Visible and near-infrared spectra collected from the thumbs of patients with chronic fatigue syndrome for diagnosis.
Visible and near-infrared spectra collected from the thumbs of patients with chronic fatigue syndrome for diagnosis.
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DOI：
10.1016/j.cca.2012.05.004
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发表时间：
2012-10
期刊：
影响因子：
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通讯作者：
A. Sakudo;H. Kuratsune;Y. Kato;K. Ikuta
中科院分区：
文献类型：
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作者：
A. Sakudo;H. Kuratsune;Y. Kato;K. Ikuta
背景目前，慢性疲劳综合征（CFS）的诊断是基于临床症状，因此依赖于医生的经验和技能。在这里，我们已经研究了可能的诊断CFS的基础上光谱信息和化学计量学分析，方法采用可见-近红外光谱（Vis-NIR）技术对拇指在600- 1100 nm波长范围内的变化进行分析和评价。对57例CFS患者和74名健康志愿者的拇指近红外光谱进行主成分分析和SIMCA分析，建立CFS患者和健康人的多变量模型。通过预测120个测定值（健康组60个，CFS患者组60个）进一步评估模型。PCA模型预测了掩蔽样本的区分度; SIMCA模型准确预测了60个中的51个，（83.3%）的健康志愿者和42 60（70%）CFS患者。结论尽管参与本试验的受试者人数相对较少，他们都是日本人，我们的研究结果表明，可见-近红外光谱的拇指结合化学计量学分析可能提供一个有价值的工具，诊断CFS。
BACKGROUNDCurrently, diagnosis of chronic fatigue syndrome (CFS) is based on clinical symptoms and therefore relies on the experience and skill of the doctors. Here, we have examined the possible diagnosis of CFS based on spectral information and chemometrics analysis, such as principal component analysis (PCA) and soft modeling of class analogy (SIMCA).METHODSVisible and near-infrared (Vis-NIR) spectroscopy was used to examine possible changes in the region of 600–1100nm in thumbs and assessed.RESULTSThe Vis-NIR spectra of thumbs from 57 CFS patients and 74 healthy volunteers were subjected to PCA and SIMCA to develop multivariate models to discriminate between CFS patients and healthy individuals. The model was further assessed by the prediction of 120 determinations (60 in the healthy group and 60 in the CFS patient group). The PCA model predicted a discrimination of the masked samples; specifically the SIMCA model correctly predicted 51 of 60 (83.3%) healthy volunteers and 42 of 60 (70%) CFS patients.CONCLUSIONSDespite the relatively small number of subjects involved in this trial, who were exclusively Japanese, our results imply that Vis-NIR spectroscopy of the thumb combined with chemometrics analysis may provide a valuable tool for diagnosing CFS.