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Association of Myosteatosis and of Graft Loss after Kidney Transplantation: An International Observational Study. 肾移植后肌骨化病与移植物损失的关系:一项国际观察性研究。
IF 9.8 1区 医学 Q1 UROLOGY & NEPHROLOGY Pub Date : 2025-10-15 DOI: 10.2215/cjn.0000000862
Marcel Zorgdrager,Yi Liu,Jingyao Hong,Nidhi Ghildayal,Tim D A Swaab,Stephan J L Bakker,Alain R Viddeleer,Babak J Orandi,Omid Shafaat,Clifford R Weiss,Dorry Segev,Mara McAdams-DeMarco,Robert A Pol
BACKGROUNDSarcopenia and myosteatosis are indicators of abnormal body composition (BC). Computed tomography (CT) imaging has proven to be an accurate modality for BC quantification in kidney transplantation (KT). We tested whether pre-KT CT-based BC was associated with both all-cause graft loss (ACGL) and mortality among adult recipients from two centers (Johns Hopkins Hospital [JHH] and University Medical Center Groningen [UMCG]).METHODSPatients who underwent a KT between 2003 and 2020 were followed for a median (interquartile range) follow-up of 6.4 (4.6-8.5) years at JHH and 6.3 (5.1-7.5) years at UMCG. Cox proportional hazard models were used to estimate the associations of BC with ACGL/ mortality. Fine and Gray regression analysis was performed to assess the association between BC and death-censored graft loss. Prior to KT, 49% of recipients had sarcopenia and 66% had myosteatosis.RESULTSIn total 608 patients were included from JHH (N= 294) and UMCG (N=314). Sarcopenia was not associated with post-KT outcomes. Myosteatosis was associated with a higher risk of ACGL (adjusted hazard ratio 1.78, 95%CI:1.08 - 2.93) and mortality (adjusted hazard ratio 2.35, 95%CI: 1.27 - 4.33) at JHH, but showed no significant association at UMCG after adjusting for confounders. Myosteatosis did not show a significant association with death-censored graft loss at both centers.CONCLUSIONMyosteatosis ascertained from existing CT scans could help identify recipients at higher risk for ACGL who may benefit most from prehabilitation.
背景:肌肉减少症和骨骼肌病是异常体成分(BC)的指标。计算机断层扫描(CT)成像已被证明是肾移植(KT)中BC定量的准确方式。我们在两个中心(约翰霍普金斯医院[JHH]和格罗宁根大学医学中心[UMCG])的成年受者中测试了kt前ct为基础的BC是否与全因移植物损失(ACGL)和死亡率相关。方法对2003年至2020年间接受KT的患者进行中位(四分位数范围)随访,JHH组为6.4(4.6-8.5)年,UMCG组为6.3(5.1-7.5)年。使用Cox比例风险模型来估计BC与ACGL/死亡率的关系。采用精细和灰色回归分析来评估BC与死亡审查的移植物损失之间的关系。在KT之前,49%的接受者患有肌肉减少症,66%患有肌骨化症。结果共纳入JHH(294例)和UMCG(314例)患者608例。肌少症与kt后的预后无关。在JHH时,肌骨化病与较高的ACGL(校正风险比1.78,95%CI:1.08 - 2.93)和死亡率(校正风险比2.35,95%CI: 1.27 - 4.33)相关,但在校正混杂因素后,在UMCG时无显著相关性。在两个中心,肌骨化病与死亡审查的移植物损失没有明显的关联。结论从现有的CT扫描中确定的肌骨化病可以帮助识别ACGL的高风险受者,他们可能从康复中获益最多。
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引用次数: 0
The Importance of the Patient Perspective and Real-World Experience in Home Dialysis Training. 家庭透析培训中患者观点和实际经验的重要性。
IF 9.8 1区 医学 Q1 UROLOGY & NEPHROLOGY Pub Date : 2025-10-13 DOI: 10.2215/cjn.0000000903
Pesh Patel
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引用次数: 0
Sepsis-Related Hospitalization and Mortality in Patients with Chronic Kidney Disease. 慢性肾脏疾病患者败血症相关住院和死亡率
IF 9.8 1区 医学 Q1 UROLOGY & NEPHROLOGY Pub Date : 2025-10-13 DOI: 10.2215/cjn.0000000861
Ninad Khandekar,Shung Chiu,Lauren Tong,Deepa Raghavan,Nishank Jain
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引用次数: 0
Bridging the "Employment Gap" for Dialysis Patients: From Association to Action. 弥合透析患者的“就业差距”:从协会到行动。
IF 9.8 1区 医学 Q1 UROLOGY & NEPHROLOGY Pub Date : 2025-10-13 DOI: 10.2215/cjn.0000000907
Karthik Tennankore,Annie-Claire Nadeau-Fredette
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引用次数: 0
