Search Results (14,933)

Influenza is typically framed as an acute respiratory infection, yet accumulating evidence suggests that—like SARS-CoV-2—it may trigger persistent, multi-organ morbidity consistent with a post-acute infection syndrome (“long flu”). Leveraging the nationwide FinnGen registry infrastructure, we conducted a temporally stratified disease-wide association study (DWAS) to map antecedent risk factors and long-term sequelae following clinically diagnosed influenza and COVID-19. We assembled an exposed cohort comprising 9204 individuals with influenza (ICD-10 J09–J11) and 4,258 individuals with COVID-19 (ICD-10 U072) recorded in specialist inpatient/outpatient care between 1998 and 2021, and an unexposed comparator cohort of 420,005 individuals with no recorded influenza or pneumonia (J09–J18) across their available medical history. Across harmonized clinical endpoints, we fitted age- and sex-adjusted Cox proportional hazards models and controlled for multiple testing using a stringent false discovery rate threshold (FDR-adjusted p<0.001), further interrogating temporal persistence within 1-, 5-, and 15-year windows. The DWAS revealed that both infections are associated with broad, system-spanning disease signatures extending beyond the respiratory tract, including circulatory, neurological, metabolic, musculoskeletal, digestive, mental/behavioural, ocular, and oncologic endpoints. Predisposition analyses demonstrated that infection risk is concentrated in individuals with substantial pre-existing multimorbidity, most prominently cardiovascular disease, alongside cardiometabolic, respiratory, renal, neuropsychiatric, and inflammatory conditions. Post-infection analyses identified a durable burden of incident multi-system morbidity after influenza, with particularly robust and persistent cardiovascular and neurological signatures—encompassing thromboembolic disease and major adverse cardiovascular outcomes, as well as migraine, neurodegenerative disorders, and depression—together with metabolic and renal sequelae that, in subsets, extended across multi-year horizons. Collectively, these longitudinal findings reframe influenza as a systemic event embedded within a chronic disease continuum, motivate recognition of “long flu” as a clinically meaningful post-viral risk landscape, and support intensified prevention and risk-stratified surveillance strategies alongside analogous efforts for long COVID. Full article

Background/Objectives: Insulin resistance (IR) is a relevant metabolic concern in patients with rheumatic diseases; however, data regarding its clinical influence on the systemic sclerosis (SSc) phenotype is lacking. This study aimed to evaluate the characteristics of patients exhibiting IR in a monocentric SSc cohort. Methods: We conducted a cross-sectional study on 178 SSc patients, stratified according to the presence of IR, defined as a HOMA-IR value >1.85 for men and >2.07 for women, based on thresholds previously validated in the Estudio Epidemiológico de la Insuficiencia Renal en España (EPIRCE) cross-sectional study. The rationale for applying the current cut-offs is based on its discriminative potential when using sex- and age-specific thresholds in a nondiabetic population. This approach is particularly applicable to SSc, where the prevalence of diabetes is very low and the median ages of the two cohorts are comparable. Data collected included demographic-, clinical-, laboratory-, pulmonary function-, capillaroscopic-, and treatment-related parameters. A multivariable logistic regression model was used to identify independent predictors of IR. Results: Patients with IR (n = 76) had a significantly higher prevalence of diffuse cutaneous subset (26.3% vs. 11.8%, p = 0.012) and interstitial lung disease (39.5% vs. 17.6%, p = 0.001), along with the positivity for anti-Scl70 antibodies and the current presence of musculoskeletal symptoms (p = 0.021) and digital ulcers (p = 0.037). As expected, body mass index (BMI) was significantly higher in the IR population (24.6 ± 5.2 vs. 22.9 ± 4.1, p = 0.012), along with fasting glucose, insulin, HOMA-IR, and HbA1c levels. IR patients exhibited higher percentages of dyslipidemia and liver steatosis. Medications such as hydroxychloroquine, statins, and Iloprost were more frequently used in the IR group; as for corticosteroids usage (21.1% vs. 5.9%, p = 0.002), however, cumulative glucocorticoid dosage did not differ between the groups. In multivariable analysis, BMI (OR 1.09; p = 0.038) and interstitial lung disease (ILD) (OR 3.03; p = 0.034) were independent predictors of IR. Conclusions: In SSc, IR is associated with ILD, digital ulcers, musculoskeletal involvement, and anti-Scl70 autoantibodies. Full article

