Search Results (869)

Background: The COVID-19 pandemic profoundly disrupted healthcare systems worldwide, compelling rapid adaptation of clinical workflows and accelerating the integration of telemedicine. Objective: This study evaluates the implementation of telemedicine in neurosurgical outpatient care at a tertiary referral hospital in Madrid during the first epidemic wave (March–May 2020) and explores its long-term significance five years later. Methods: A retrospective observational analysis including 5175 neurosurgical outpatient consultations was conducted, comparing the first epidemic wave of COVID-19 (2070 teleconsultations) with the equivalent period in 2019 (3105 in-person visits). Demographic, clinical, and procedural data were analyzed, including six-month follow-up outcomes. Univariate and multivariate analyses were performed to identify factors associated with teleconsultation use and follow-up delay. Results: The total number of consultations decreased by 33% compared to the pre-pandemic year. In May 2020, teleconsultations represented more than 70% of all visits. Continuity of care was preserved (follow-up adherence >80%), and missed appointments declined to zero. Cranial and oncological pathologies were prioritized, while degenerative and benign cases were largely deferred. Teleconsultation independently predicted delayed six-month follow-up (aOR 1.9, 95% CI 1.3–2.8, p = 0.002) and a lower likelihood of surgical indication (aOR 0.4, 95% CI 0.2–0.7, p = 0.004). Despite these differences, remote care ensured accessibility, safety, and clinical continuity under extreme healthcare system strain. Five years perspective: In addition to these early outcomes, the study describes the sustained integration of telemedicine during the subsequent five years, illustrating how this model became permanently embedded in routine neurosurgical practice in this center. Conclusions: This study represents one of the earliest structured telemedicine experiences in Spanish neurosurgery. The rapid adaptation of the Hospital General Universitario Gregorio Marañón ensured care continuity during the pandemic and catalyzed the lasting adoption of hybrid models that enhance accessibility, safety, efficiency, and healthcare system resilience. Full article

Bacteremia is a life-threatening condition contributing significantly to sepsis-related mortality worldwide. With delayed appropriate antibiotic therapy, mortality increases by 20% regardless of antimicrobial resistance. This study evaluated the perceived clinical utility of Artificial Intelligence (AI)-powered Clinical Decision Support Systems (CDSSs) (OneChoice and OneChoice Fusion) among specialist physicians managing bacteremia cases. A cross-sectional survey was conducted with 65 unique specialist physicians from multiple medical specialties who were presented with clinical vignettes describing patients with bacteremia and 90 corresponding AI-CDSS recommendations. Participants assessed the perceived helpfulness of AI decision-making, the impact of AI recommendations on their own clinical judgment, and the concordance between AI recommendations and their own clinical judgment, as well as the validity of changing therapy based on CDSS recommendations. The study encompassed a diverse range of bacterial pathogens, with Escherichia coli representing 38.7% of the isolates and 30% being extended-spectrum β-lactamase (ESBL) producers. Findings show that 97.8% [(95% CI: 92.2–99.7%)] of physicians reported that AI facilitated decision-making and substantial concordance (87.8% [95% CI: 79.2–93.7%; Cohen’s κ = 0.76]) between AI recommendations and physicians’ therapeutic recommendations. Stratification by pathogen revealed the highest concordance for Escherichia coli bacteremia (96.6%, 28/29 cases). Implementation analysis revealed a meaningful clinical impact, with 68.9% [(95% CI: 58.3–78.2%)] of cases resulting in AI-guided treatment modifications. These findings indicate that AI-powered CDSSs effectively bridge critical gaps in infectious disease expertise and antimicrobial stewardship, providing clinicians with evidence-based therapeutic recommendations that can be integrated into routine practice to optimize antibiotic selection, particularly in settings with limited access to infectious disease specialists. For optimal clinical integration, we recommend that clinicians utilize AI-CDSS recommendations as an adjunct to clinical judgment rather than a replacement, particularly in complex cases involving immunocompromised hosts or polymicrobial infections. Future research should prioritize prospective clinical trials that evaluate direct patient outcomes to establish evidence of broader clinical effectiveness and applicability across diverse healthcare settings. Full article