How I Treat Nocturnal Home Hemodialysis - an under-prescribed but essential home dialysis modality in the United States. 我如何治疗夜间家庭血液透析——在美国,这是一种处方不足但必不可少的家庭透析方式。
IF 9.8 1区 医学 Q1 UROLOGY & NEPHROLOGY Pub Date : 2025-10-10 DOI: 10.2215/cjn.0000000927
Frank Liu,Graham Abra,Nupur Gupta,Brigitte Schiller,Matthew B Rivara
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引用次数: 0
Is Assisted Home Dialysis Feasible In the US? Addressing Legislative and Regulatory Levers. 辅助家庭透析在美国可行吗?解决立法和监管杠杆问题。
IF 9.8 1区 医学 Q1 UROLOGY & NEPHROLOGY Pub Date : 2025-10-10 DOI: 10.2215/cjn.0000000925
Yuvaram N V Reddy,Suzanne Watnick,Nupur Gupta
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引用次数: 0
Joslin Kidney Panel of Circulating Proteins: A Tool for ESKD Risk Discrimination and Individualized Diabetic Kidney Disease Treatment. 乔斯林肾循环蛋白组:ESKD风险鉴别和糖尿病肾病个体化治疗的工具。
IF 9.8 1区 医学 Q1 UROLOGY & NEPHROLOGY Pub Date : 2025-10-10 DOI: 10.2215/cjn.0000000863
Andrzej S Krolewski,Jani K Haukka,Zaipul I Md Dom,Viktor R Curovic,Chunyi Wu,Mario Luca Morieri,Katsuhito Ihara,Sok Cin Tye,Hiroki Kobayashi,Youngshin Keum,Sathishkumar Baskaran,Stefan Mutter,Simone Theilade,Eiichiro Satake,Narges Rashidi,Valma Harjutsalo,Tarunveer S Ahluwalia,Monika A Niewczas,Fergus Fleming,Marlon Pragnell,Robert G Nelson,Joseph V Bonventre,Per-Henrik Groop,Peter Rossing,Niina Sandholm,Andrzej Galecki,Alessandro Doria
BACKGROUNDTo facilitate personalized treatment of diabetic kidney disease (DKD), we developed the Joslin Kidney Panel (JKP) of 21 circulating proteins associated with progression to end-stage kidney disease (ESKD). Prognostic models using baseline concentrations of JKP proteins in circulation and clinical markers were then developed to stratify individuals according to ESKD risk and according to response to fenofibrate, a potential reno-protective drug.METHODSThe custom-made Joslin OLINK multipurpose proteomics platform was used to quantify JKP proteins. Association between baseline serum/plasma concentrations of these proteins and kidney outcomes was examined in five independent study groups.RESULTSIn Type 1 diabetes individuals from Joslin (N=59), FinnDiane (N=389), and Steno (N=283), all JKP proteins were good discriminators of ESKD risk during 10-year follow-up. Baseline concentrations of KIM-1 and WFDC2 performed the best, matching or outperforming the clinical markers. An optimal model to discriminate ESKD risk that included three clinical markers and eight JKP proteins (KIM1, TNF-R2, TNF-R3, TNF-R19L, PVRL4, WFDC2, DLL1, SYND1), was developed using the FinnDiane cohort (C-index 0.868, SE±0.019) and validated in the Steno cohort (C-index 0.913, SE±0.104) and in Type 2 diabetes Joslin study (C-index 0.807, SE±0.036). In each of these studies the optimal model performed better than models based solely on three clinical markers. In a subgroup of 450 individuals with Type 2 diabetes from the ACCORD-Lipid trial, high levels of three JKP proteins (EFNA4, DLL1, IL-1RT1) predicted amelioration of fast kidney function decline during four years of follow-up in those treated with fenofibrate compared to placebo.CONCLUSIONQuantification of circulating JKP proteins using the Joslin OLINK platform discriminates ESKD risk in individuals with diabetes and their response to reno-protective drugs. Use of this multi-purpose precision medicine tool should facilitate studies on the etiology of DKD and enable the development of effective personalized treatment protocols for individuals with DKD.