Despite the increasing number of older Syrian refugees in Canada, little is known about how they manage their health care needs while contending with language barriers, cultural dissonance, and systemic inequities. This qualitative study explored how older Syrian refugees in the Greater Toronto Area (GTA) navigate healthcare across Canadian and transnational contexts. The study was guided by the transnational circulation of care framework and used an interpretive descriptive design. Following research ethics approval, 20 older Syrian refugees were interviewed by bilingual research assistants. In-depth individual interviews were conducted in Arabic and analyzed using reflexive thematic analysis. Four interrelated themes emerged: (1) Navigating a New System; (2) Living in Two Worlds; (3) Medication Portability, Herbal Practices, and Supplement Culture; and (4) Digital Health Across Borders. Findings demonstrate that older Syrian refugees actively construct hybrid care pathways that integrate biomedical, cultural, and transnational practices. These strategies reflect resilience and adaptability but also expose gaps in the healthcare system. The study underscores the need for culturally responsive and age-friendly healthcare practices that acknowledge transnational realities. By illuminating how care circulates across borders, this study provides actionable guidance for designing responsive health systems. Full article

Background and Objectives: This study aimed to comparatively evaluate the association of commonly used comorbidity scores with survival, mortality, and recurrence in ovarian cancer patients aged 50 years and above. Materials and Methods: In this single-center, retrospective study, 130 female patients diagnosed between 2017 and 2024 who had received systemic therapy and had complete medical records were included. Comorbidity scores—including the Charlson Comorbidity Index (CCI), Cumulative Illness Rating Scale-Geriatric (CIRS-G), Adult Comorbidity Evaluation-27 (ACE-27), Elixhauser Comorbidity Index, Index of Coexistent Disease (ICED), and Functional Comorbidity Index (FCI)—were calculated for each patient. Survival analyses were conducted using the Kaplan–Meier method and Cox regression modeling. The prognostic accuracy of comorbidity scores was assessed via receiver operating characteristic (ROC) curve analysis. Results: Patients with higher CCI scores had significantly shorter survival, and CCI was identified as an independent prognostic factor in multivariate analysis. While other comorbidity scores were associated with overall survival in univariate analyses, they lost statistical significance in multivariate models. Patients with a higher comorbidity burden experienced more frequent disease recurrence and shorter time to recurrence. Conclusions: Comorbidity burden is a key clinical determinant of survival and disease trajectory in older patients with ovarian cancer. The CCI demonstrated the highest prognostic accuracy in this population and may serve as a valuable tool in individualized treatment planning. Integration of comorbidity-based assessments into standard decision-making processes is recommended in geriatric oncology practice. Full article

Chloride, the leading extracellular anion, plays a crucial role in acid-base balance, fluid homeostasis, and neuromuscular function. Despite historical underrecognition, emerging evidence demonstrates significant associations between chloremia disturbances and critical care outcomes. This paper aims to narratively review the pathophysiology, clinical features, and management strategies of chloremia disturbances in critically ill patients. Chloremia disturbances are common in ICU patients, with both hypochloremia (<96 mEq/L) and hyperchloremia (>106 mEq/L) independently associated with increased mortality, prolonged ICU length of stay, and organ dysfunction. In sepsis, chloride levels exhibit a prognostic value, with threshold effects around 105 mEq/L. Hyperchloremia particularly increases acute kidney injury risk, while hypochloremia correlates with prolonged mechanical ventilation. The choice of resuscitation fluids significantly influences clinical outcomes, with balanced crystalloids potentially reducing adverse events if compared to normal saline solutions. Recent large-scale trials demonstrate lower rates of major adverse kidney events with chloride-restrictive strategies. Optimal management requires careful patient monitoring along with acid-base assessment. Treatment approaches must identify underlying causes to avoid complications. Prevention strategies include protocol-based fluid therapy, medication selection consideration, and early intervention in high-risk patients. Emerging technologies, including continuous monitoring systems and machine learning algorithms, offer promising advances for predicting and managing chloride disturbances. Full article

Audiovestibular disorders arising from the inner ear (e.g., hearing loss, tinnitus, vertigo) are widely prevalent in the United States. Yet, medical treatments targeting the underlying pathology of these disorders remain scarce. The practice of repurposing FDA-approved drugs for new therapeutic indications has become increasingly common, offering a lower risk route to treatment development with fewer barriers to implementation, as safety profiles are already established. The renin–angiotensin system (RAS) is well known for its role in blood pressure and fluid balance, and its overactivation induces acute and chronic inflammation and oxidative stress. This review discusses existing evidence and proposed otoprotective mechanisms of RAS inhibition, specifically using angiotensin II type 1 receptor blockers (ARBs), which support the repurposing of these medications as novel treatments to affect the inner ear pathologies that underlay hearing loss, tinnitus, and vertigo. Full article

