limit access to transplantation. Lifestyle changes rarely achieve lasting weight loss, whereas bariatric surgery—especially sleeve gastrectomy—can improve transplant eligibility with fewer complications. Weight-loss medications may be used before transplantation but remain insufficiently studied in ESKD. After transplantation, weight-reduction efforts should continue, with pharmacotherapy preferred over bariatric surgery. Comprehensive assessment strategies and individualized management approaches in ESKD patients are essential to optimize outcomes in this growing patient population. Full article

Background/Objectives: The COVID-19 pandemic disproportionately impacted rural areas across the United States, including rural North Carolina (NC). Consistent with national patterns, COVID-19 vaccination coverage as of December 2022 was higher for non-rural (72%) than rural (58%) NC counties. The role of trusted sources of vaccine information used by rural and non-rural residents is unknown. Methods: Using data from two surveys distributed by the COVID-19 Community Research Partnership from 8 June 2021 through 21 December 2021, we compared self-reported sources of trusted COVID-19 vaccine information by non-rural and rural counties and by county-level predominant political vote in the 2020 Presidential election. Results: While NC respondents were highly vaccinated (94%), fewer residents from rural counties self-reported COVID-19 vaccination than those from non-rural counties (91% versus 95%). The most common reported source of trusted vaccine information was federal health agencies. The proportion citing a federal health agency was higher for respondents from non-rural (80%) than rural (72%) counties and was higher for vaccinated (75%) than unvaccinated (42%) rural respondents. The next two most trusted sources of vaccine information were state/local health officials (48%) and health care providers (42%). Among trusted resources reported by 10–15% of respondents, those from rural counties were less likely to use hospital websites, employers, or news sources than those from non-rural counties. More respondents from counties with >60% vote for the 2020 Democratic Presidential candidate cited federal health agencies, state and local officials, and new sources than respondents from counties with >60% vote for the 2020 Republican Presidential candidate. Conclusions: By identifying the trusted sources of vaccine information for residents in non-rural and rural NC counties, future vaccine implementation efforts can tailor communication efforts to increase vaccine uptake and potentially reduce the rates of hospitalizations and death from vaccine-preventable diseases such as COVID-19 or other future pandemics. Full article

Ageing is a dynamic biological process involving interconnected physiological, psychological, and social changes, making the promotion of healthy ageing a global public health priority. The World Health Organization (WHO) defines healthy ageing as the process of developing and maintaining functional ability that enables well-being in older age. The WHO’s Decade of Healthy Aging (2021–2030) outlines four key action areas: changing attitudes toward ageing, creating age-friendly environments, delivering integrated and person-centred care, and ensuring access to long-term care. This Perspective examines yoga, a holistic mind–body practice integrating physical postures, breath regulation, and mindfulness, as a potentially safe, adaptable, and scalable intervention for older adults. Evidence suggests that yoga may improve flexibility, balance, mobility, and cardiovascular function, reduce pain, and support the management of chronic conditions commonly associated with ageing. Psychological and cognitive research further indicates reductions in stress, anxiety, and depressive symptoms, alongside potential benefits for attention, memory, and executive function. Improvements in health-related quality of life (HRQoL) have been reported across physical, psychological, and social domains, with benefits sustained through regular practice. Adaptations such as chair-based practices, restorative postures, and the use of props enhance accessibility and safety, allowing participation across diverse functional levels. Mindfulness and breath-focused components of yoga may additionally support emotional regulation, resilience, and psychological well-being, particularly among older adults experiencing stress or limited mobility. Yoga interventions are generally well tolerated, demonstrate high adherence, and can be delivered through in-person and digital formats, addressing common access barriers. Despite this growing evidence base, yoga remains underintegrated within health policy and care systems in the US, UK, and India. Strengthening its role may require coordinated efforts across research, policy, and implementation to support healthy ageing outcomes. Full article

Introduction: The health care burden of chronic hepatis B virus (CHB) infection can be reduced by appropriate workup, treatment, and monitoring. Methods: As a primary objective, we determined whether adequate initial hepatitis B virus (HBV) laboratory workup in CHB patients is associated with improved CHB complications risk. Secondary outcomes assessed included: mortality, hospitalization, emergency department, and liver specialist visits. We conducted a retrospective cohort study from 1 January 2012 to 31 December 2018. Participants were followed from 12 months post index event until outcome occurrence, death, loss of eligibility, or 31 March 2023. Health administrative data from Ontario, Canada was utilized. The study cohort included individuals with at least one positive result of either hepatitis B surface antigen, hepatitis B e antigen, or HBV DNA viral load documented during the study window. The exposure of interest was defined as adequate laboratory workup, defined as having subsequent quantitative HBV DNA, and alanine aminotransferase testing completed within 12 months of the index event. CHB-related complications were assessed using previously validated diagnostic codes. Modified Poisson regression modelling was used to estimate relative risks. Results: The study cohort consisted of 30,794 CHB patients, with a mean age 45.7 years. The majority were male (53.5%) and within the lowest two income quintiles (50.2%). In total, 68.0% underwent adequate workup. Individuals with adequate workup were more likely to be older, male, urban based, and of the highest racialized and newcomer populations quintile. The risk for CHB complications was 1.50 (95% CI 1.36–1.65) times greater among those with adequate workup. By multivariable analysis, adequate workup was associated with a lower risk of mortality (RR 0.78; 95% CI 0.69–0.87), all-cause hospitalizations (RR 0.77; 95% CI 0.74–0.80), all-cause (RR 0.77; 95% CI 0.75–0.78), and liver-related (RR 0.67; 95% CI 0.60–0.75) ED visits. Conclusions: Adequate CHB clinical workup is associated with improved patient outcomes. Our findings advocate for the comprehensive evaluation of CHB patients using key laboratory tests to optimize clinical management and improve long-term health outcomes. We identified gaps in the workup of young adults, females, and those residing in rural settings, which should be addressed to ensure equity of HBV care. Full article