Early diagnosis and rapid treatment of respiratory abnormalities such as many lung diseases including pneumonia, TB, cancer, and other pulmonary problems depend on accurate and fast classification of chest X-ray images. Delayed diagnosis and insufficient treatment lead to the subjective, labour-intensive, error-prone features of current manual diagnosis systems. To tackle this pressing healthcare issue, this work investigates many deep convolutional neural network (CNN) architectures including VGG16, VGG19, ResNet50, InceptionV3, Xception, DenseNet121, NASNetMobile, and NASNet Large. LungVisionNet (LVNet) is an innovative hybrid model proposed here that combines MobileNetV2 with multilayer perceptron (MLP) layers in a unique way. LungVisionNet outperformed previous models in accuracy 96.91%, recall 97.59%, precision, specificity, F1-score 97.01%, and area under the curve (AUC) measurements according to thorough examination on two publicly available datasets including various chest abnormalities and normal cases exhibited. Comprehensive evaluation with an independent, real-world clinical dataset from King Hussein Cancer Centre (KHCC), which achieved 95.3% accuracy, 95.3% precision, 78.8% recall, 99.1% specificity, and 86.4% F1-score, confirmed the model’s robustness, generalizability, and clinical usefulness. We also created a simple mobile application that lets doctors quickly classify and evaluate chest X-ray images in hospitals, so enhancing clinical integration and practical application and supporting fast decision-making and better patient outcomes. Full article

Background/Objectives: Transportation is a critical social determinant of health with direct impacts on healthcare access and utilization. This study examines transportation challenges faced by low-income individuals with chronic conditions who participated in the Food as Medicine (FAM) program offered by their primary care provider and explores the strategies they employ to overcome those challenges, particularly during the COVID-19 pandemic. Methods: We conducted semi-structured interviews with 36 FAM participants from Grady Health System in Atlanta, Georgia between May 2022 and October 2023. Interviews explored their ability to access routine care, FAM, and healthy food as prescribed by their physicians and nutritionists, as well as how the COVID-19 pandemic affected their transportation challenges and solutions. Results: Participants reported various transportation barriers including long wait times, delays, cost burdens, unreliable services, and coordination failures, which contributed to missing doctor appointments and FAM attendance. To overcome those challenges, participants planned trips in advance, used multiple transportation options, relied on social networks, or reduced and sometimes forwent trips. The COVID-19 pandemic limited their accessibility to healthcare, FAM, and healthy food options by reducing business hours and disrupting transportation services. Alternatives such as telemedicine and online ordering were less utilized due to distrust, dissatisfaction, and limited digital literacy. Conclusions: Transportation barriers can substantially restrict healthcare and food access for low-income individuals managing chronic conditions, especially during public crises that may lead to service disruptions. Transportation assistance that accommodates individuals’ financial circumstances and health conditions, implemented through collaborative efforts of healthcare institutions, transportation agencies, and governments, is essential to facilitating chronic disease management and reducing health disparities. Full article

