Citations

ABSTRACTBackgroundMetabolic dysfunction‐associated steatotic liver disease (MASLD) affects over one third of the global population and is closely linked to gastrointestinal, oncological, and cardiovascular diseases. As the most common cause of steatotic liver disease (SLD), MASLD is often referred to as “fatty liver” in general health information searches. With the Internet becoming a primary source of healthcare information, this study aimed to evaluate global and regional public interest in steatotic liver disease using Google Trends data from January 2004 to December 2024.MethodsA comprehensive analysis was performed using Google Trends with the search term “fatty liver disease.” Interest levels were quantified using Google Trends indices, and temporal patterns were evaluated using average annual percent change (AAPC). Regional variations were assessed to identify geographic hotspots of public interest.ResultsGlobal interest in MASLD demonstrated significant growth (AAPC: 6.77%, 95% Confidence interval [CI]: 5.33–8.23), with a 264% increase from 2004 to 2024. Peak interest was observed in August 2024 (index: 100) compared to the lowest point in June 2007. Iran showed the highest country‐specific search volume (index: 100), while within the United States, West Virginia demonstrated the greatest relative interest (index: 100). Key topics associated with MASLD included “liver,” “symptoms,” “disease,” and “therapy.”ConclusionsSubstantial growth in global public interest in MASLD, with distinct temporal and geographical patterns, provides insights to develop targeted awareness campaigns and educational interventions, particularly in regions with low search volumes. Future research should examine the relationship between online search patterns and clinical outcomes in MASLD.

Key Points Preexisting CKD, elevated serum creatinine, and severe interstitial fibrosis and tubular atrophy were linked to poor renal prognosis in renal sarcoidosis. Steroid therapy was strongly associated with renal recovery and improved long-term outcomes in renal sarcoidosis. Early detection and management of renal involvement in sarcoidosis are critical to preventing irreversible kidney damage. Background Renal sarcoidosis (RS) is a rare but potentially severe manifestation of sarcoidosis, primarily affecting the kidneys through granulomatous interstitial nephritis and calcium metabolic disturbances. This study evaluates the clinicopathologic features and renal outcomes of biopsy-proven RS, focusing on identifying predictors of renal recovery and disease progression. Methods This retrospective study included 43 biopsy-proven RS at Mayo Clinic (2012–2024). Demographic, clinical, laboratory, and histopathologic data were analyzed. Renal recovery within 6 months was classified as complete, partial, or no recovery based on serum creatinine (sCr) changes. Long-term adverse composite outcomes included the CKD onset, CKD progression, ESKD, dialysis initiation, or death. Logistic regression and Cox proportional hazards regression were used to assess predictors of renal outcomes. Results Among the cohort, 84% exhibited interstitial nephritis, with granulomatous interstitial nephritis in 33%. Calcium phosphate deposits were found in 58% of cases. Hypercalciuria (90%) was more common than hypercalcemia (74%). Within 6 months, 86% achieved recovery (74% complete, 12% partial), while 40% experienced long-term adverse composite outcomes. Higher sCr at biopsy (≥2.4 mg/dl) and moderate-to-severe interstitial fibrosis and tubular atrophy were associated with reduced complete recovery and worse long-term outcomes, while preexisting CKD significantly increased the risk of adverse long-term outcomes. Steroid therapy significantly increased the likelihood of complete recovery and reduced the risk of adverse long-term outcomes. Conclusions Preexisting CKD, elevated sCr at biopsy, interstitial fibrosis and tubular atrophy, and steroid therapy are key predictors of renal outcomes in RS. Early diagnosis and intervention are crucial to preventing irreversible kidney damage.

ABSTRACT Background Kidney disease significantly increases the risk of dementia, including among kidney transplant (KTx) recipients. To date, the cost implications of dementia after KTx are not well described. Methods We performed a retrospective cohort study of US Renal Data System (USRDS) data (2006–2020) to estimate cost of care for ≥65‐year‐old Medicare insured KTx recipients (2006–2020) with newly diagnosed dementia ( n = 3285), compared to propensity‐matched controls without dementia ( n = 6570). KTx recipients age 65+ years with post‐KTx dementia were identified by diagnosis codes, and costs were computed based on payments on Medicare claims. Average costs per month, marginal costs per month, and cumulative costs were compared after dementia diagnosis versus after the equivalent time post‐KTx in controls. Results Dementia was diagnosed at a mean of 5.1 ± 3.4 years post‐KTx. Patients' characteristics were well matched in cases versus controls, including age (mean: 70.1 vs. 69.9 years), sex (38.4% vs. 37.9% women), race (23.7% vs. 22.2% African American), and cause of ESKD (45.4% vs. 43.7% diabetes). Over 4 years post‐KTx, dementia was associated with reduced survival (27% vs. 68%) along with $66 145 (95% CI $51 560‐$78 489) higher Medicare spending. Average monthly costs in dementia patients reached a maximum of $12 713 and exceeded the cost of unaffected patients by up to $9789 per month. Conclusions Post‐KTx dementia dramatically increased resource utilization and reduced post‐KTx surivival. These findings highlight the need for care pathways that better integrate cognitive health assessment and management into the care of KTx candidates and recipients.

INTRODUCTION: DeepSeek was evaluated in gastroenterology board examination performance against legacy ChatGPT offline models, which previously showed failing performance. METHODS: The performances of the DeepSeek base R1 model and search-augmented R1 model were assessed using American College of Gastroenterology self-assessments (455 questions). RESULTS: DeepSeek exceeded the passing threshold. Search-augmented DeepSeek scored 81.5% across all questions, and the R1 base model scored 77.1%. Both search-augmented and offline DeepSeek models surpassed offline ChatGPT-3 (65.1%) and ChatGPT-4 (62.4%) ( P < 0.001). DISCUSSION: DeepSeek exhibited passing performance on the gastroenterology board examination but had gaps in niche topics and image exclusion limit utility. It may supplement education if validated by specialists.

