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通过活动记录仪诊断原发性失眠——数据选择改善结果

Diagnosis of primary insomnia by actigraphy--improved results by data selection.

作者信息

Rajna Péter, Takács Johanna

出版信息

Ideggyogy Sz. 2014 Jan 30;67(1-2):43-51.

PMID:24654446
Abstract

STUDY OBJECTIVES

In spite of the useful information provided by actigraphy in sleep medicine it is still not an independent tool either in the clinical diagnosis or in the follow-up. In the frame of a retrospective study, a simple new method of data reduction was applied with the aim of improving the clinical impact of actigraphy for the diagnosis of primary insomnia.

METHODS

Actigraphic records with a duration of 1 week produced on 47 subjects who met the inclusion-exclusion criteria. The daily activities during the investigational period were registered by means a self-completed questionnaire. Three parameters (sleep latency, sleep fragmentation and sleep efficiency) and only their three 'worse - as regards insomnia' daily values were analyzed statistically. The study participants comprised 13 healthy controls, 17 healthy 'bad sleepers' and 17 subjects with primary insomnia.

RESULTS

The post-hoc tests did not reveal statistically significant difference in the three parameters between the healthy and 'bad sleeper' groups, but these two groups differed statistically from the primary insomnia group.

CONCLUSION

The actigraphic analysis of sleep latency, sleep fragmentation and sleep efficacy allows a significant differentiation between subjects with primary insomnia and healthy controls, but not between healthy controls and healthy 'bad sleepers'. Statistical algorithms indicated 'models' for clinically good and bad sleepers. Further studies on large populations are necessary before this method can be introduced in the routine medical care of individuals with primary insomnia.

摘要

研究目的

尽管活动记录仪在睡眠医学中提供了有用信息,但它在临床诊断或随访中仍不是一个独立工具。在一项回顾性研究框架内,应用了一种简单的新数据简化方法,旨在提高活动记录仪对原发性失眠诊断的临床影响。

方法

对47名符合纳入-排除标准的受试者进行了为期1周的活动记录仪记录。通过一份自我填写的问卷记录调查期间的日常活动。对三个参数(睡眠潜伏期、睡眠片段化和睡眠效率)及其仅三个“就失眠而言更差”的每日值进行了统计分析。研究参与者包括13名健康对照者、17名健康的“睡眠不佳者”和17名原发性失眠患者。

结果

事后检验未显示健康组和“睡眠不佳者”组在这三个参数上有统计学显著差异,但这两组与原发性失眠组在统计学上有差异。

结论

对睡眠潜伏期、睡眠片段化和睡眠效率进行活动记录仪分析可显著区分原发性失眠患者和健康对照者,但无法区分健康对照者和健康的“睡眠不佳者”。统计算法表明了临床睡眠良好者和睡眠不佳者的“模型”。在将该方法引入原发性失眠患者的常规医疗护理之前,有必要对大量人群进行进一步研究。

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