Background/Objectives: Heart Failure (HF) remains a leading cause of hospitalization and mortality worldwide, representing a significant burden on patients and healthcare systems. Despite advances in pharmacological and device-based therapies, readmission rates remain high and traditional monitoring approaches often fail to detect early physiological deterioration. This review examines the clinical utility and implementation challenges of remote hemodynamic monitoring in HF, highlighting its role in improving patient outcomes and guiding precision care. Method: A comprehensive narrative review was conducted using PubMed, Scopus, and Web of Science databases to identify peer-reviewed English-language studies published in the past ten years. Results: Monitoring hemodynamic status is essential for preventing HF readmissions, as elevated filling pressures often precede symptoms. Previous studies suggest that traditional methods may be less effective in detecting early changes, which could contribute to delays in initiating treatment. Remote monitoring offers continuous, individualized assessment and has shown potential to reduce hospitalizations, though its effectiveness varies across populations and settings. Telemonitoring primarily targets patients at higher risk of hospitalization, such as those classified as New York Heart Association(NYHA) class III and individuals with comorbidities that exacerbate HF. Remote hemodynamic monitoring presents notable clinical advantages, although its widespread adoption faces several challenges (i.e., the invasiveness of some monitoring systems; limited patient adherence due to technical complexity or cognitive and physical barriers; difficulties associated with comorbidities; variability in the efficacy of monitoring strategies across populations; difficulties faced by healthcare teams in managing and interpreting large volumes of real-time data; cost-effectiveness issues related to devices and infrastructure costs). Addressing these limitations will be essential to fully understanding the potential of remote monitoring in HF care. Conclusions: Remote hemodynamic monitoring enables early detection of physiological deterioration in HF, allowing timely interventions that reduce hospitalizations and improve outcomes. Emerging evidence suggests that, in contrast to traditional approaches, this method has the potential to support more personalized, data-driven care. Integrating biopsychosocial, gender, and intersectional perspectives further aligns this strategy with precision medicine, enhancing its effectiveness and equity in clinical practice. Despite promising recent advances, further research is essential to broaden the scientific evidence base and to enhance support for clinical decision-making. Full article

Background/Objectives: Conventional imaging assesses therapy response in stage IV solid-tumor patients in 8- to 12-week intervals, delaying detection of non-responders. We evaluated a quantitative PCR (qPCR) assay that interrogates size-distributed cell-free DNA (cfDNA) fragments to provide earlier insights into treatment efficacy. Methods: In this prospective study, 128 patients with metastatic lung, breast, or colorectal cancer provided plasma 12–21 days after the first dose of a new systemic regimen. The qPCR targets multi-copy retrotransposon element fragments of greater than 80 bp, greater than 105 bp, and greater than 265 bp, as well as an internal control. A model integrates these quantities into a Progression Score (PS) ranging from 0 to 100; higher values indicate probable disease progression. Results: The PS model yielded an area under (AUC) the receiver-operating-characteristic (ROC) curve of 0.93 for predicting radiographic progression at first imaging. Scores were strongly bimodal: 92% of patients with PS > 90 progressed, whereas 95% with PS < 10 did not. Intermediate scores (10–90) comprised a mixed cohort. Assay performance was unaffected by tumor genomic profile. Conclusions: This cfDNA-based Progression Score (PS) assay enables tumor- and therapy-agnostic, non-invasive monitoring of treatment response as early as two weeks after initiation. By flagging ineffective regimens well before standard imaging, the test can accelerate clinical decision-making, reduce exposure to futile therapy, and potentially improve outcomes in stage IV cancer. Early treatment plan changes may also avoid the high costs of ineffective treatments, prevent downstream toxicity-related hospitalizations, and free up limited imaging and infusion-suite capacity—yielding savings for patients, payers, and healthcare systems. Full article

Introduction: Chronic wounds are a growing healthcare challenge, with infections being major complications that delay healing. Biofilms are structured microbial communities encased in extracellular polymeric substances. Biofilms confer antimicrobial resistance, promote inflammation, and protect pathogens from host defenses. These mechanisms make eradication difficult with standard therapies. Methods: A focused literature review was conducted using PubMed (2010–2025) to examine the role of biofilms in chronic wounds, diabetic foot ulcers (DFUs), and burn injuries, as well as conventional and emerging treatment strategies. Studies are included if they addressed microbial composition, host–microbe interactions, or therapeutic outcomes in clinical or translational models. Discussion: Biofilms are implicated in up to 60% of chronic wounds and more than half of burn wounds. In DFUs, both bacterial and fungal biofilms contribute to chronicity and impaired healing. Conventional treatments such as debridement and antiseptics reduce surface biofilm burden but rarely achieve full eradication. Emerging approaches include quorum sensing inhibitors, bacteriophage therapy, matrix-degrading enzymes, electroceutical dressings, antifungal strategies, and nanotechnology. They show promise when integrated with standard wound care. Conclusions: Biofilms are central to the pathogenesis of chronic wounds, DFUs, and burns. Integrating mechanism-based antibiofilm therapies with standard care represents a key research priority to improve healing outcomes. Full article

