背景:压力的诊断通常涉及使用问卷,问卷可以提供有偏见的结果。更可靠的方法依赖于精神科医生对个体症状的观察,这耗时且不适用于大规模筛查测试。这项研究建立了气相色谱-离子迁移谱(GC-IMS)和电子鼻(电子鼻)的替代方法,以基于汗液顶部空间中高挥发性化合物的指纹进行快速压力筛查。所调查的样本来自154名女护士志愿者,他们还提供了基于问卷的心理健康评分数据,并获得了精神科医生确认的高压力病例。
结果:精神科医生的访谈显示14名志愿者压力很大。将他们的腋窝汗液样本以及来自32名低/中等压力护士(对照)的汗液样本收集到棉棒上,并用GC-IMS进行分析。基于准确度数据选择可能的标记峰。它们被初步鉴定为氨,二乙醚,甲醇,辛烷值,戊烷,丙酮和二甲胺可能涉及不同的内源性机制或与局部微生物群的关系。使用偏最小二乘判别分析进一步分析数据,接收器工作特性曲线显示最佳精度,灵敏度和选择性为87%,86%和88%,分别。如果样品是从护士那里获得的,没有除臭剂的使用,高应力病例可以使用电子鼻传感器进行筛查,准确率为89%。传感器响应可以与GC-IMS中的标记峰面积数据相关,系数范围从-0.70到0.80。
结论:这代表了汗液中高挥发性化合物标记物用于高应激筛查的首次研究。建立的方法简单,可靠,快速和非侵入性,它可以进一步适应电子鼻传感器的便携式平台,并在实际应用中对PhraNakornSiAyutthaya医院的护士进行筛查测试,泰国。
BACKGROUND: Diagnosis of stress generally involves uses of questionnaires which can provide biased results. The more reliable approach relies on observation of individual symptoms by psychiatrists which is time consuming and could not be applicable for massive scale screening tests. This research established alternative approaches with gas chromatography-ion mobility spectrometry (GC-IMS) and electronic nose (e-nose) to perform fast stress screening based on fingerprinting of highly volatile compounds in headspaces of
sweat. The investigated samples were obtained from 154 female nurse volunteers who also provided the data of questionnaire-based mental health scores with the high stress cases confirmed by psychiatrists.
RESULTS: The interviews by psychiatrists revealed 14 volunteers with high stress. Their axillary
sweat samples and that from 32 nurses with low/moderate stress (controls) were collected onto cotton rods and analysed with GC-IMS. The possible marker peaks were selected based on the accuracy data. They were tentatively identified as ammonia, diethyl ether, methanol, octane, pentane, acetone and dimethylamine which could involve different endogenous mechanisms or the relationships with the local microbiomes. The data were further analysed using partial least squares discriminant analysis with the receiver operating characteristic curves showing the optimum accuracy, sensitivity and selectivity of 87%, 86% and 88%, respectively. Providing that the samples were obtained from the nurses without deodorant uses, the high stress cases could be screened using e-nose sensors with the accuracy of 89%. The sensor responses could be correlated with the marker peak area data in GC-IMS with the coefficients ranging from -0.70 to 0.80.
CONCLUSIONS: This represents the first investigation of highly volatile compound markers in
sweat for high stress screening. The established methods were simple, reliable, rapid and non-invasive, which could be further adapted into the portable platform of e-nose sensors with the practical application to perform the screening tests for nurses in Phra Nakorn Si Ayutthaya hospital, Thailand.