Search Results (23,568)

Background and Objective: Colorectal cancer (CRC) most commonly metastasizes to the liver and lungs; however, synchronous metastases to pelvic structures such as the vagina and urethra are extremely rare, posing a significant diagnostic and therapeutic challenge. This report describes an unusual case of sigmoid colon adenocarcinoma with synchronous metastases to the vagina and urethra, highlighting its diagnostic evaluation and the value of a multidisciplinary approach. Methods: A 59-year-old woman with a history of deep vein thrombosis treated with apixaban presented with chronic constipation and pelvic bleeding. A gynecological evaluation revealed a vaginal lesion. A colonoscopy, biopsy, pelvic magnetic resonance imaging, and molecular profiling were performed. Treatment included chemotherapy (capecitabine and oxaliplatin), panitumumab, and pelvic radiotherapy. Results: The biopsy confirmed a moderately differentiated invasive adenocarcinoma in the sigmoid colon with synchronous metastases to the vagina and urethra. Molecular profiling identified a rat sarcoma virus oncogene and BRAF (B-Raf proto-oncogene), allowing for the use of targeted therapy. The patient achieved a complete response according to RECIST 1.1 criteria and significant symptomatic improvement, including pain reduction, although dosages were adjusted for thrombocytopenia. She is currently continuing palliative treatment with good tolerance and durable symptomatic improvement. Conclusions: This case underscores the need to consider unusual metastatic sites in patients with colorectal cancer presenting with gynecological symptoms. Early diagnosis, based on imaging and histology, alongside molecular characterization, is crucial for effective personalized therapy. Multidisciplinary coordination is key to optimizing clinical outcomes in these rare metastatic presentations. Full article

Background and Clinical Significance: Membranoproliferative glomerulonephritis (MPGN) is a rare and heterogeneous pattern of immune-mediated glomerular injury, often associated with infections, autoimmune disorders, or monoclonal gammopathies. Idiopathic cases remain a diagnostic challenge and frequently require empirical immunosuppressive treatment. There is increasing interest in environmental triggers that may activate the immune system in genetically or immunologically predisposed individuals. We report an unusual case of idiopathic immune complex-mediated MPGN with a relapsing course potentially associated with vaccine-induced immune reactivation. Case Presentation: A 35-year-old male with no significant medical history aside from untreated dyslipidemia and active smoking presented with a hypertensive emergency and acute kidney injury (AKI). Laboratory investigations revealed nephrotic-range proteinuria, microscopic hematuria, and reduced estimated glomerular filtration rate (eGFR). Kidney biopsy demonstrated type I immune complex-mediated MPGN with a diffuse endocapillary proliferative pattern and granular subendothelial deposits (IgG+++, C3+++, C1q++). An extensive work-up ruled out secondary causes, supporting a diagnosis of idiopathic MPGN. Immunosuppressive therapy with corticosteroids and mycophenolate mofetil led to a partial clinical response. However, after receiving multiple vaccinations, the patient experienced clinical deterioration. A second biopsy revealed persistent proliferative changes and new deposits of IgM++, C4d++, and both kappa and lambda light chains. This prompted a reintroduction of immunosuppressive therapy, which resulted in subsequent clinical improvement. Conclusions: This case supports the hypothesis that vaccine-induced immune reactivation may serve as a potential trigger for disease relapse in idiopathic MPGN. Clinicians should remain alert to environmental stimuli that may influence disease activity in immune-mediated glomerulopathies. Further research is needed to elucidate the underlying immunopathogenic mechanisms. Full article

Background: Autism Spectrum Disorder (ASD) encompasses a range of neurodevelopmental conditions characterized by impairments in social communication, restricted and repetitive behaviors, and sensory sensitivities. Despite increased awareness, timely diagnosis in Türkiye remains limited due to the lack of culturally appropriate, psychometrically robust assessment tools. Objective: This study aimed to develop, validate, and standardize the Autism Behavior Assessment Scale (ABAS) as a reliable and culturally adapted tool for assessing ASD-related behaviors in individuals aged 3–24 years in Türkiye. Methods: Employing a three-phase, nine-step scale development framework, data were gathered from 1275 informants (parents and professionals) across 14 provinces. The ABAS comprises 36 items rated on a three-point Likert scale, spanning four subscales: Restricted Repetitive Behaviors & Sensory Sensitivity (RRBSS), Social Interaction (SI), Social Communication (SC), and Non-Developmental Speech (NDS). Psychometric analyses included exploratory and confirmatory factor analysis, reliability testing, and validation against established instruments. Results: The four-factor structure was confirmed via EFA and CFA with excellent model fit. The ABAS demonstrated strong internal consistency (α = 0.91–0.96), test–retest reliability (r = 0.83), and criterion validity (r = 0.93 with GARS-2-TV; r = 0.84 with U-ODKL). Discriminant validity analyses showed that the ABAS accurately differentiated individuals with ASD from individuals with intellectual disabilities (ID) and individuals with hearing impairments (AUC = 0.99). Conclusions: The ABAS is a psychometrically sound, developmentally sensitive, and culturally grounded instrument for identifying and monitoring ASD-related behaviors in Türkiye. It holds promise for improving early detection and guiding educational and clinical interventions. Full article

