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慢性肾脏病II - IV期患者的肾功能、骨骼健康及血管钙化:一项为期2 - 3年的骨活检前瞻性研究

Kidney function, bone health, and vascular calcifications in patients with CKD II - IV: A 2 - 3 year prospective study with bone biopsies.

作者信息

Malluche Hartmut H, Qiao Qi, Lima Florence, Chen Jin, Issa Mohamed, Pienkowski David

出版信息

Clin Nephrol. 2025 Feb;103(2):71-85. doi: 10.5414/CN111603.

Abstract

BACKGROUND

Patients with chronic kidney disease (CKD) have serum, bone, and vascular abnormalities presenting as chronic kidney disease-mineral bone disorder (CKD-MBD) syndrome. This study sought to identify the parameters with the greatest relative impact on progression of CKD-MBD abnormalities.

MATERIALS AND METHODS

This prospective study measured 237 parameters including serum markers, clinical variables, dual-energy X-ray absorptiometry (DXA) measurements, vascular calcifications, and histomorphometric results from bone samples obtained at baseline and after 2 - 3 years. Relative impact of these parameters on kidney function, bone changes, and vascular calcification were assessed using machine learning, a subset of artificial intelligence analyses.

RESULTS

Baseline estimated glomerular filtration rate (eGFR) values ranged from 18 to 70 mL/min and declined in 52% of subjects by at least 3.3% annually during the study. These declines in eGFR were associated with changes in specific serum markers, bone quantity decreases, and bone quality alterations, but not with arterial calcifications. Arterial calcifications were associated with collagen crosslinking heterogeneity, serum phosphorus, diuretics and atorvastatin treatment, but not with kidney function. Baseline collagen crosslinking heterogeneity was an important factor impacting progression of coronary, but not aortic calcification. Baseline serum phosphorus was a factor primarily associated with progression of aortic calcification.

CONCLUSION

Machine learning revealed specific bone and vascular abnormalities occurring early during loss of kidney function. Bone, vascular, blood, medication use, and other parameters were identified impacting the presence and progression of arterial calcification and altering bone quality and quantity in this understudied patient population. Serum phosphorus levels considered normal impacted progression of arterial calcification. Identification of these parameters and their relative importance enhances our understanding of CKD progression and should improve patient care.

摘要

背景

慢性肾脏病(CKD)患者存在血清、骨骼和血管异常,表现为慢性肾脏病-矿物质和骨异常(CKD-MBD)综合征。本研究旨在确定对CKD-MBD异常进展影响最大的相关参数。

材料与方法

这项前瞻性研究测量了237项参数,包括血清标志物、临床变量、双能X线吸收法(DXA)测量、血管钙化以及在基线和2至3年后获取的骨样本的组织形态计量学结果。使用机器学习(人工智能分析的一个子集)评估这些参数对肾功能、骨骼变化和血管钙化的相对影响。

结果

基线估计肾小球滤过率(eGFR)值范围为18至70 mL/分钟,在研究期间52%的受试者每年下降至少3.3%。这些eGFR的下降与特定血清标志物的变化、骨量减少和骨质量改变有关,但与动脉钙化无关。动脉钙化与胶原交联异质性、血清磷、利尿剂和阿托伐他汀治疗有关,但与肾功能无关。基线胶原交联异质性是影响冠状动脉而非主动脉钙化进展的重要因素。基线血清磷是主要与主动脉钙化进展相关的一个因素。

结论

机器学习揭示了肾功能丧失早期出现的特定骨骼和血管异常。在这个研究较少的患者群体中,确定了影响动脉钙化的存在和进展以及改变骨质量和骨量的骨骼、血管、血液、药物使用和其他参数。被认为正常的血清磷水平影响动脉钙化的进展。识别这些参数及其相对重要性可增强我们对CKD进展的理解,并应改善患者护理。

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