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在非透析和透析慢性肾脏病患者中,容量负荷和血管机制对高血压的相对潜在贡献。

The relative potential contribution of volume load and vascular mechanisms to hypertension in non-dialysis and dialysis chronic kidney disease patients.

作者信息

Tade Grace, Hsu Hon-Chun, Robinson Chanel, Dlongolo Noluntu, Teckie Gloria, Solomon Ahmed, Dessein Patrick Hector

机构信息

Cardiovascular Pathophysiology and Genomics Research Unit, Faculty of Health Sciences, School of Physiology, University of the Witwatersrand, Johannesburg, South Africa.

Nephrology Unit, Milpark Hospital, Johannesburg, South Africa.

出版信息

Front Cardiovasc Med. 2024 Apr 15;11:1377887. doi: 10.3389/fcvm.2024.1377887. eCollection 2024.

DOI:10.3389/fcvm.2024.1377887
PMID:38689863
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11060794/
Abstract

BACKGROUND

Hypertension is highly prevalent and particularly difficult to treat adequately in patients with chronic kidney disease (CKD). The relative contribution of volume overload and vascular mechanisms to blood pressure measures in CKD and whether these effects differ in non-dialysis compared to dialysis patients is unknown.

METHODS

We determined the potential impact of volume load (stroke volume) and vascular mechanisms (inverse of total arterial compliance (inv TAC) and systemic vascular resistance (SVR)) on mean and brachial and aortic systolic blood pressures in 67 non-dialysis and 48 dialysis chronic kidney disease (CKD) patients. Relationships were determined in confounder adjusted regression models.

RESULTS

Stroke volume ( value = 0.003) was more strongly associated with mean arterial pressure than SVR ( value = 0.9) ( value for difference = 0.03). When stroke volume and SVR were entered in the same regression model (model = 0.324), they contributed equally to the variation in mean arterial pressure ( value for difference = 0.5). Stroke volume ( value ≤ 0.002) and inv TAC ( value ≤ 0.001) contributed equally to the variation in systolic pressures ( value for difference ≥ 0.9). When stroke volume and inv TAC were entered in the same regression model (model = 0.752 to 0.765), they contributed equally to the variation in systolic blood pressures ( value for difference = 0.7). Stroke volume, TAC and SVR were similar ( value ≥ 0.5) and associated to the same extent with blood pressure measures in non-dialysis and dialysis CKD patients ( value for difference ≥ 0.1). In receiver operator characteristic curve analysis, elevated systolic blood pressure was determined by stroke volume ( value = 0.005) and inv TAC ( value = 0.03) but not SVR ( value = 0.8). The calculated power of the study was 0.999 based on  = 0.05.

CONCLUSIONS

The present investigation suggests that both volume load and vascular mechanisms should be considered in the management of hypertension among patients with CKD. The extent and relative potential impact of volume load and vascular mechanisms on blood pressure measures are as large in non-dialysis compared to dialysis CKD patients.

摘要

背景

高血压在慢性肾脏病(CKD)患者中极为常见,且难以得到充分治疗。容量超负荷和血管机制对CKD患者血压测量的相对贡献,以及这些影响在非透析患者与透析患者中是否存在差异尚不清楚。

方法

我们测定了67例非透析和48例透析慢性肾脏病(CKD)患者的容量负荷(每搏输出量)和血管机制(总动脉顺应性倒数(inv TAC)和全身血管阻力(SVR))对平均血压、肱动脉收缩压和主动脉收缩压的潜在影响。在调整混杂因素的回归模型中确定相关性。

结果

每搏输出量(P值 = 0.003)与平均动脉压的相关性比SVR(P值 = 0.9)更强(差异P值 = 0.03)。当将每搏输出量和SVR纳入同一回归模型时(模型R² = 0.324),它们对平均动脉压变化的贡献相同(差异P值 = 0.5)。每搏输出量(P值≤0.002)和inv TAC(P值≤0.001)对收缩压变化的贡献相同(差异P值≥0.9)。当将每搏输出量和inv TAC纳入同一回归模型时(模型R² = 0.752至0.765),它们对收缩压变化的贡献相同(差异P值 = 0.7)。非透析和透析CKD患者的每搏输出量、TAC和SVR相似(P值≥0.5),与血压测量的关联程度相同(差异P值≥0.1)。在受试者工作特征曲线分析中,收缩压升高由每搏输出量(P值 = 0.005)和inv TAC(P值 = 0.03)决定,而非SVR(P值 = 0.8)。基于α = 0.05,该研究计算出的检验效能为0.999。

结论

本研究表明,在CKD患者高血压管理中应同时考虑容量负荷和血管机制。与透析CKD患者相比,非透析CKD患者中容量负荷和血管机制对血压测量的影响程度和相对潜在影响同样大。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bff/11060794/a870cc6f21db/fcvm-11-1377887-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bff/11060794/ff9bc9d30c33/fcvm-11-1377887-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bff/11060794/e067beeb4e8d/fcvm-11-1377887-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bff/11060794/a870cc6f21db/fcvm-11-1377887-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bff/11060794/ff9bc9d30c33/fcvm-11-1377887-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bff/11060794/e067beeb4e8d/fcvm-11-1377887-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bff/11060794/a870cc6f21db/fcvm-11-1377887-g003.jpg

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