(1) Background: The COVID-19 pandemic presented unprecedented challenges for people with multiple sclerosis (PwMS) in Oman, necessitating targeted healthcare planning and patient support. This study aimed to investigate the impact of COVID-19 on MS management and disease course, incidence, and outcomes of COVID-19, psychosocial and mental health effects of the pandemic, and demographic and clinical predictors of the effects related to COVID-19 among Omani PwMS. (2) Methods: This cross-sectional study was conducted from January to April 2021. Adult (18–60 years) Omani PwMS completed a structured interview along with the Expanded Disability Status Scale (EDSS) and World Health Organization Well-being Index (WHO-5). Clinical data on relapses and disease-modifying therapies and adherence were analyzed. The data was statistically analyzed. (3) Results: Of 104 PwMS (73.1% female), 22.1% contracted COVID-19, with fatigue being the most reported symptom (87%). Female sex (p = 0.042), younger age (18–34 vs. 35–45 years; p = 0.014), diagnosis of COVID-19 (p = 0.037), and low current mental well-being scores (p = 0.021) predicted greater COVID-19-related effects. (4) Conclusion: These findings highlight the need to study the mental resilience of this subgroup of PwMS and provide them with targeted support during crises. Full article

Introduction: Cutaneous squamous cell carcinoma (cSCC) is the second most common skin cancer entity in Germany, following basal cell carcinoma. Its incidence has increased fourfold over the past three decades. Early diagnosis and treatment are essential for achieving favorable outcomes. Our study aims to identify prognostic factors based on real-world data to improve follow-up protocols and raise clinical vigilance. Methods: We conducted a retrospective, monocenter analysis with a total of 124 patients with at least one cSCC thicker than 3 mm, treated at the Department of Dermatology, University Medical Center Mainz, between 2010 and 2020. Tumor-specific criteria were correlated with patient-specific data, such as gender, age, immunosuppression, UV exposure and mortality. Results: A higher incidence of cSCC was found on UV-exposed skin (91.1%); however, tumors on non-UV-exposed skin were on average thicker (6.55 mm vs. 9.25 mm, p = 0.011) and associated with higher metastasis rates (10.6% vs. 63.3%, p < 0.001). Immunosuppression was strongly associated with a younger age at diagnosis (74 years vs. 81 years), a higher metastasis rate (29% vs. 10.8%, p = 0.021) and a worse 5Y-OS-rate (36.1% vs. 97.8%, p = 0.04). SLNB was performed in eight patients, with one positive SLN identified (12.5%). Local recurrence was observed in 18.1% (n = 21) of patients who did not experience SLNB, whereas no local recurrences (0%) were reported in patients with SLNB (p = 0.349). Discussion: Tumors on non-UV-exposed areas were thicker and more often metastatic, suggesting delayed detection or more aggressive tumor subtypes. Immunosuppression was associated with worse outcomes, underscoring the need for intensified follow-up. SLNB was rarely performed, and larger studies are needed to assess its role. Full article

DIALOGUE (DIagnostic AI Learning through Objective Guided User Experience) is a generative artificial intelligence (GenAI)-based training program designed to enhance diagnostic communication skills in medical students. In this single-arm pre–post study, we evaluated whether DIALOGUE could improve students’ ability to disclose a type 2 diabetes mellitus (T2DM) diagnosis with clarity, structure, and empathy. Thirty clinical-phase students completed two pre-test virtual encounters with an AI-simulated patient (ChatGPT, GPT-4o), scored by blinded raters using an eight-domain rubric. Participants then engaged in ten asynchronous GenAI scenarios with automated natural-language feedback. Seven days later, they completed two post-test consultations with human standardized patients, again evaluated with the same rubric. Mean total performance increased by 36.7 points (95% CI: 31.4–42.1; p < 0.001), and the proportion of high-performing students rose from 0% to 70%. Gains were significant across all domains, most notably in opening the encounter, closure, and diabetes specific explanation. Multiple regression showed that lower baseline empathy (β = −0.41, p = 0.005) and higher digital self-efficacy (β = 0.35, p = 0.016) independently predicted greater improvement; gender had only a marginal effect. Cluster analysis revealed three learner profiles, with the highest-gain group characterized by low empathy and high digital self-efficacy. Inter-rater reliability was excellent (ICC ≈ 0.90). These findings provide empirical evidence that GenAI-mediated training can meaningfully enhance diagnostic communication and may serve as a scalable, individualized adjunct to conventional medical education. Full article

