Miao, Jing

Background Kidney transplantation offers substantial clinical and economic benefits for patients with end-stage kidney disease (ESKD), yet organ shortages persist. Enhancing public awareness and health literacy regarding kidney donation is essential for effective donor recruitment. While online patient education materials are primary drivers of public perception, their readability, digital engagement, and accessibility remain underexplored barriers. Methods We analyzed the most prominent kidney donation websites identified through U.S.-based Google searches, including 11 primary organizations and 16 affiliated subdomains, for a total of 27 websites. Readability was benchmarked using Flesch-Kincaid, SMOG, and Gunning Fog indices. To assess qualitative metrics, we deployed a generative AI framework utilizing a Large Language Model (Claude) to conduct automated sentiment analysis and tone evaluation, validated by human review. We systematically mapped digital engagement features, including multimedia, interactive tools, and multilingual support, to determine content comprehensiveness. Results Websites consistently provided accurate information with a generally positive or neutral tone. Average readability exceeded recommended levels, with a combined mean grade of 12.3; 34% of websites were written at a college-level reading standard. Consensus across content was high. Multimedia elements were widely used, but engagement features were limited; only 30% of sites included extensive testimonials, and interactive tools were absent. AI-based analysis enabled standardized and reproducible evaluation, highlighting opportunities to improve accessibility, tone, and inclusivity. Conclusion Current U.S. kidney donation digital resources present a barrier to health equity due to excessive reading complexity and static engagement models. AI provides a scalable, reproducible framework to audit and optimize patient education materials. Future initiatives must leverage AI-guided content optimization to bridge the literacy gap, potentially increasing donor registration and access to transplantation.

Key Points Baseline kidney function and chronic structural injury strongly predicted both renal recovery and long-term clinical outcomes. Tubulointerstitial nephritis was the predominant lesion in Sjögren syndrome with renal involvement. Early detection and management of renal involvement in Sjögren syndrome are critical to preventing irreversible kidney damage. Background Renal involvement in primary Sjögren syndrome (SS) is uncommon but clinically consequential. Previous studies have been limited by small samples and incomplete biopsy data. We evaluated a large biopsy-confirmed cohort to characterize clinicopathologic features of SS with renal involvement and identify predictors of renal recovery and long-term outcomes. Methods We retrospectively identified adults with SS and kidney biopsy at Mayo Clinic (2012–2025). Clinical, laboratory, and histologic data were extracted. Predictors of complete renal recovery within 6 months, defined as serum creatinine (sCr) returning to within 25% of baseline or <1.4 mg/dl if baseline was unknown, were evaluated using logistic regression. Cox regression assessed long-term risk of a composite end point: newly developed or progressive CKD, ESKD, or all-cause mortality. Results Fifty-six patients were included (median age 57 years; 91% female). Extraglandular manifestations occurred in 76% and baseline CKD in 65%. The median sCr at baseline and biopsy was 1.3 and 1.6 mg/dl, respectively. Anti-Sjogren's syndrome antigen A, often linked with Ro ribonucleoprotein was positive in 80%. Low C3 occurred in 14% and low C4 in 25%. Tubulointerstitial nephritis was the predominant lesion (71%). Moderate/severe interstitial fibrosis/tubular atrophy and arteriosclerosis were present in 36% and 41%, respectively. Immunosuppressive therapy was applied in 84%. Complete recovery occurred in 67%. Over a median 3.9 years (interquartile range, 1.4–7.2), 43% reached the composite end point. Baseline sCr ≥2 mg/dl, 24-hour proteinuria ≥1 g, and presence of segmental glomerulosclerosis were associated with lower odds of recovery (odds ratio=0.16, 0.13 and 0.11, P = 0.02, 0.001 and 0.008, respectively) and higher long-term risk (hazard ratio=4.51, 2.92 and 3.52; P = 0.002, 0.01 and 0.02, respectively). Moderate/severe arteriosclerosis also increased long-term risk (hazard ratio=2.56; P = 0.03). Conclusions In biopsy-confirmed SS-related renal involvement, the severity of kidney dysfunction and the extent of chronic glomerular and vascular injury strongly predict renal prognosis. Early detection and targeted management of high-risk features may improve long-term renal outcomes.

