Clinical value of predicting relapse within 3 months in alcohol-dependent patients using fNIRS in verbal fluency task

利用近红外光谱技术在言语流畅性任务中预测酒精依赖患者3个月内复发的临床价值

阅读:1

Abstract

To investigate the hemodynamic differences in various brain regions between alcohol dependence (AlcD) patients and healthy controls during a verbal fluency task (VFT) using functional near-infrared spectroscopy (fNIRS), and to further explore the clinical predictive value of fNIRS before therapy for the outcome of relapse in AlcD patients after 3 months. A retrospective survey was conducted on 123 AlcD patients and 149 healthy controls during the same period. Baseline assessment of fNIRS was performed to analyze the hemodynamic differences between the two groups in different brain regions. During hospitalization, AlcD patients underwent a 3-week benzodiazepine substitution therapy, gradually tapering off the medication to achieve alcohol withdrawal treatment goals. Three months after discharge, we conducted follow-up phone calls to assess the relapse status of the patients. Compared to the control group, the AlcD group had significantly lower integral values in the frontal and bilateral temporal lobes, as well as lower β-values in all channels of the frontal lobe except for Ch13, and in all channels of the bilateral temporal lobes (p < 0.005), with no significant difference in the parietal lobe channel(p > 0.05). ROC (Receiver Operating Characteristic Curve) analysis for predicting relapse within 3 months showed that the area under the curve for all channels was highest (0.951, sensitivity 0.924, specificity 0.886). Patients with AlcD exhibit functional impairments in the frontal and temporal lobes. fNIRS channels in the frontal and parietal lobes based on VFT have good clinical predictive value for relapse within 3 months after pharmacotherapy in AlcD and can be applied in clinical practice.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。