Objective: To evaluate the clinical, radiological, and bronchoscopic features of pediatric patients admitted to the pediatric intensive care unit (PICU) with suspected foreign body aspiration (FBA), and to compare the diagnostic performance of chest radiography (CXR) and computed tomography (CT). Methods: We retrospectively analyzed 71 children admitted to the PICU of Kayseri City Training and Research Hospital for suspected tracheobronchial FBA between January 2020 and December 2024. Demographic data, clinical presentations, imaging findings, bronchoscopic results, and outcomes were recorded. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of CXR and CT were calculated using bronchoscopy as the reference standard. Results: The mean age was 2.61 ± 3.59 years, and 66.1% were male. Organic materials were the most commonly aspirated objects, especially in children aged 0–3 years. The right main bronchus was the most frequently affected site. CXR had a sensitivity of 94.9% (95% CI: 83.1–98.6) and a specificity of 71.0% (95% CI: 53.4–83.9), while CT had a sensitivity of 63.2% (95% CI: 41.0–80.9) and a specificity of 100% (95% CI: 87.5–100.0). Bronchoscopy revealed no foreign body in 45.1% of cases. Most patients (94.4%) fully recovered; complications included two deaths, one lobectomy, and one case of hypoxic sequelae. Conclusion: FBA remains a critical pediatric emergency, particularly in young children. CXR is a highly sensitive and accessible screening tool, while CT offers high specificity but lower sensitivity. Prompt diagnosis and bronchoscopy by experienced teams ensure favorable outcomes. Full article

Background/Objectives: Melanoma is an aggressive skin cancer with increasing incidence worldwide. Dermoscopy has revolutionized early melanoma detection, but most studies have focused on the general adult population. This study aims to analyze dermoscopic and histological differences in melanoma across age groups, evaluating whether specific patterns vary between younger and older patients. Methods: This retrospective study included 285 histopathological confirmed melanomas diagnosed at the Dermatology Clinic of the University of Turin between November 2021 and April 2024. Patients were stratified by age (<40 vs. ≥40 years), and statistical analyses (Chi-square, logistic regression) assessed differences in dermoscopic, histopathological, and anatomical parameters. Results: Younger patients showed a higher prevalence of growth-related features (e.g., pseudopods, OR = 5.43; asymmetric globules, OR = 2.33) and a thicker Breslow index (mean = 1.05 mm). Older patients exhibited more regression-associated signs (scar-like depigmentation, OR = 0.15; peppering, OR = 0.39), greater lesion size, and solar elastosis. Dermoscopic regression significantly predicted histological regression, with age-stratified analysis revealing peppering as a predictor in younger patients (p = 0.015) and scar-like depigmentation in older ones (p = 0.012). Conclusions: Melanoma exhibits distinct dermoscopic features depending on patient age, with growth-associated patterns being more common in younger individuals and regressive patterns predominating in older patients. These findings highlight the importance of age-specific diagnostic considerations in melanoma detection, potentially improving early diagnosis and patient outcomes. Full article

Aseptic abscess syndrome is a clinical entity that is being increasingly documented. Unfortunately, apart from the French registry, there are no other studies presenting collective data. In this review, we sought to analyze clinical and laboratory data from case reports published from the rest of the world. A total of 107 articles were found through our literature search in PubMed, Scopus, and Google, which contained 108 patients who met our eligibility criteria, including pediatric cases. The mean age at diagnosis was 39.1 years, and 54.6% of the patients were female. Cases were found affecting almost every organ, but the most common abscess locations were the spleen (51.9%), liver (35.2%), and lung (23.1%); 34.3% of the patients had multiorgan disease at diagnosis. An inflammatory syndrome was evident, with fever (79.6%), pain (66.7%), median white blood cell count of 16,200/μL, median C-reactive protein level of 15.5 mg/dL, and mean erythrocyte sedimentation rate of 79 mm/h. In total, 88.9% had an associated disease, with the most frequent being neutrophilic dermatosis (43.5%) and inflammatory bowel disease (31.5%); associated disease was inactive during abscess diagnosis in approximately one-quarter of patients. Moreover, 93.5% received corticosteroids with or without other agents, while 21.3% underwent excision surgery, which led to relapse if immunosuppressants were not concomitantly administered. No deaths were reported due to the syndrome, but 42.4% of cases that provided relevant data relapsed despite the relatively short follow-up period (median 1 year), either in the same or different organs. Combined immunomodulatory treatment, based on subgroup analysis, appeared protective against relapse in females and patients with splenic abscess or C-reactive protein >12 mg/dL (odds ratio 0.16 [95% CI 0.04–0.59]/p = 0.004, 0.09 [95% CI 0.01–0.62]/p = 0.008 and 0.23 [95% CI 0.06–0.92]/p = 0.03, respectively). Infection should always be the working diagnosis in patients with abscesses. However, if the infectious workup is negative, antimicrobials have failed, and no sepsis is present, then aseptic abscess syndrome should be considered; response to high-dose corticosteroids is a therapeutic criterion in almost all cases. Full article