Aesthetic Medicine is advanced as an integrated, evidence-based framework for patient-centered care that unites physical, psychological, social, and aesthetic dimensions of health. Drawing on Clinical Health Psychology, the paper introduces Aesthetic Health Psychology as a specialization that embeds psychological theory, assessment, and intervention within aesthetic medicine and surgery, emphasizing interdisciplinary collaboration rather than professional mistrust. The paper argues that integrating Aesthetic Health Psychology into aesthetic medicine can enhance ethical practice, improve patient-reported outcomes, and support equity-focused implementation across diverse procedures and settings. It further suggests a practical framework for implementation. Three interrelated models are proposed: the Aesthetic Biopsychosocial Model, which conceptualizes aesthetics as a distinct health domain alongside biological, psychological, and social factors; the Aesthetic Health Care Process Model, which structures care as a five-stage journey supported by systematic screening for body dysmorphic disorder and the routine use of patient-reported outcome measures; and the Aesthetic Health Systems Model, which situates aesthetic care within institutional, policy, and cultural contexts. Idealized but clinically grounded vignettes from elective cosmetic, reconstructive, and gender-affirming settings illustrate how these models address non-linear trajectories of adaptation, evolving expectations, complications, and stigma. These concepts jointly define both the motivation for Aesthetic Health Psychology and its practical implications, from the use of brief, selective aesthetic screening during primary health care visits to the design of equity-focused implementation strategies across aesthetic procedures and settings. Full article

Brain tumors, encompassing subtypes with distinct progression and risk profiles, are a serious public health concern. Magnetic resonance imaging (MRI) is the primary imaging modality for non-invasive assessment, providing the contrast and detail necessary for diagnosis, subtype classification, and individualized care planning. In this paper, we evaluate the capability of modern deep learning models to classify gliomas as high-grade (HGG) or low-grade (LGG) using reduced training data from MRI scans. Utilizing the BraTS 2019 best-slice dataset (2185 images in two classes, HGG and LGG) divided in two folders, training and testing, with different images obtained from different patients, we created subsets including 10%, 25%, 50%, 75%, and 100% of the dataset. Six deep learning architectures, DeiT3_base_patch16_224, Inception_v4, Xception41, ConvNextV2_tiny, swin_tiny_patch4_window7_224, and EfficientNet_B0, were evaluated utilizing three-fold cross-validation (k = 3) and increasingly large training datasets. Explainability was assessed using Grad-CAM. With 25% of the training data, DeiT3_base_patch16_224 achieved an accuracy of 99.401% and an F1-Score of 99.403%. Under the same conditions, Inception_v4 achieved an accuracy of 99.212% and a F1-Score of 99.222%. Considering how the models performed across both data subsets and their compute demands, Inception_v4 struck the best balance for MRI-based glioma classification. Both convolutional networks and vision transformers achieved superior discrimination between HGGs and LGGs, even under data-limited conditions. Architectural disparities became increasingly apparent as training data diminished, highlighting unique inductive biases and efficiency characteristics. Even with a relatively limited amount of training data, current deep learning (DL) methods can achieve reliable performance in classifying gliomas from MRI scans. Among the architectures evaluated, Inception_v4 offered the most consistent balance between accuracy, F1-Score, and computational cost, making it a strong candidate for integration into MRI-based clinical workflows. Full article

Background/Objectives: Blood thinners (anticoagulants) remain the first line pharmacotherapy for the management of cardiovascular and thromboembolic disorders. The increased utilization of polypharmacy, likely driven by the greater burden of comorbidities, elevates the risk of potential drug–drug interactions (pDDIs) and creates a significant challenge in anticoagulant management. The aim of the study was to assess the prescribing trend and impact of polypharmacy and pDDIs in patients receiving anticoagulant drug therapy in a public hospital providing secondary care. Methods: A cross-sectional observational study was undertaken between January–June 2023. Data from electronic medical records of prescriptions for anticoagulants were collected, analyzed for prescribing patterns, and checked for pDDIs using Micromedex database 2.0^®. Utilizing binary logistic regression, the relationship between polypharmacy and sociodemographic factors was assessed. Multivariate logistic regression analysis served to uncover determinants linked to pDDIs. Results: Of the total 130 patients, females were predominant (58.46%), with a higher prevalence among those aged 61–90 years. Atrial fibrillation emerged as the main clinical reason and apixaban (51.53%) ranked as the top prescribed anticoagulant in our cohort. Among the 766 pDDIs identified, the majority [401 (52.34%)] were categorized as moderate in severity. Polypharmacy was strongly linked to age (p = 0.001), the Charlson comorbidity index (CCI) (p = 0.040), and comorbidities (p = 0.005) in the binary logistic regression analysis. In the multivariable analysis, the number of medications remain a strong predictor of pDDIs (adjusted OR: 30.514, p = 0.001). Conclusions: Polypharmacy and pDDIs were exhibited in a significant segment of cohort receiving anticoagulant therapy, with strong correlations to age, CCI, comorbidities, and the number of medications. A multidimensional approach involving collaboration among healthcare providers assisted by clinical decision support systems can help optimize the management of polypharmacy, minimize the risks of pDDIs, and ultimately enhance health outcomes. Full article