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RESULTSThe cumulative lag 0-3 risk of hospitalization associated with heat exposure was highest in the West (rate ratio [RR]: 1.099; 95% confidence interval [CI]: 1.041, 1.160), whereas the highest risk of mortality was observed in the Northwest region (RR: 1.097; 95% CI: 1.007, 1.195). We observed significant increases in the risk of hospitalization at the low- and mid-latitude bands and a significant increase in the risk of mortality in the mid-latitude band.CONCLUSIONWe observed spatial heterogeneity across US climate regions. The strongest effects of heat exposure were observed in the Ohio Valley, South, and West regions for hospitalization and the Upper Midwest, Southeast, and Northwest regions for mortality. Findings may be used to inform targeted interventions to patients with ESKD residing in areas with higher risks of adverse health outcomes following heat exposure.BACKGROUNDThe impact of heat exposure on patients with end-stage kidney disease (ESKD) is of growing concern in the context of climate change. In this study, we investigated the association of heat exposure with hospitalization and mortality, and how the risk of these adverse health outcomes varied by climate region in the US.METHODSWe obtained hospitalization and mortality data for patients with ESKD receiving in-center hemodialysis treatment between 2012 and 2018 at Fresenius Kidney Care facilities located within the contiguous US. We used the treatment facility location to assign heat exposure using maximum universal thermal climate index temperature data. We conducted a space-time-stratified case-crossover study using conditional Poisson regression with distributed lag nonlinear models to examine the effects of heat exposure at the 95th percentile of the region-specific temperature distribution for lags of three days. Stratified analyses were run to assess differences in associations across nine climate regions and three latitude bands.

Artificial intelligence (AI) is rapidly transforming the delivery of kidney care through predictive analytics, machine learning, deep learning, and generative AI technologies. To meet this challenge, the American Society of Nephrology convened an AI Workgroup to provide a framework for the responsible use of AI in nephrology. The group outlines foundational principles to guide AI development: prioritizing patient benefit, ensuring clinician oversight, and advancing innovation in high-burden disease areas. Its set of foundational assumptions are grounded in the physician always being in the loop and an overarching goal to benefit patients with kidney disease. This review provides an overview of the clinical uses of AI in nephrology and offers practical guidance for nephrologists seeking to incorporate AI into CKD and AKI management, dialysis, and transplantation care. It also highlights key challenges-such as data quality, equity, transparency, and clinical integration-that must be addressed to ensure the responsible and effective implementation of AI in kidney care.

RESULTSAt baseline, 55% of patients were receiving hemodialysis and 45% of patients were receiving hemodiafiltration. Baseline characteristics were similar between baseline modalities, except that hemodiafiltration patients were a median of 2 years younger, had higher percentage of fistula access (66% vs. 47%), and had longer mean dialysis vintages (4.4 years vs. 2.6 years). Compared with hemodialysis, hemodiafiltration was associated with an adjusted hazard ratio (HR) for all-cause mortality of 0.78 (95% confidence interval [Cl], 0.76-0.80), irrespective of COVID-19 infection. The pattern of a beneficial effect of hemodiafiltration was consistently observed among all analyzed subgroups. Among patients receiving high-volume hemodiafiltration (mean convection volume ≥ 23 L), the risk of death was reduced by 30% (HR, 0.70 [95% CI, 0.68-0.72]). Hemodiafiltration was also associated with a 31% reduced risk of cardiovascular death.CONCLUSIONSOur results suggest that hemodiafiltration has a beneficial effect on all-cause and cardiovascular mortality in a large, unselected patient population and across patient subgroups in real-world settings. Our study complements evidence from the CONVINCE trial and adds to the growing body of real-world evidence on hemodiafiltration.BACKGROUNDResults from the CONVINCE clinical trial suggest a 23% mortality risk reduction among patients receiving high-volume (> 23 L) hemodiafiltration. We assessed the real-world effectiveness of blood-based kidney replacement therapy (KRT) with hemodiafiltration vs. hemodialysis in a large, unselected patient population treated prior to and during the COVID-19 pandemic.METHODSIn this retrospective cohort study, we analyzed pseudonymized data from 85,117 adults receiving in-center care across NephroCare clinics in Europe, the Middle East, and Africa during 2019-2022. Cox regression models with KRT modality and coronavirus disease 2019 (COVID-19) status as time-varying covariates, and adjusted for multiple confounders, were used to estimate all-cause (primary) and cardiovascular (secondary) mortality. Subgroup analyses were performed for age, dialysis vintage, COVID-19 status, diabetes, and cardiovascular disease.

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