ADHD is a childhood neurodevelopmental disorder, but it can persist into adolescence and adulthood and become detrimental to the individual’s well-being. It is known that many individuals with ADHD manifest executive functioning problems that affect their adaptive functioning. In the evaluation phase, it is, therefore, useful to consider these aspects as well. The diagnosis of ADHD is purely clinical in adults: it is based on anamnesis and the completion of questionnaires on the history of symptoms and current symptomatology. In recent years, the tele-assessment has become a valuable and accessible tool for diagnostic framing and intervention planning; however, there are currently few tele-assessment tools that enable the in-depth analysis of young adults. In this study, a group of 34 young adults with ADHD was compared with 35 typically developing peers using a tele-assessment tool for executive functioning (TeleFE, Anastasis). This research can be considered a pilot study to evaluate the differences in these tasks between the two populations and open the possibility of standardizing the tool for young adults. The use of this tool to assess executive functioning in individuals with ADHD in this age group would enable clinicians to plan more individualized interventions. Full article

The sphingolipidoses Fabry disease, Gaucher disease and Acid sphingomyelinase deficiency (ASMD) are the three most common lysosomal storage diseases for which treatment is currently available. Timely diagnosis with estimation of the disease severity and possibilities of follow-up of patients, whether or not under therapy, is crucial for providing good care and for the prevention of possible lethal complications. With this research we provide an efficient and sensitive detection method; its implementation in clinical practice could optimize the diagnosis and follow-up of patients with Gaucher, Fabry and ASMD. This detection method on dried blood spots (DBS) was validated according to the international Clinical and Laboratory Standards Institute (CLSI) guidelines, looking at reproducibility, linearity, carry-over and lower limit of quantification. Analogously, validation and subsequent comparison of the method validation results using another matrix, the Capitainer blood sampling cards (Capitainers), was fulfilled. The results showed that this detection method is fully applicable clinically when using DBS as well as Capitainers. In addition, even additional improvements of some validation parameters were found when using the Capitainers. Twenty-six patient samples and fifteen healthy samples were analyzed for case finding control. All patient cases were detected without ambiguity. We present a high-resolution mass spectrometry method that provides an accurate analysis for targeted screening, aiming for improved/accelerated diagnosis when added in the diagnostic pathway and monitoring of Fabry, Gaucher and ASMD in DBS as well as in Capitainers, with the main advantages of a small volume of blood samples, guaranteeing stability and easy transportation from the collection site to the laboratory. Full article

Objective: With a global prevalence ranging from 50% to 100%, gingivitis is considered the most common oral disease in adults worldwide. It is characterized by clinical signs of inflammation, such as redness, swelling and bleeding, on gentle probing. Although it is considered a milder form of periodontal disease, gingivitis plays an important role in overall oral health. Early detection and treatment are essential to prevent progression to more severe conditions. Typically, diagnosis is performed by dental professionals, as individuals are often unable to accurately assess whether they are affected. Therefore, the aim of the present study was to determine to what degree gingivitis is visually detectable by an easy-to-use camera-based application. Materials and methods: Standardized intraoral photographs were taken using a specialized intraoral camera and processed using a custom-developed filter based on a machine-learning algorithm. The latter was trained to highlight areas suggestive of gingivitis. A total of 110 participants were enrolled through ad hoc sampling, resulting in 320 assessable test sites. A dentist provided two reference standards: the clinical diagnosis based on bleeding on probing of the periodontal sulcus (BOP) and an independent visual assessment of the same images. Agreement between diagnostic methods was measured using Cohen’s kappa statistic. Results: The agreement between the application’s output and the BOP-based clinical diagnosis was low, with a kappa value of 0.055 [p = 0.010]. Similarly, the dentist’s visual assessment of clinical photos showed low agreement with BOP, with a kappa value of 0.087 [p < 0.001]. In contrast, the agreement between the application and the dentist’s photo-based evaluations was higher, with a kappa value of 0.280 [p < 0.001]. Conclusions: In its current form, the camera-based application is not able to reliably detect gingivitis. The low level of agreement between dentists’ visual assessments and the clinical gold standard highlights that gingivitis is difficult to identify merely visually. These results underscore the need to refine visual diagnostic approaches further, which could support future self-assessment or remote screening applications. Full article