The 2S LGBTQIA+ (Two-Spirit, Lesbian, Gay, Bisexual, Trans, Queer and/or Questioning, Intersex, Asexual, and additional sexually and gender-diverse self-identities) population often faces barriers to care in the context of cervical cancer screening. With the shift from primary cervical cytology (Papanicolaou test) to primary human papillomavirus (HPV)-DNA testing, it is crucial to examine these populations’ healthcare needs. An intersectionality framework with an anti-oppressive lens is needed to restructure a healthcare system whose systems have traditionally erased the care needs of diverse populations through colonial, racialized, and cis-heteronormative practices. Barriers to cervical screening in 2S LGBTQIA+ populations include stigma, discrimination, limited provider guidance and understanding, and high rates of physical, sexual, and medical trauma. Self-sampling for HPV is a less invasive alternative to traditional Pap tests with a high rate of acceptability. The option to self-sample may increase participation in cervical screening based on improved privacy, comfort, and feelings of empowerment. Organizational, psychosocial, and physical recommendations for practice are shared to create a welcoming environment that reflects the diversity of populations in all aspects of healthcare. Affirmative care aims to make clients feel safe and accommodated by prioritizing dignity and respect as essential elements of eliminating cervical cancer in 2S LGBTQIA+ populations. Full article

In order to solve the dynamic analysis and interactive imaging control problems in the deformation process of bionic soft lenses, dielectric elastomer (DE) actuators are separated from a convex lens, and data-driven eye-controlled motion technology is investigated. According to the DE properties, which are consistent with the deformation characteristics of hydrogel electrodes, the motion and deformation effect of eye-controlled lenses under film prestretching, lens size, and driving voltage, is studied. The results show that when the driving voltage increases to 7.8 kV, the focal length of the lens, whose prestretching λ is 4, and the diameter d is 1 cm, varies in the range of 49.7 mm and 112.5 mm. And the maximum focal-length change could reach 58.9%. In the process of eye controlling design and experimental verification, a high DC voltage supply was programmed, and eye movement signals for controlling the lens were analyzed by MATLAB software (R2023b). Eye-controlled interactive real-time motion and tunable imaging of the lens were realized. The response efficiency of soft lenses could reach over 93%. The adaptive lens system developed in this research has the potential to be applied to medical rehabilitation, exploration, augmented reality (AR), and virtual reality (VR) in the future. Full article

Background: Large language models (LLMs) are increasingly integrated into clinical documentation, decision support, and patient-facing applications across healthcare, including plastic and reconstructive surgery. Yet, their evaluation remains bottlenecked by costly, time-consuming human review. This has given rise to LLM-as-a-judge, in which LLMs are used to evaluate the outputs of other AI systems. Methods: This review examines LLM-as-a-judge in healthcare with particular attention to judging architectures, validation strategies, and emerging applications. A narrative review of the literature was conducted, synthesizing LLM judge methodologies as well as judging paradigms, including those applied to clinical documentation, medical question-answering systems, and clinical conversation assessment. Results: Across tasks, LLM judges align most closely with clinicians on objective criteria (e.g., factuality, grammaticality, internal consistency), benefit from structured evaluation and chain-of-thought prompting, and can approach or exceed inter-clinician agreement, but remain limited for subjective or affective judgments and by dataset quality and task specificity. Conclusions: The literature indicates that LLM judges can enable efficient, standardized evaluation in controlled settings; however, their appropriate role remains supportive rather than substitutive, and their performance may not generalize to complex plastic surgery environments. Their safe use depends on rigorous human oversight and explicit governance structures. Full article

Background and Objectives: Payment parity laws require commercial health plans to pay for telehealth on the same basis as in-person care. We systematically reviewed open-access empirical studies to identify and synthesize empirical U.S. studies that explicitly evaluated state telehealth payment parity (distinct from coverage-only parity) and to summarize reported effects on telehealth utilization, modality mix, quality/adherence, equity/access, and expenditures. Methods: Following PRISMA 2020, we searched PubMed/MEDLINE, Scopus, and Web of Science for U.S. studies that explicitly modeled state payment parity or stratified results by payment parity vs. coverage-only vs. no parity. We included original quantitative or qualitative studies with a time or geographic comparator and free full-text availability. The primary outcome was telehealth utilization (share or odds of telehealth use); secondary outcomes were modality mix, quality and adherence, equity and access, and spending. Because designs were heterogeneous (interrupted time series [ITS], difference-in-differences [DiD], regression, qualitative), we used structured narrative synthesis. Results: Nine studies met inclusion criteria. In community health centers (CHCs), payment parity was associated with higher telehealth use (42% of visits in parity states vs. 29% without; Δ = +13.0 percentage points; adjusted odds ratio 1.74, 95% CI 1.49–2.03). Among patients with newly diagnosed cancer, adjusted telehealth rates were 23.3% in coverage + payment parity states vs. 19.1% in states without parity, while cross-state practice limits reduced telehealth use (14.9% vs. 17.8%). At the health-system level, parity mandates were linked to a +2.5-percentage-point telemedicine share in 2023, with mental-health (29%) and substance use disorder (SUD) care (21%) showing the highest telemedicine shares. A Medicaid coverage policy bundle increased live-video use by 6.0 points and the proportion “always able to access needed care” by 11.1 points. For hypertension, payment parity improved medication adherence, whereas early emergency department and hospital adoption studies found null associations. Direct spending evidence from open-access sources remained sparse. Conclusions: Across ambulatory settings—especially behavioral health and chronic disease management—state payment parity laws are consistently associated with modest but meaningful increases in telehealth use and some improvements in adherence and perceived access. Effects vary by specialty and are attenuated where cross-state practice limits persist, and the impact of payment parity on overall spending remains understudied. Full article

