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解码 IBS:一种用于心理困扰和肠脑相互作用的机器学习方法。

Decoding IBS: a machine learning approach to psychological distress and gut-brain interaction.

机构信息

Department of Biological and Medical Psychology, Universtity of Bergen, Bergen, 5020, Norway.

National Center for Functional Gastrointestinal Disorders, Department of Medicine, Haukeland University Hospital, Bergen, 5021, Norway.

出版信息

BMC Gastroenterol. 2024 Aug 15;24(1):267. doi: 10.1186/s12876-024-03355-z.

Abstract

PURPOSE

Irritable bowel syndrome (IBS) is a diagnosis defined by gastrointestinal (GI) symptoms like abdominal pain and changes associated with defecation. The condition is classified as a disorder of the gut-brain interaction (DGBI), and patients with IBS commonly experience psychological distress. The present study focuses on this distress, defined from reports of fatigue, anxiety, depression, sleep disturbances, and performance on cognitive tests. The aim was to investigate the joint contribution of these features of psychological distress in predicting IBS versus healthy controls (HCs) and to disentangle clinically meaningful subgroups of IBS patients.

METHODS

IBS patients ( ) and HCs ( ) completed the Chalder Fatigue Scale (CFQ), the Hamilton Anxiety and Depression Scale (HADS), and the Bergen Insomnia Scale (BIS), and performed tests of memory function and attention from the Repeatable Battery Assessing Neuropsychological Symptoms (RBANS). An initial exploratory data analysis was followed by supervised (Random Forest) and unsupervised (K-means) classification procedures.

RESULTS

The explorative data analysis showed that the group of IBS patients obtained significantly more severe scores than HCs on all included measures, with the strongest pairwise correlation between fatigue and a quality measure of sleep disturbances. The supervised classification model correctly predicted belongings to the IBS group in 80% of the cases in a test set of unseen data. Two methods for calculating feature importance in the test set gave mental and physical fatigue and anxiety the strongest weights. An unsupervised procedure with showed that one cluster contained 24% of the patients and all but two HCs. In the two other clusters, their IBS members were overall more impaired, with the following differences. One of the two clusters showed more severe cognitive problems and anxiety symptoms than the other, which experienced more severe problems related to the quality of sleep and fatigue. The three clusters were not different on a severity measure of IBS and age.

CONCLUSION

The results showed that psychological distress is an integral component of IBS symptomatology. The study should inspire future longitudinal studies to further dissect clinical patterns of IBS to improve the assessment and personalized treatment for this and other patient groups defined as disorders of the gut-brain interaction. The project is registered at https://classic.

CLINICALTRIALS

gov/ct2/show/NCT04296552 20/05/2019.

摘要

目的

肠易激综合征(IBS)是一种以腹痛和与排便相关的变化为特征的胃肠道(GI)症状的诊断。该疾病被归类为肠脑互动障碍(DGBI),IBS 患者通常会经历心理困扰。本研究关注这种困扰,通过疲劳、焦虑、抑郁、睡眠障碍和认知测试的表现来定义。目的是研究这些心理困扰特征对预测 IBS 与健康对照组(HC)的联合贡献,并分解 IBS 患者的有临床意义的亚组。

方法

IBS 患者( )和 HCs( )完成了 Chalder 疲劳量表(CFQ)、汉密尔顿焦虑和抑郁量表(HADS)和卑尔根失眠量表(BIS),并进行了 RBANS 中的记忆功能和注意力测试。初始探索性数据分析之后是有监督(随机森林)和无监督(K 均值)分类程序。

结果

探索性数据分析显示,IBS 患者组在所有纳入的测量中获得的严重程度评分明显高于 HCs,疲劳与睡眠质量障碍的一个质量测量之间存在最强的两两相关性。在一个看不见的数据测试集中,有监督分类模型正确预测了 80%的 IBS 组归属。在测试集中计算特征重要性的两种方法赋予精神和身体疲劳以及焦虑的权重最强。无监督程序( )显示,一个聚类包含 24%的患者和除了两个 HCs 之外的所有人。在另外两个聚类中,他们的 IBS 成员总体上受到更大的影响,以下是不同之处。其中一个聚类表现出更严重的认知问题和焦虑症状,而另一个聚类则经历了更严重的与睡眠质量和疲劳相关的问题。三个聚类在 IBS 和年龄的严重程度测量上没有差异。

结论

结果表明,心理困扰是 IBS 症状学的一个组成部分。该研究应激发未来的纵向研究,以进一步剖析 IBS 的临床模式,从而改善对这种和其他被定义为肠脑互动障碍的患者群体的评估和个性化治疗。该项目在 https://classic. 注册。

临床试验

gov/ct2/show/NCT04296552 2019 年 5 月 20 日。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fad/11325751/671e9c4aa00c/12876_2024_3355_Fig1_HTML.jpg

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