In digital pathology, accurate diagnosis and prognosis critically depend on robust feature representation of Whole Slide Images (WSIs). While deep learning offers powerful solutions, its “black box” nature presents significant challenges to clinical interpretability and widespread adoption. Handcrafted features offer interpretability, yet orthogonal moments, particularly Tchebichef moments (TMs), remain underexplored for WSI analysis. This study introduces TMs as interpretable, efficient, and scalable handcrafted descriptors for WSIs, alongside a novel two-dimensional digital filter architecture designed to enhance numerical stability and hardware compatibility during TM computation. We conducted a comprehensive reconstruction analysis using H&E-stained WSIs from the MIDOG++ dataset to evaluate TM effectiveness. Our results demonstrate that lower-order TMs accurately reconstruct both square and rectangular WSI patches, with performance stabilising beyond a threshold moment order, confirmed by SNIRE, SSIM, and BRISQUE metrics, highlighting their capacity to retain structural fidelity. Furthermore, our analysis reveals significant computational efficiency gains through the use of pre-computed polynomials. These findings establish TMs as highly promising, interpretable, and scalable feature descriptors, offering a robust alternative for computational pathology applications that prioritise both accuracy and transparency. Full article

Background/Objectives: Invasive coronary angiography (ICA) is the gold standard for the diagnosis of coronary artery disease (CAD), with various non-invasive imaging modalities also available. Machine learning (ML) methods are increasingly applied to overcome the limitations of diagnostic imaging by improving accuracy and observer independent performance. Methods: This meta-analysis (PRISMA method) summarizes the evidence for ML-based analyses of coronary imaging data from ICA, coronary computed tomography angiography (CT), and nuclear stress perfusion imaging (SPECT) to predict clinical outcomes and performance for precise diagnosis. We searched for studies from Jan 2012–March 2023. Study-reported c index values and 95% confidence intervals were used. Subgroup analyses separated models by outcome. Combined effect sizes using a random-effects model, test for heterogeneity, and Egger’s test to assess publication bias were considered. Results: In total, 46 studies were included (total subjects = 192,561; events = 31,353), of which 27 had sufficient data. Imaging modalities used were CT (n = 34), ICA (n = 7) and SPECT (n = 5). The most frequent study outcome was detection of stenosis (n = 11). Classic deep neural networks (n = 12) and convolutional neural networks (n = 7) were the most used ML models. Studies aiming to diagnose CAD performed best (0.85; 95% CI: 82, 89); models aiming to predict clinical outcomes performed slightly lower (0.81; 95% CI: 78, 84). The combined c-index was 0.84 (95% CI: 0.81–0.86). Test of heterogeneity showed a high variation among studies (I² = 97.2%). Egger’s test did not indicate publication bias (p = 0.485). Conclusions: The application of ML methods to diagnose CAD and predict clinical outcomes appears promising, although there is lack of standardization across studies. Full article

Depression represents one of the most prevalent mental health disorders globally, significantly impacting quality of life and posing substantial healthcare challenges. Traditional diagnostic methods rely on subjective assessments and clinical interviews, often leading to misdiagnosis, delayed treatment, and suboptimal outcomes. Recent advances in biosensing technologies offer promising avenues for objective depression assessment through detection of relevant biomarkers and physiological parameters. This review examines multi-modal biosensing approaches for depression by analyzing electrochemical biosensors for neurotransmitter monitoring alongside wearable sensors tracking autonomic, neural, and behavioral parameters. We explore sensor fusion methodologies, temporal dynamics analysis, and context-aware frameworks that enhance monitoring accuracy through complementary data streams. The review discusses clinical validation across diagnostic, screening, and treatment applications, identifying performance metrics, implementation challenges, and ethical considerations. We outline technical barriers, user acceptance factors, and data privacy concerns while presenting a development roadmap for personalized, continuous monitoring solutions. This integrative approach holds significant potential to revolutionize depression care by enabling earlier detection, precise diagnosis, tailored treatment, and sensitive monitoring guided by objective biosignatures. Successful implementation requires interdisciplinary collaboration among engineers, clinicians, data scientists, and end-users to balance technical sophistication with practical usability across diverse healthcare contexts. Full article