Invasive candidiasis (IC) is a life-threatening fungal infection predominantly affecting critically ill patients in intensive care units (ICUs). Despite advances in antifungal therapies, IC remains a diagnostic and therapeutic challenge, with a mortality rate exceeding 40%. The current reliance on blood cultures as the diagnostic gold standard is limited by low sensitivity and prolonged turnaround times, often delaying effective treatment. This often leads to the overuse of empirical antifungal therapies, increasing resistance, healthcare costs, and inconsistent outcomes. To address these issues, this paper introduces a five-step diagnostic strategy developed by an expert panel to optimise IC diagnosis and management. The strategy integrates predictive risk scores, biomarkers, and antifungal susceptibility testing to streamline diagnosis, identify high-risk patients, and promote antifungal stewardship. It also addresses barriers such as resource disparities and variability in clinical practices, offering a practical, standardised strategy for ICUs in the UK and Ireland. The clinical utility of this approach is highlighted through two patient cases. One describes the safe discontinuation of antifungal therapy after a negative (1,3)-β-D-glucan (BDG) assay ruled out IC, reducing unnecessary treatment and adverse effects. The other showcases the use of rapid in-house antifungal susceptibility testing to precisely tailor therapy for a patient with Nakaseomyces glabratus, ensuring effective treatment and preventing resistance. This pragmatic five-step guide simplifies and standardises IC diagnosis, aiming to lower mortality, optimise therapies, and promote judicious antifungal use. Full article

Background/Objectives: Cancer remains a major public health concern in India, with the Northeast Region (NER) reporting the country’s highest incidence rates. In Meghalaya, a predominantly tribal state, cultural beliefs, financial hardship, and limited healthcare access significantly affect cancer diagnosis and treatment outcomes. This study explores the experiences and needs of cancer patients in Meghalaya, India, to inform culturally sensitive, patient-centred, and financially inclusive approaches to cancer care among tribal populations. Methods: A qualitative study was conducted among 19 participants (12 patients and 7 caregivers; in cases where patients were unable to communicate effectively due to physical weakness or treatment-related complications, their primary caregivers, those directly linked to the specific patients, were interviewed instead) receiving treatment at Civil Hospital, Shillong, between August and November 2023. In-depth interviews were conducted in Khasi, translated into English, and analysed thematically following COREQ guidelines. Results: Ten key themes emerged. Patients often attributed early symptoms to supernatural causes and sought traditional healers, delaying diagnosis. Many experienced fragmented care pathways, misinformation, and fear of treatment side effects. The financial burden was severe, with high out-of-pocket costs for travel, diagnostics, and medicines, despite partial relief through the Meghalaya Health Insurance Scheme. Communication about costs between patients and providers was limited, leaving families unprepared for the expenses. Emotional distress, loss of livelihood, and dependence on family support were common, while faith and spirituality served as major coping mechanisms. Conclusions: Cancer care in Meghalaya is shaped by intertwined cultural, economic, and systemic barriers. Strengthening culturally tailored health education, decentralised diagnostic services, structured financial counselling, and cost transparency can improve care delivery. Future research should adopt multi-centre, longitudinal approaches to guide equitable, patient-centred cancer policies in tribal and rural settings. Full article