BACKGROUND: Hypertension, the leading cause of cardiovascular mortality, remains suboptimally controlled. Large language models (LLMs) could improve hypertension control by augmenting clinical decision-making, but their reliability for guideline-driven tasks is unverified. This study evaluated the accuracy and safety of hypertension management recommendations generated by 3 LLMs. METHODS: Fifty-one vignettes were constructed and submitted to the LLMs (GPT-4, Gemini, Medical Large Language Model [by Google; MedLM]) and a hypertension expert to generate the responses. Three blinded reviewers rated each response on a 4-point accuracy scale, a binary safety (safe/unsafe) scale, and attempted to identify the source (LLM versus expert) providing the response. RESULTS: GPT-4 had the highest accuracy (83%) and safety (86%) scores among LLMs but remained inferior to expert responses (92% accuracy, 93% safety). Gemini and MedLM performed significantly worse (accuracy: 64% and 35%; safety: 73% and 39%, respectively). GPT-4 generated the most guideline-concordant responses (46%) among the 3 LLMs (Gemini 35%, MedLM 14%) but was lower than expert responses (68%). Interrater reliability for accuracy ratings was higher for LLM-generated responses (GPT-4 [intraclass correlation coefficient, 0.30], Gemini [intraclass correlation coefficient, 0.61], and MedLM [intraclass correlation coefficient, 0.58]), with lower agreement for expert responses (intraclass correlation coefficient, 0.23). A similar pattern was observed for safety and source discrimination ratings. The agreement was strongest for safety assessments and weakest for source discrimination. CONCLUSIONS: Among the 3 tested LLMs, GPT-4 demonstrated closer agreement to expert decisions, thereby showing greater potential for supporting hypertension management. Despite their potential, current LLM versions are inferior to expert recommendations. Human-in-the-loop supervision remains essential when deploying LLMs for clinical decision-making.

Background We aimed to assess the longitudinal changes of glycocalyx, a proteoglycan/glycoprotein layer that lines and protects endothelial cells in normotensive pregnancies (NPs); to correlate glycocalyx parameters with kidney injury markers (podocin‐positive to nephrin‐positive [P/N] ratio); and to explore changes in P/N ratio in preeclampsia. Methods Plasma and urine samples and glycocalyx measurements using side‐stream darkfield imaging were collected at each trimester from pregnant women (n=31). Plasma glycocalyx components were measured by ELISA, and urinary P/N‐positive extracellular vesicles by flow cytometry. Results In NPs (n=26), glycocalyx degradation increased from the first to the second trimester ( P =0.008) and returned to first‐trimester values in the third trimester ( P =0.008). Microvascular perfusion decreased from the first to the second trimester ( P =0.006) and increased back to first‐trimester values by the third trimester ( P =0.039). Plasma syndecan 1 level showed a steady increase from the first to the second trimester ( P <0.001) and further in the third trimester ( P <0.001); hyaluronic acid increased from the first to the second trimester ( P =0.016) without further changes. Glycocalyx degradation was associated with an increase in P/N ratio from the first to the second trimester of NPs and remained stable through the third trimester. P/N ratio strongly correlated with elevated syndecan 1 and hyaluronic acid levels in the third trimester. Comparison of P/N ratios between NP and preeclampsia (n=5) showed higher values in preeclampsia across all trimesters ( P =0.028). Conclusions Glycocalyx changes during NPs are associated with elevated urinary podocyte markers. Increase in P/N ratio across NPs, and further in preeclampsia, suggests that podocyte injury in preeclampsia is extension of physiological changes in pregnancy, which may predate its clinical presentation.

ABSTRACT Background Membranous nephropathy (MN) associated with phospholipase A2 receptor (PLA2R) antibodies is the most common cause of nephrotic syndrome in non-diabetic adult patients. This study investigated the relationship between clinical phenotypes and renal outcomes in this population, emphasizing the potential for phenotype-based treatment stratification. Methods We conducted a retrospective, multi-center cohort study of PLA2R-positive MN. Unsupervised cluster analysis grouped patients based on clinicopathological characteristics. Primary outcomes included complete or partial remission within 2 years of biopsy and end-stage kidney disease (ESKD) or death during follow-up. Results Among 178 patients, three distinct clusters emerged (n = 89, 70, and 19). Within 2 years of biopsy, 102 patients (57%) achieved complete or partial remission. Cluster 1, characterized by the mildest disease markers, including the lowest body mass index, serum anti-PLA2R titer, serum creatinine, proteinuria, and triglycerides, had the highest remission rate of 72%, compared with 50% in cluster 2 and 54% in cluster 3. Cluster 2 had significantly lower remission compared to cluster 1 (HR 0.64, 95% CI 0.42–0.96, P = .03); results were similar in cluster 3, albeit not statistically significant (HR 0.50, 95% CI 0.23–1.09, P = .08). Elevated anti-PLA2R levels (&gt;100 U/ml) and proteinuria (&gt;8 g/24-hour) predicted reduced remission (HR 0.56, 95% CI 0.36–0.88, P = .01; HR 0.43, 95% CI 0.26–0.73, P = .002, respectively), while high high-density lipoprotein levels were protective (HR 1.01, 95% CI 1.00–1.02, P = .048). Overall, 21 patients (12%) developed ESKD or died. ESKD-free survival differed significantly across clusters (log-rank test P = .04). Conclusions Unsupervised clustering identified distinct clinical phenotypes in PLA2R-positive MN, each associated with different renal prognoses. Phenotype-based risk stratification could enhance treatment precision, improve patient outcomes, and potentially reduce treatment-related adverse effects.

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.

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.