White Coat Hypertension in Pregnancy: The Challenge of Combining Inconsistent Data.
White Coat Hypertension in Pregnancy: The Challenge of Combining Inconsistent Data.
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妊娠期白大衣高血压：合并不一致数据的挑战。
DOI：
10.1161/hypertensionaha.120.15056
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Countouris,Malamo
中科院分区：
文献类型：
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作者：
Roberts,JamesM;Countouris,Malamo
由于被排除研究的局限性，2020年7月只纳入了12项研究。即使在这12项研究中，除了妊娠期间评估WCH诊断的时间不同外，WCH和先兆子痫的定义和调查结果也各不相同。大多数研究没有包括动态血压测定、质量控制措施或结果掩盖的方案。使用纽卡斯尔-渥太华的研究质量衡量标准（9分最好，1分最差），只有3项研究的评分高于6分。作者指出，根据综合数据的分级推荐评估、发展和评价（GRADE）评分标准，由于偏差和不精确，他们收集的数据质量较低。不幸的是，在试图合并来自多个研究的数据以深入了解生理学、病理生理学和临床问题时，这是一个规则（而不是例外）。在一个分析大型数据集的能力比以往任何时候都强大的时代，现有数据的质量、异质性和不兼容性极大地限制了将研究结果扩展到少数研究之外的能力。如何促进数据共享？第一步是心态。在过去，很少有研究人员在进行研究时考虑到，如果他们的发现能够被分享，他们的发现的价值将会增加。此外，研究机构和资助机构并没有奖励共享数据，事实上，在一项大型研究中作为许多作者之一被认为价值极小。然而，正在采取措施解决这些问题。越来越明显的是，数据共享需要收集适当的数据和标准化的结果，并通过统一的数据集大大促进。对于妊娠期高血压，有些问题已经解决，有些问题正在进行中。最近一套标准化的数据字段、标准化的生物样本收集策略和统一的数据库已经可用，并且在标准化结果和这些结果的定义方面取得了很大进展，这些结果应该包括在这些研究中。人们可以希望这些方法成为心态的一部分
36 Hypertension July 2020 only included 12 because of the limitations of the excluded studies. Even in the 12 studies considered, in addition to the variation in times during gestation at which the diagnosis of WCH was assessed, the definitions of WCH and preeclampsia and investigated outcomes also varied. Most studies did not include the protocol for ambulatory blood pressure determinations, quality control measures or masking of findings. Using the Newcastle-Ottawa1 measure of study quality in which 9 is best and 1 is worst, only 3 studies were rated better than 6. The authors point out that the data that they assembled was of low quality by the Grading of Recommendations Assessment, Development and Evaluation (GRADE) scoring criteria of synthesized data due to bias and imprecision. This is unfortunately the rule (not the exception) in attempts to merge data from several studies to gain insight into physiology, pathophysiology, and clinical problems. At a time when the capacity for analysis of large datasets is more powerful than ever before4 the quality, heterogeneity, and incompatibility of available data strongly limit the ability to extend findings beyond at most a very few studies. What can be done to facilitate data sharing? The first step is mindset. Very few investigators in the past have performed studies with the consideration that the value of their findings would be increased if they could be shared. Further, institutions and funding agencies have not rewarded sharing data and in fact, being one author of many in a large study has been considered of minimal value. 4 There are, however, steps that are being taken to address these issues. It is becoming increasingly evident that sharing data demands the collection of appropriate data, standardized outcomes and is greatly facilitated by harmonized datasets. 4 For pregnancy hypertension, some of these topics have been addressed and some are in progress. A recent standardized set of data fields, 5 standardized biological sample collection strategies, 6 and harmonized data base7 have become available and efforts are well advanced to standardizing outcomes and the definition of these outcomes8 that should be included in such studies. One can hope that these approaches become part of the mindset