Background: Chronic skin ulcers are characterized by an impaired and delayed wound healing process, posing a major economic and healthcare burden. These multifactorial conditions are influenced by both biological, clinical and psychosocial factors. The aim of our cross-sectional study was to investigate the influence of psychosocial and lifestyle factors—specifically adherence to the Mediterranean diet, emotional health, sleep quality and demographic characteristics—on physical symptoms and clinical severity in patients with skin ulcers, using a multidisciplinary approach to identify key predictors of disease burden. Methods: A cross-sectional analysis was conducted on patients with skin ulcers, using data from a monocentric pathology registry. Collected variables included gender, age, dietary habits (specifically, adherence to the Mediterranean diet), sleep disturbances, educational level, anxiety and depressive symptoms, Physician Global Assessment (PGA), Patient Global Assessment (PtGA), and Skindex-17 (a dermatology-specific quality of life measure). Hierarchic multivariate linear regression models were applied to identify predictors of physical symptoms and clinical severity, while simultaneously controlling for potential confounders. Results: Older age, poorer adherence to the Mediterranean diet, and elevated anxiety levels emerged as the strongest predictors of worse physical symptoms, as measured by the Skindex-17. Male sex and more severe depressive symptoms were significantly associated with higher PGA scores. Our data also suggest older age and poorer Mediterranean diet adherence to influence clinical severity. Lastly, sleep disturbances were also found to correlate with patient-reported severity. Conclusions: Our study underscores the impact of psychosocial and behavioral/lifestyle factors on the clinical burden of skin ulcers through a comprehensive multidisciplinary approach. In particular, our data indicate that dietary patterns and emotional health appear to shape both symptom perception and clinical evaluation, emphasizing the need for holistic management strategies. Full article

Caregivers of a child with a serious medical condition are often confronted with difficult and stressful medical information. While they commonly seek out health-related information to better care for their child and help with their decision-making, sometimes caregivers engage in healthcare information avoidance. Healthcare information avoidance is the decision to prevent or delay the acquisition of available, but potentially unwanted, health-related information. We begin by defining the construct of healthcare information avoidance and exploring key theoretical frameworks that illuminate its underlying mechanisms including emotion regulation theory, attentional and cognitive models, approach-avoidance coping strategies, and dispositional theories. A lack of validated measures to assess caregiver healthcare information avoidance was noted as contributing to the dearth of empirical work in this area. Common areas of caregiver healthcare information avoidance were identified at various points throughout the pediatric palliative care illness trajectory. The review concludes with directions for future research and practical recommendations for clinical care, highlighting the importance of identifying the occurrence and reasons for caregiver information avoidance as well as optimizing approaches to information provision. Full article

Background/Objectives: Menopause, marked by permanent cessation of menstruation, is a universal transition associated with vasomotor, genitourinary, psychological, and metabolic changes. These conditions significantly affect health-related quality of life (HRQoL) and increase the risk of chronic diseases. Despite their impact, timely diagnosis and individualized management are often limited by delayed care, fragmented health systems, and cultural barriers. Methods: This review summarizes current applications of artificial intelligence (AI) in postmenopausal health, focusing on risk prediction, early detection, and personalized treatment. Evidence was compiled from studies using biomarkers, imaging, wearable sensors, electronic health records, natural language processing, and digital health platforms. Results: AI enhances disease prediction and diagnosis, including improved accuracy in breast cancer and osteoporosis screening through imaging analysis, and cardiovascular risk stratification via machine learning models. Wearable devices and natural language processing enable real-time monitoring of underreported symptoms such as hot flushes and mood disorders. Digital technologies further support individualized interventions, including lifestyle modification and optimized medication regimens. By improving access to telemedicine and reducing bias, AI also has the potential to narrow healthcare disparities. Conclusions: AI can transform postmenopausal care from reactive to proactive, offering personalized strategies that improve outcomes and quality of life. However, challenges remain, including algorithmic bias, data privacy, and clinical implementation. Ethical frameworks and interdisciplinary collaboration among clinicians, data scientists, and policymakers are essential for safe and equitable adoption. Full article

