LAQV/REQUIMTE, Departamento de Ciências Químicas, Faculdade de Farmácia, Universidade do Porto, Rua Jorge de Viterbo Ferreira 228, 4050-313, Porto, Portugal.
BoneLab, Laboratory for Bone Metabolism and Regeneration, Faculdade de Medicina Dentária, Universidade do Porto, Rua Dr. Manuel Pereira da Silva, 4200-393, Porto, Portugal.
Eat Weight Disord. 2020 Aug;25(4):1111-1115. doi: 10.1007/s40519-019-00721-9. Epub 2019 Jun 5.
Eating disorders (EDs) are characterized by a persistent disturbance of eating patterns, leading to poor psychological and physical health. EDs' symptoms are diverse, but their biochemical manifestations can be identified in biofluids, as the gingival crevicular fluid (GCF). The development of a rapid and accurate analytical diagnostic technique, able to provide a wider comprehension of established biochemical abnormalities, would greatly assist EDs' management. Mid-infrared (MIR) spectroscopy gathers all the referred features, and is considered a fingerprint technique. In this pilot trial, the GCF discrimination of patients with EDs and controls was accessed through MIR spectroscopy, further elucidating the relevant spectral differences between both groups.
GCF was collected from 20 women with ED diagnosis and from age-matched controls. Principal component analysis and partial least squares discriminant analysis (PLSDA) were conducted on GCF MIR spectra. Different PLSDA models were considered to address the predictive capability regarding patient identification, sampling site, and presence of EDs.
MIR spectroscopy was capable to discriminate GCF samples, between EDs and controls, with 84.1% of correct predictions. Regression coefficient vectors' analyses revealed that major differences were related to higher protein content in EDs.
Whether further studies are needed to validate the attained data, GCF MIR analysis may be regarded as an innovative, fast, and low-cost technique to assist on early diagnosis and clinical follow-up of EDs' patients.
Level IV, case-control trial.
饮食失调(EDs)的特征是饮食模式持续紊乱,导致心理和身体健康状况不佳。EDs 的症状多种多样,但它们的生化表现可以在生物流体中识别出来,如牙龈沟液(GCF)。开发一种快速准确的分析诊断技术,能够更全面地了解已确立的生化异常,将极大地有助于 EDs 的管理。中红外(MIR)光谱汇集了所有相关特征,被认为是一种指纹技术。在这项初步试验中,通过 MIR 光谱对 ED 患者和对照组的 GCF 进行了区分,进一步阐明了两组之间相关的光谱差异。
从 20 名 ED 诊断患者和年龄匹配的对照组中采集 GCF。对 GCF MIR 光谱进行主成分分析和偏最小二乘判别分析(PLSDA)。考虑了不同的 PLSDA 模型,以解决关于患者识别、采样部位和 EDs 存在的预测能力问题。
MIR 光谱能够区分 ED 患者和对照组的 GCF 样本,正确预测率为 84.1%。回归系数向量分析表明,主要差异与 EDs 中更高的蛋白质含量有关。
无论是否需要进一步研究来验证所获得的数据,GCF MIR 分析都可以被视为一种创新、快速且低成本的技术,有助于 ED 患者的早期诊断和临床随访。
IV 级,病例对照试验。