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首页> 外文期刊>Journal of Clinical Epidemiology >A systematic review finds methodological improvements necessary for prognostic models in determining traumatic brain injury outcomes.
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A systematic review finds methodological improvements necessary for prognostic models in determining traumatic brain injury outcomes.

机译:一项系统的审查发现确定创伤性脑损伤预后模型的方法学改进是必要的。

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摘要

OBJECTIVES: To describe the modeling techniques used for early prediction of outcome in traumatic brain injury (TBI) and to identify aspects for potential improvements. STUDY DESIGN AND SETTING: We reviewed key methodological aspects of studies published between 1970 and 2005 that proposed a prognostic model for the Glasgow Outcome Scale of TBI based on admission data. RESULTS: We included 31 papers. Twenty-four were single-center studies, and 22 reported on fewer than 500 patients. The median of the number of initially considered predictors was eight, and on average five of these were selected for the prognostic model, generally including age, Glasgow Coma Score (or only motor score), and pupillary reactivity. The most common statistical technique was logistic regression with stepwise selection of predictors. Model performance was often quantified by accuracy rate rather than by more appropriate measures such as the area under the receiver-operating characteristic curve. Model validity was addressed in 15 studies, but mostly used a simple split-sample approach, and external validation was performed in only four studies. CONCLUSION: Although most models agree on the three most important predictors, many were developed on small sample sizes within single centers and hence lack generalizability. Modeling strategies have to be improved, and include external validation.
机译:目的:描述用于早期预测创伤性脑损伤(TBI)结局的建模技术,并确定可能改善的方面。研究设计与背景:我们回顾了1970年至2005年发表的研究的主要方法论方面,这些研究提出了基于入院数据的TBI格拉斯哥成果量表的预后模型。结果:我们收录了31篇论文。有24项是单中心研究,有22项报道了少于500名患者。最初考虑的预测因素的中位数为8,平均选择其中5个作为预测模型,通常包括年龄,格拉斯哥昏迷评分(或仅运动评分)和瞳孔反应性。最常用的统计技术是逻辑回归,逐步选择预测变量。模型的性能通常通过准确率来量化,而不是通过诸如接收机工作特性曲线下的面积之类的更合适的度量来量化。模型有效性在15项研究中得到解决,但大多数使用简单的分割样本方法,并且仅在四项研究中进行了外部验证。结论:尽管大多数模型都同意三个最重要的预测因素,但许多预测因素都是在单个中心的小样本规模上开发的,因此缺乏可概括性。建模策略必须改进,包括外部验证。

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