首页> 美国卫生研究院文献>BMJ Open >Diagnostic accuracy of the Geriatric Depression Scale-30 Geriatric Depression Scale-15 Geriatric Depression Scale-5 and Geriatric Depression Scale-4 for detecting major depression: protocol for a systematic review and individual participant data meta-analysis
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Diagnostic accuracy of the Geriatric Depression Scale-30 Geriatric Depression Scale-15 Geriatric Depression Scale-5 and Geriatric Depression Scale-4 for detecting major depression: protocol for a systematic review and individual participant data meta-analysis

机译:老年抑郁量表-30老年抑郁量表-15老年抑郁量表5和老年抑郁量表4的诊断准确性:用于检测重度抑郁的方法:用于系统回顾的方案和个体参与者数据的荟萃分析

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摘要

IntroductionThe 30-item Geriatric Depression Scale (GDS-30) and the shorter GDS-15, GDS-5 and GDS-4 are recommended as depression screening tools for elderly individuals. Existing meta-analyses on the diagnostic accuracy of the GDS have not been able to conduct subgroup analyses, have included patients already identified as depressed who would not be screened in practice and have not accounted for possible bias due to selective reporting of results from only better-performing cut-offs in primary studies. Individual participant data meta-analysis (IPDMA), which involves a standard systematic review, then a synthesis of individual participant data, rather than summary results, could address these limitations. The objective of our IPDMA is to generate accuracy estimates to detect major depression for all possible cut-offs of each version of the GDS among studies using different reference standards, separately and among participant subgroups based on age, sex, dementia diagnosis and care settings. In addition, we will use a modelling approach to generate individual participant probabilities for major depression based on GDS scores (rather than a dichotomous cut-off) and participant characteristics (eg, sex, age, dementia status, care setting).
机译:简介建议使用30项老年抑郁量表(GDS-30)和较短的GDS-15,GDS-5和GDS-4作为老年人的抑郁症筛查工具。现有的关于GDS诊断准确性的荟萃分析无法进行亚组分析,包括已经被确定为抑郁症的患者,他们将在实践中不进行筛查,也没有考虑由于仅报告更好的结果而可能产生的偏倚-在初等研究中达到临界值。单个参与者数据的荟萃分析(IPDMA)涉及到标准的系统审查,然后对单个参与者数据进行综合而不是汇总结果,可以解决这些局限性。我们IPDMA的目的是生成准确度估算值,以在使用不同参考标准的研究之间,分别以及在年龄,性别,痴呆症诊断和护理设置的参与者亚组中检测GDS每种版本的所有可能临界值的严重抑郁。此外,我们将使用一种建模方法,根据GDS评分(而不是二分法的临界值)和参与者特征(例如性别,年龄,痴呆状况,护理环境)来生成个体严重抑郁的参与者概率。

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