背景:为了促进糖尿病肾病(DKD)的个性化治疗,我们开发了乔斯林肾脏面板(JKP),包含21种与终末期肾病(ESKD)进展相关的循环蛋白。然后,利用循环中JKP蛋白的基线浓度和临床标志物建立预后模型,根据ESKD风险和对非诺贝特(一种潜在的肾保护药物)的反应对个体进行分层。方法采用定制的Joslin OLINK多用途蛋白质组学平台对JKP蛋白进行定量分析。在5个独立的研究组中研究了这些蛋白的基线血清/血浆浓度与肾脏预后之间的关系。结果Joslin (N=59)、FinnDiane (N=389)和Steno (N=283) 3例1型糖尿病患者在10年随访期间,JKP蛋白均为ESKD风险的良好鉴别指标。KIM-1和WFDC2的基线浓度表现最好,与临床指标相匹配或优于临床指标。采用FinnDiane队列(c -指数0.868,SE±0.019)建立了包括3个临床标志物和8个JKP蛋白(KIM1、TNF-R2、TNF-R3、TNF-R19L、PVRL4、WFDC2、DLL1、SYND1)的ESKD风险鉴别优化模型,并在Steno队列(c -指数0.913,SE±0.104)和2型糖尿病Joslin研究(c -指数0.807,SE±0.036)中进行了验证。在这些研究中,最佳模型比仅基于三个临床标志物的模型表现更好。在accord -脂质试验的450名2型糖尿病患者的亚组中,与安慰剂相比,非诺贝特治疗的4年随访期间,高水平的三种JKP蛋白(EFNA4, DLL1, IL-1RT1)预测了快速肾功能下降的改善。结论利用Joslin OLINK平台定量检测循环JKP蛋白,可区分糖尿病患者的ESKD风险及其对肾保护药物的反应。这种多用途精准医疗工具的使用将促进DKD病因学的研究,并为DKD患者制定有效的个性化治疗方案。
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引用次数: 0
Spatial Atlas Creation at the Single Cell Level: Unveiling the Human Kidney Metaverse. 单细胞水平的空间图谱创建:揭示人类肾脏的超宇宙。
IF 9.8 1区 医学 Q1 UROLOGY & NEPHROLOGY Pub Date : 2025-10-09 DOI: 10.2215/cjn.0000000924
Pierre C Dagher,Michael T Eadon,Tarek M El-Achkar
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引用次数: 0
Untangling the Web of Dietary Micronutrient Intake and the Metabolome in Children with CKD. 解开CKD儿童膳食微量营养素摄入和代谢组的网络。
IF 9.8 1区 医学 Q1 UROLOGY & NEPHROLOGY Pub Date : 2025-10-09 DOI: 10.2215/cjn.0000000908
Denver D Brown,Kristen Sgambat,Marva Moxey-Mims
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引用次数: 0
TESTING for the Best Biomarker in IgA Nephropathy. 检测IgA肾病的最佳生物标志物。
IF 9.8 1区 医学 Q1 UROLOGY & NEPHROLOGY Pub Date : 2025-10-08 DOI: 10.2215/cjn.0000000904
Richard A Lafayette
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引用次数: 0
期刊
Clinical Journal of the American Society of Nephrology
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