Mucopolysaccharidosis type IIIC (MPS IIIC) is a rare lysosomal storage disorder caused by biallelic pathogenic variants in the HGSNAT gene, encoding heparan-α-glucosaminide N-acetyltransferase. Deficient enzymatic activity leads to heparan sulfate accumulation, resulting in progressive central nervous system involvement and multisystem disease. Clinical features typically include developmental delay, intellectual disability, behavioral disturbances, coarse facial features, hypertrichosis, and hearing loss. This report describes the oldest documented siblings with MPS IIIC: a male diagnosed at 46 years (currently 50 years) and his sister diagnosed at 38 years (currently 42 years). Both presented with bilateral sensorineural hearing loss, retinitis pigmentosa, intellectual disability, mildly coarse facial features, and hypertrichosis. Molecular analysis identified two novel HGSNAT variants: c.1205T>C; p.(Leu402Pro) and c.1565C>A; p.(Thr522Lys). Functional studies demonstrated markedly reduced heparan-α-glucosaminide N-acetyltransferase activity and elevated urinary heparan sulfate excretion, providing biochemical evidence supporting variant pathogenicity and confirming the diagnosis. These cases expand both the phenotypic and genotypic spectrum of MPS IIIC and underscore the importance of considering this disorder in adults with multisystem involvement. Functional characterization proved essential for establishing a definitive diagnosis when molecular findings alone were inconclusive.
To compare Aquablation and anatomical endoscopic enucleation of the prostate (AEEP) for the surgical management of benign prostatic hyperplasia (BPH), focusing on surgical technique, perioperative outcomes, functional results, safety, and durability. A narrative review of randomized controlled trials, prospective studies, and real-world evidence was performed, including key studies such as WATER I, II, and III, as well as large-gland cohorts and guideline-based data evaluating Aquablation and AEEP. Both Aquablation and AEEP provide significant and durable improvements in lower urinary tract symptoms and urinary flow across a wide range of prostate sizes. AEEP remains the reference standard for size-independent treatment, with long-term retreatment rates of approximately 1–2
BACKGROUND:Liver volumetry (LV) is essential in preoperative planning for liver resection and living donor liver transplantation, particularly in extended resections, where minimizing the risk of post-hepatectomy liver failure (PHLF) and ensuring donor safety are pivotal. Several software platforms have been developed to support LV, employing different segmentation techniques, from manual to semi-automated and fully automated, based on contrast-enhanced computed tomography (CT) or, less frequently, magnetic resonance imaging. MAIN FINDINGS:Manual tracing remains the reference standard but it is limited by high operator dependency, long execution times, and low reproducibility. Semi-automated tools reduce user variability and shorten processing time. Synapse has shown no evident learning curve, while Syngo.via requires user training. Hermes, integrating functional data from SPECT, offers superior prediction of PHLF but less precise correlation with actual graft weight in living donor liver transplantation. Automated platforms such as LiverVision, Myrian XP-Liver, and Vitrea have demonstrated strong agreement with manual or graft weight references and shorter execution times. However, most tools still require manual contouring, particularly for anatomical delineation and exclusion of vessels or biliary structures. Fully automated tools such as LISA remain experimental and lack clinical validation. Software comparison remains challenging and limited due to the absence of standardized validation protocols, metrics variations across studies, and the predominance of proprietary conditions. CONCLUSION:The aim of this narrative review is to summarize the available features, performances and clinical applicability of 11 widely used LV tools. While emerging evidence supports their clinical utility, further multicenter studies using standardized methodologies are needed to clarify their relative advantages and promote consistent use in surgical practice.
Upper gastrointestinal bleeding (UGIB) remains a significant clinical emergency with substantial mortality. Accurate risk stratification is essential for optimal patient triage and management. The ABC score (Age, Blood tests, Comorbidities) and AIMS65 score are prominent pre-endoscopy risk stratification tools, yet direct comparative studies within diverse United States healthcare populations remain limited. To compare the predictive accuracy of ABC and AIMS65 scores for in-hospital mortality and secondary clinical outcomes in patients with acute UGIB. This retrospective cohort study analyzed 2,009 adult patients admitted with acute UGIB across multiple Northwell Health hospitals between January 2019 and January 2024. Both ABC and AIMS65 scores were calculated for each patient using structured EMR data, ICD-10 diagnosis codes, and anesthesiology procedure documentation. Primary outcomes included in-hospital mortality and 30-day readmission. Secondary outcomes encompassed hospital length of stay, ICU admission, development of complications (shock, sepsis, acute kidney injury), vasopressor use, and need for mechanical ventilation. Univariable logistic regression models assessed predictive accuracy using area under the receiver operating characteristic curve (AUC), with bootstrap internal validation (10,000 resamples) confirming negligible optimism bias. DeLong’s test compared discriminative abilities between scores. Sensitivity analyses evaluated score performance across pandemic periods and in a broader AIMS65-computable cohort. Among 2,009 patients (56.1
Millions of patients are regularly using large language model (LLM) chatbots for medical advice, raising patient safety concerns. This physician-led red-teaming study compares the safety of four publicly available chatbots—Claude by Anthropic, Gemini by Google, GPT-4o by OpenAI, and Llama-3.0/3.1-70B by Meta—on a new dataset, HealthAdvice, using an evaluation framework that enables quantitative and qualitative analysis. In total, 888 chatbot responses are evaluated for 222 patient-posed advice-seeking medical questions on primary care topics spanning internal medicine, women’s health, and pediatrics. We find statistically significant differences between chatbots. The rate of problematic responses varies from 21.6% (Claude) to 43.2% (Llama), with unsafe responses varying from 5% (Claude) to 13% (GPT-4o, Llama). Qualitative results reveal chatbot responses with the potential to lead to serious patient harm. This study suggests that millions of patients could be receiving unsafe medical advice from publicly available chatbots, and further work is needed to improve the clinical safety of these powerful tools.
