儿童高血压的定义:是否过于复杂?评估不同方法对澳大利亚儿科人群的潜在影响。

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
ACS Applied Electronic Materials Pub Date : 2024-11-01 Epub Date: 2024-07-12 DOI:10.1097/HJH.0000000000003815
Nicholas G Larkins, Catherine Choong, Markus Schlaich, Catherine Quinlan, Jonathan P Mynard, Siah Kim, Trevor A Mori, Lawrence J Beilin
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引用次数: 0

摘要

目标:美国儿科学会 (AAP) 和欧洲高血压学会 (ESH) 目前定义儿童高血压的阈值使用的是按年龄、性别和身高归一化的血压 (BP)。然而,关于年龄和身高这两个变量对准确建立血压第 95 个量值模型的相对重要性,目前还没有相关数据。我们假设,与更复杂的定义相比,仅身高一项可能同样适合人口数据。我们还比较了在澳大利亚人群中定义高血压的各种阈值的潜在影响:我们使用了雷恩研究的纵向数据,2248 名参与者在 3/5/10/14/17 年的研究访问中提供了 7479 个有效血压值。每次访问使用 Dinamap 设备测量休息 5 分钟后的血压,测量次数≥3 次。使用量子回归预测血压的第 95 百分位数,并通过受限三次样条对协变量进行非线性建模:单次就诊时,6%-16% 的幼儿超过 ESH 临界值,12%-23% 的幼儿超过 AAP 临界值。过渡到固定阈值(≥13 岁 AAP,≥16 岁 ESH)后,被认为患有高血压的男性人数增加(仅 AAP),女性人数减少。利用雷恩研究数据构建的仅以身高为解释变量的量子回归模型比仅以年龄为解释变量的模型(或两者的组合)更能预测血压:结论:根据 AAP 和 ESH 标准,高血压患病率可能存在很大差异,在青春期应用固定阈值时会出现明显的性别差异。也许没有必要同时按年龄和身高对血压进行正常化处理,因为后者能更好地预测儿童血压。在临床实践中,更简单的方法可能更可取,但需要根据临床结果进行验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Defining childhood hypertension: is it too complicated? An evaluation of the potential impact of different approaches in an Australian paediatric population.

Objectives: Current American Academy of Pediatrics (AAP) and European Society of Hypertension (ESH) thresholds defining hypertension in children use blood pressure (BP) normalised to age, sex and height. However, scare data exists regarding the relative importance of these variables to accurately model the 95th quantile of BP. We hypothesised that height alone may fit the population data equally well compared to more complex definitions. We also compare the potential impact of various thresholds for defining hypertension in an Australian population.

Methods: Longitudinal data from the Raine Study were used, with 2248 participants contributing 7479 valid BP values across the 3/5/10/14/17-year study visits. BP was measured after 5 min rest, ≥3 times at each visit, using a Dinamap device. Quantile regression was used to predict the 95th percentile of BP, with nonlinear modelling of covariates through restricted cubic spline terms.

Results: At a single visit, 6-16% of young children exceeded the ESH threshold and 12-23% the AAP threshold. The transition to fixed thresholds (≥13 years AAP, ≥16 years ESH), increased the number of males (AAP only) and reduced the number of females considered hypertensive. A quantile regression model constructed with Raine Study data using height-only as the explanatory variable better predicted BP than the respective model using age-only (or a combination of the two).

Conclusions: There may be large differences in the prevalence of hypertension according to AAP and ESH criteria, with a marked sex-discrepancy emerging from the point of fixed threshold application in adolescence. It may not be necessary to normalise BP by both age and height, the latter being a better predictor of childhood BP. Simpler methods may be preferable in clinical practice but require validation against clinical outcomes.

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CiteScore
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