Health Services, University of Liverpool, Liverpool, UK.
Mersey Care NHS Foundation Trust, Liverpool, UK.
Int J Geriatr Psychiatry. 2018 Apr;33(4):561-575. doi: 10.1002/gps.4852. Epub 2018 Jan 22.
The aim of this review is to determine whether automated computerised tests accurately identify patients with progressive cognitive impairment and, if so, to investigate their role in monitoring disease progression and/or response to treatment.
Six electronic databases (Medline, Embase, Cochrane, Institute for Scientific Information, PsycINFO, and ProQuest) were searched from January 2005 to August 2015 to identify papers for inclusion. Studies assessing the diagnostic accuracy of automated computerised tests for mild cognitive impairment (MCI) and early dementia against a reference standard were included. Where possible, sensitivity, specificity, positive predictive value, negative predictive value, and likelihood ratios were calculated. The Quality Assessment of Diagnostic Accuracy Studies tool was used to assess risk of bias.
Sixteen studies assessing 11 diagnostic tools for MCI and early dementia were included. No studies were eligible for inclusion in the review of tools for monitoring progressive disease and response to treatment. The overall quality of the studies was good. However, the wide range of tests assessed and the non-standardised reporting of diagnostic accuracy outcomes meant that statistical analysis was not possible.
Some tests have shown promising results for identifying MCI and early dementia. However, concerns over small sample sizes, lack of replicability of studies, and lack of evidence available make it difficult to make recommendations on the clinical use of the computerised tests for diagnosing, monitoring progression, and treatment response for MCI and early dementia. Research is required to establish stable cut-off points for automated computerised tests used to diagnose patients with MCI or early dementia.
本综述旨在确定自动化计算机测试是否能准确识别进行性认知障碍患者，如果可以，那么进一步研究其在监测疾病进展和/或治疗反应中的作用。
从 2005 年 1 月至 2015 年 8 月，我们检索了 6 个电子数据库（Medline、Embase、Cochrane、ISI、PsycINFO 和 ProQuest）以确定纳入的文献。纳入评估自动化计算机测试对轻度认知障碍（MCI）和早期痴呆与参考标准对比的诊断准确性的研究。如果可能，计算灵敏度、特异性、阳性预测值、阴性预测值和似然比。使用诊断准确性研究质量评估工具评估偏倚风险。
纳入了 16 项评估 11 种用于 MCI 和早期痴呆的诊断工具的研究。没有研究符合纳入用于监测进行性疾病和治疗反应的工具的标准。研究的总体质量良好。然而，评估的测试种类繁多，诊断准确性结果的报告不规范，因此无法进行统计分析。
一些测试在识别 MCI 和早期痴呆方面显示出有前景的结果。然而，样本量小、研究缺乏可重复性以及缺乏可用证据等问题使得难以就计算机测试的临床应用提出诊断、监测进展和治疗反应的建议。需要开展研究以确定用于诊断 MCI 或早期痴呆患者的自动化计算机测试的稳定截断值。