Individuals across their lifespan may experience hearing loss from medications or chemicals, prompting concern about ototoxic environmental exposures. This study applies computational modeling as a screening-level hazard identification and chemical prioritization approach and is not intended to constitute a human health risk assessment or to estimate exposure- or dose-dependent ototoxic risk. We evaluated in silico drug-induced ototoxicity models on 80 environmental chemicals, excluding 4 with known ototoxicity, and analyzed 76 chemicals using fingerprinting, similarity assessment, and machine learning classification. We compared predicted environmental ototoxicants with ototoxic drugs, paired select polychlorinated biphenyls with the antineoplastic drug mitotane, and used PCB 177 as a case study to construct an ototoxicity pathway. A systems biology framework predicted and compared molecular targets of mitotane and PCB 177 to generate a network-level mechanism. The consensus model (accuracy 0.95 test; 0.90 validation) identified 18 of 76 chemicals as potential ototoxicants within acceptable confidence ranges. Mitotane and PCB 177 were both predicted to disrupt thyroid-stimulating hormone receptor signaling, suggesting thyroid-mediated pathways may contribute to auditory harm; additional targets included AhR, transthyretin, and PXR. Findings indicate overlapping mechanisms involving metabolic, cellular, and inflammatory processes. This work shows that integrated computational modeling can support virtual screening and prioritization for chemical and drug ototoxicity risk assessment. Full article

Background/Objectives: Understanding the biological factors that drive the behavior and clinical presentation of breast cancer (BC) skeletal metastases (SM) is critical for improving diagnostic accuracy and guiding treatment strategies. However, evidence regarding the immunohistochemical (IHC) profiles of SM and their association with radiographic characteristics and clinical features remains limited. This study aimed to evaluate the relationship between estrogen receptor (ER), progesterone receptor (PR), HER2 receptor status, and Ki-67 proliferation index with the radiographic presentation of SM in patients with BC. Methods: A total of 185 SM samples from individual BC patients were analyzed. IHC expressions of ER, PR, HER2, and Ki-67 were determined for each sample. Clinical and radiological data were retrieved from medical records. IHC profiles were compared between metastases demonstrating purely lytic versus mixed radiographic patterns. Results: Of the 185 cases, 66 exhibited a lytic pattern, and 119 demonstrated a mixed pattern. Lytic metastases showed a significantly higher rate of HER2 positivity compared with mixed lesions. The Ki-67 index was also significantly higher in lytic metastases, with a cutoff value of 25 yielding a sensitivity of 92.98% and specificity of 89.84% (positive likelihood ratio 9.16; negative likelihood ratio 0.08). No significant differences were observed between groups in ER or PR expression. Conclusions: SM from BC with a lytic radiographic presentation are more likely to exhibit HER2 positivity and a Ki-67 index above 25. Assessing the IHC status of SM may help identify patients at elevated risk for skeletal complications, including pathological fracture, and may support more tailored surgical and systemic treatment planning. Full article