Background/Objectives: Malnutrition is a prevalent yet under-recognized condition in patients with advanced chronic kidney disease (CKD), contributing to increased morbidity, mortality, and healthcare burden. The aim of this study is to determine the prevalence and trends of malnutrition and investigate the impact of malnutrition on in-hospital outcomes, treatments, and resource utilization in hospitalized patients with advanced CKD. Methods: This study utilized the National Inpatient Sample (NIS) database to identify hospitalized patients with advanced CKD from 2016 to 2021. This study investigated temporal trends in the prevalence and in-hospital mortality across different degrees of malnutrition in advanced CKD patients. Multivariable regression models were used to assess the association between malnutrition and in-hospital outcomes. Results: Out of 1,244,415 advanced CKD patients, 67,587 (5.4%) had mild to moderate malnutrition, and 63,785 (5.1%) had severe malnutrition. Malnourished patients exhibited significantly higher in-hospital mortality, with adjusted odds ratios of 1.70 (95% confidence interval (CI), 1.64–1.75) for mild to moderate cases and 2.67 (95% CI, 2.60–2.75) for severe cases. Severely malnourished patients were associated with longer mean hospital stay by 7.0 days and higher hospitalization costs by $97,767 compared with non-malnourished patients. The prevalence of severe malnutrition showed a significant uptrend from 4.2% in 2016 to 5.5% in 2021 (p for trend < 0.001). Conclusions: Malnutrition in advanced CKD is an increasingly prevalent condition linked to worsened in-hospital outcomes and heightened healthcare resource utilization. The rising trend of severe malnutrition underscores the need for early nutritional screening and the need for future interventional studies to mitigate adverse clinical outcomes in this high-risk population.

Background The digital transformation in medical education is reshaping how clinical skills, such as point-of-care ultrasound (POCUS), are taught. In nephrology fellowship programs, POCUS is essential for enhancing diagnostic accuracy, guiding procedures, and optimizing patient management. To address these evolving demands, we developed an artificial intelligence (AI)-driven POCUS curriculum using a multiagent approach that integrates human expertise with advanced AI models, thereby elevating educational standards and better preparing fellows for contemporary clinical practice. Methods In April 2024, the Mayo Clinic Minnesota Nephrology Fellowship Program initiated a novel AI-assisted process to design a comprehensive POCUS curriculum. This process integrated multiple advanced AI models—including GPT-4.0, Claude 3.0 Opus, Gemini Advanced, and Meta AI with Llama 3—to generate initial drafts and iteratively refine content. A panel of blinded nephrology POCUS experts subsequently reviewed and modified the AI-generated material to ensure both clinical relevance and educational rigor. Results The curriculum underwent 12 iterative revisions, incorporating feedback from 29 communications across AI models. Key features of the final curriculum included expanded core topics, diversified teaching methods, enhanced assessment tools, and integration into inpatient and outpatient nephrology rotations. The curriculum emphasized quality assurance, POCUS limitations, and essential clinical applications, such as fistula/graft evaluation and software integration. Alignment with certification standards further strengthened its utility. AI models contributed significantly to the curriculum's foundational structure, while human experts provided critical clinical insights. Conclusion This curriculum, enhanced through a multiagent approach that combines AI and human collaboration, exemplifies the transformative potential of digital tools in nephrology education. The innovative framework seamlessly integrates advanced AI models with expert clinical insights, providing a scalable model for medical curriculum development that is responsive to evolving educational demands. The synergy between technological innovation and human expertise holds promising implications for advancing fellowship training. Future studies should evaluate its impact on clinical competencies and patient outcomes across diverse practice environments.

Background/Objectives: With the growing population of kidney transplant recipients (KTRs) in intensive care units (ICUs), understanding their prognostic outcomes is critical. As conflicting findings exist, we aim to systematically evaluate and meta-analyze ICU outcomes in kidney transplant recipients compared to non-recipients. Methods: We conducted a comprehensive search of the PubMed, Embase, and Cochrane databases, from inception through 23 December 2024, to identify relevant studies comparing the outcomes of KTRs and non-transplant ICU patients. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for dichotomous outcomes, and weighted mean differences (WMDs) were calculated for continuous outcomes. The risk of bias was assessed using the ROBINS-I V2 tool. The study protocol was registered in the International Prospective Register of Systematic Reviews (CRD42024595104). Results: Seven studies, including 12,062 patients, were analyzed. Demographics, including age and sex, were comparable across groups. No statistically significant associations were found for overall mortality (OR: 1.82, 95% CI: 0.79 to 4.16), ICU mortality (OR: 1.06, 95% CI: 0.45 to 2.48), or 28/30-day mortality (OR: 2.06, 95% CI: 0.30 to 14.10) in KTRs, though there was a trend suggesting a potential increase in the odds of overall mortality. KTRs tended to have longer ICU stays (WMD: +1.96 days, 95% CI: 0.81–3.11) and higher Sequential Organ Failure Assessment (SOFA) scores (WMD: +0.79, 95% CI: −0.78–2.36), but these findings did not reach statistical significance. One study reported higher 1-year and 5-year mortality for KTRs. Sensitivity analyses revealed one influential study. Begg’s test for overall mortality suggested non-significant publication bias (p = 1.0). Conclusions: KTRs in ICUs are at significantly higher risk for long-term mortality, emphasizing the need for tailored critical care strategies and long-term management. Future research should focus on standardizing methodologies, reducing heterogeneity, and addressing gaps in data to improve evidence-based care for this vulnerable population.