Background/Objectives: Diabetic foot infections (DFIs) are a leading cause of hospitalization, amputation, and costs among patients with diabetes. Although early treatment is assumed to reduce complications, its real-world effects remain uncertain. We applied a causal machine-learning (ML) approach to investigate whether early DFI treatment improves hospitalization and clinical outcomes. Methods: We conducted an observational study using de-identified UCSF electronic health record (EHR) data from 1434 adults with DFI (2015–2024). Early treatment (<3 days after diagnosis) was compared to delayed/no treatment (≥3 days or none). Outcomes included DFI-related hospitalization and lower-extremity amputation (LEA). Confounders included demographics, comorbidities, antidiabetic medication use, and laboratory values. We applied Targeted Maximum Likelihood Estimation (TMLE) with SuperLearner, a machine-learning ensemble. Results: Early treatment was associated with higher hospitalization risk (TMLE risk difference [RD]: 0.293; 95% CI: 0.220–0.367), reflecting the triage of clinically sicker patients. In contrast, early treatment showed a protective trend against amputation (TMLE RD: −0.040; 95% CI: −0.098 to 0.066). Results were consistent across estimation methods and robust to bootstrap validation. A major limitation is that many patients likely received treatment outside UCSF, introducing uncertainty around exposure classification. Conclusions: Early treatment of DFIs increased hospitalization but reduced amputation risk, a paradox reflecting appropriate clinical triage and systematic exposure misclassification from fragmented healthcare records. Providers prioritize the sickest patients for early intervention, leading to greater short-term utilization but potentially preventing irreversible complications. These findings highlight a cautionary tale; even with causal ML, single-institution analyses may misrepresent treatment effects, underscoring the need for causally informed decision support and unified EHR data. Full article

Background and Clinical Significance: Hell’s Itch is a rare, intensely uncomfortable post-sunburn condition with burning pruritus emerging 24–72 h after UV exposure. This condition often goes unrecognized and is frequently misdiagnosed by healthcare providers due to a lack of knowledge and familiarity. Standard antipruritic measures are often ineffective, and patients frequently rely on anecdotal self-management. Case Presentation: Three healthy adult males between 23 and 28 years old experienced multiple episodes of delayed-onset intense pruritus following moderate-to-severe sun exposure. The patients experienced a burning or stinging pain which they described as “fire ants” or “thumbtacks,“ and their symptoms started between 24 and 72 h after sun exposure without any rash or fever symptoms. The patients did not achieve symptom relief from standard treatments which included oral antihistamines and topical lidocaine, NSAIDs, aloe vera, and cold compresses. The patients received β-alanine treatment through pre-workout supplements or pure powder after consulting non-clinical sources. Each patient ingested β-alanine and reported rapid relief (itch 8–10/10 → 1–2/10) lasting 2–3 h. The only adverse effect reported by one patient was mild paresthesia. Conclusions: This case introduces β-alanine as a potential off-label therapy for Hell’s Itch and emphasizes the psychological burden and clinical complexity of the condition. While anecdotal, further study is needed to elucidate the mechanism of action of β-alanine in relieving symptoms of Hell’s Itch, as well as assess safety and efficacy in controlled settings. Increased clinical awareness of Hell’s Itch may reduce patient distress and improve management strategies. Full article

This narrative review examines the Comprehensive Geriatric Assessment (CGA), a multidisciplinary approach used to evaluate and manage the health of older adults. CGA has been shown to improve functional status, reduce hospital readmissions, delay institutionalization, and lower mortality. Despite these benefits, systematic implementation remains limited. Major barriers include shortages in the workforce and resources, a lack of standardized protocols, and insufficient training in geriatric competencies. These challenges leave many older adults with unmet healthcare needs, particularly in chronic disease management, functional limitations, mental health, and social support. Nurses are well positioned to address these gaps because of their expertise in patient-centered care, care coordination, and chronic disease management. Strengthening geriatric nursing education and integrating CGA into routine nursing practice can improve outcomes for the aging population. Although CGA is often associated with hospital settings, its future lies in broader application. Digital solutions scheduled health assessments, workforce planning, and community- or home-based evaluations can make CGA more accessible. Policymakers, healthcare systems, and educational institutions must work together to develop policies that embed CGA within primary healthcare. Full article