Chronic obstructive pulmonary disease (COPD) is a major health burden worldwide and in Taiwan, ranking as the third leading cause of death globally, and its prevalence in Taiwan continues to rise. Readmission within 14 days is a key indicator of disease instability and care efficiency, driven jointly by patient-level physiological vulnerability (such as reduced lung function and multiple comorbidities) and healthcare system-level deficiencies in transitional care. To mitigate the growing burden and improve quality of care, it is urgently necessary to develop an AI-based prediction model for 14-day readmission. Such a model could enable early identification of high-risk patients and trigger multidisciplinary interventions, such as pulmonary rehabilitation and remote monitoring, to effectively reduce avoidable early readmissions. However, medical data are commonly characterized by severe class imbalance, which limits the ability of conventional machine learning methods to identify minority-class cases. In this study, we used real-world clinical data from multiple hospitals in Kaohsiung City to construct a prediction framework that integrates data generation and ensemble learning to forecast readmission risk among patients with chronic obstructive pulmonary disease (COPD). CTGAN and kernel density estimation (KDE) were employed to augment the minority class, and the impact of these two generation approaches on model performance was compared across different augmentation ratios. We adopted a stacking architecture composed of six base models as the core framework and conducted systematic comparisons against the baseline models XGBoost, AdaBoost, Random Forest, and LightGBM across multiple recall thresholds, different feature configurations, and alternative data generation strategies. Overall, the results show that, under high-recall targets, KDE combined with stacking achieves the most stable and superior overall performance relative to the baseline models. We further performed ablation experiments by sequentially removing each base model to evaluate and analyze its contribution. The results indicate that removing KNN yields the greatest negative impact on the stacking classifier, particularly under high-recall settings where the declines in precision and F1-score are most pronounced, suggesting that KNN is most sensitive to the distributional changes introduced by KDE-generated data. This configuration simultaneously improves precision, F1-score, and specificity, and is therefore adopted as the final recommended model setting in this study. Full article

Background/Objectives: Long COVID (LC) is associated with more than 200 symptoms. This study aimed to evaluate the correlation between symptoms clusters and pharmacological treatment in patients with LC and to explore differences by sex. Methods: We conducted a cross-sectional descriptive study including 304 participants diagnosed with LC according to the World Health Organization criteria. Symptoms during the acute phase, at the time of diagnosis of LC, and those persisting across both phases were collected by anamnesis. Symptoms were grouped into six clusters: systemic, neurocognitive, respiratory/cardiovascular, musculoskeletal, neurological/neuromuscular, and psychological/psychiatric. Drug use was assessed through a questionnaire verified by the medical records, including the consumption of cardiovascular drugs, antidepressants/anxiolytics, and anti-inflammatory/analgesics. Results: Patients reported a mean of 5.23 ± 1.10 symptoms in the acute phase, 4.20 ± 1.70 at LC diagnosis, and 3.83 ± 1.80 persisting across both phases. The most consumed pharmacological group was cardiovascular drugs (43.3%), followed by antidepressants/anxiolytics (34.8%). Psychotropic drugs and anti-inflammatory/analgesic drugs showed a positive association with all symptomatic groups (p < 0.05). Cardiovascular drugs showed a positive association with cardiorespiratory (β = 0.19, p < 0.05), neuromuscular (β = 0.11, p < 0.05), and psychological (β = 0.14, p < 0.05) symptoms. Conclusions: Psychotropic and anti-inflammatory/analgesic drugs were positively associated with all symptom clusters, while cardiovascular drugs were associated only with cardiorespiratory, neuromuscular, and psychological symptoms, highlighting the relevance of better characterization of treatment patterns in this population. Full article

As new technologies, such as electronic medical records (EMRs), are introduced into healthcare services, we need to consider how they may be incorporated into simulated environments, so as to maintain and enhance authenticity and learning opportunities. While EMRs have revolutionised clinical practice, many education settings continue to rely on paper-based documentation in simulation, creating a widening gap between educational environments and real-world clinical workflows. This disconnect limits learners’ ability to engage authentically with the tools and resources that underpin contemporary healthcare, impeding the transfer of knowledge to the clinical environment. This practice-based commentary draws on institutional experience from a large, multi-disciplinary simulation-based education facility that explored approaches to integrating EMRs into simulation-based education. It describes the decision points and efforts made to integrate an EMR into simulation-based education and concludes that while genuine EMR systems increase fidelity, their technical rigidity and data governance constraints reduce authenticity. To overcome this, Adelaide Health Simulation adopted an academic EMR (AEMR), a purpose-built digital platform designed for education. The AEMR maintains the functional realism of clinical systems while offering the pedagogical flexibility required to control data, timelines, and learner interactions. Drawing on this experience, this commentary highlights how authenticity in simulation-based education is best achieved not through technological replication alone, but through deliberate use of technologies that align with clinical realities while supporting flexible, learner-centred design. Purpose-built AEMRs exemplify how digital tools can enhance both fidelity and authenticity, fostering higher-order thinking, clinical reasoning, and digital fluency essential for safe and effective contemporary healthcare practice. Here, we argue that advancing simulation-based education in parallel with health service innovations is required if we want to adequately prepare learners for contemporary clinical practice. Full article