Oravec Chesney S, Motiwala Mustafa, Reed Kevin, Jones Tamekia L, Klimo Paul
College of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
Departments of Pediatrics and Preventive Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
Pediatr Neurosurg. 2019;54(2):85-97. doi: 10.1159/000495790. Epub 2019 Feb 20.
BACKGROUND/AIMS: We sought to describe pediatric "big data" publications since 2000, their statistical output, and clinical implications.
We searched 4 major North American neurosurgical journals for articles utilizing non-neurosurgery-specific databases for clinical pediatric neurosurgery research. Articles were analyzed for descriptive and statistical information. We analyzed effect sizes (ESs), confidence intervals (CIs), and p values for clinical relevance. A bibliometric analysis was performed using several key citation metrics.
We identified 74 articles, which constituted 1.7% of all pediatric articles (n = 4,436) published, with an exponential increase after 2013 (53/74, 72%). The Healthcare Cost and Utilization Project (HCUP) databases were most frequently utilized (n = 33); hydrocephalus (n = 19) was the most common study topic. The statistical output (n = 49 studies with 464 ESs, 456 CIs, and 389 p values) demonstrated that the majority of the ESs (253/464, 55%) were categorized as small; half or more of the CI spread (CIS) values and p values were high (274/456, 60%) and very strong (195/389, 50%), respectively. Associations with a combination of medium-to-large ESs (i.e., magnitude of difference), medium-to-high CISs (i.e., precision), and strong-to-very strong p values comprised only 20% (75/381) of the reported ESs. The total number of citations for the 74 articles was 1,115 (range per article, 0-129), with the median number of citations per article being 8.5. Four studies had > 50 citations, and 2 of them had > 100 citations. The calculated h-index was 16, h-core citations were 718, the e-index was 21.5, and the Google i10-index was 34.
There has been a dramatic increase in the use of "big data" in the pediatric neurosurgical literature. Reported associations that may, as a group, be of greatest interest to practitioners represented only 20% of the total output from these publications. Citations were weighted towards a few highly cited publications.
背景/目的：我们试图描述2000年以来儿科“大数据”相关出版物、其统计数据输出以及临床意义。
我们在北美4种主要的神经外科期刊中搜索利用非神经外科特定数据库进行临床儿科神经外科研究的文章。对文章进行描述性和统计信息分析。我们分析了效应大小（ESs）、置信区间（CIs）和p值的临床相关性。使用几个关键的引用指标进行文献计量分析。
我们识别出74篇文章，占已发表的所有儿科文章（n = 4436）的1.7%，2013年后呈指数增长（74篇中的53篇，72%）。医疗成本与利用项目（HCUP）数据库使用最为频繁（n = 33）；脑积水（n = 19）是最常见的研究主题。统计数据输出（49项研究，有464个ESs、456个CIs和389个p值）表明，大多数ESs（464个中的253个，55%）被归类为小效应；一半或更多的置信区间跨度（CIS）值和p值分别为高（456个中的274个，60%）和非常强（389个中的195个，50%）。中等至大效应大小（即差异幅度）、中等至高CIS（即精度）以及强至非常强p值组合的关联仅占所报告ESs的20%（75/381）。这74篇文章的总引用次数为1115次（每篇文章的引用次数范围为0 - 129），每篇文章的引用次数中位数为8.5。4项研究的引用次数超过50次，其中2项超过100次。计算得出的h指数为16，h核心引用次数为718，e指数为21.5，谷歌i10指数为34。
儿科神经外科文献中“大数据”的使用有显著增加。所报告的关联作为一个整体，可能是从业者最感兴趣的，但仅占这些出版物总产出的20%。引用集中在少数高引用率的出版物上。
