Cognitive function in patients with irritable bowel syndrome: impairment is common and only weakly correlated with depression/anxiety and severity of gastrointestinal symptoms.

OBJECTIVE: To investigate cognitive function in patients with irritable bowel syndrome (IBS) and its relation to anxiety/depression and severity of gastrointestinal (GI) symptoms. METHODS: Patients with IBS (n = 65) and healthy controls (HCs, n = 37) performed the ten subtests of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Age-normed index scores of five cognitive domains (Immediate memory, Visuospatial function, Language function, Attention, Recall) and a total (Fullscale) score were derived from the performance. Emotional function was assessed using the Hospital Anxiety and Depression Scale (HADS), and the IBS Symptom Scoring System (IBS-SSS) was used to define the severity of GI symptoms. RESULTS: Patients with IBS reported significantly higher scores than the HC group on symptom measures of anxiety and depression, and significantly lower scores on the Immediate memory, Recall, and Fullscale RBANS indexes. Approximately 30% of the IBS patients obtained index scores at least one standard deviation below the population mean, and more than 50% scored above the screening threshold for an anxiety disorder. The severity of GI symptoms was significantly correlated with the severity level of anxiety symptoms (p=.006), but neither the severity level of emotional nor GI symptoms was significantly correlated with the RBANS index scores in the IBS group. CONCLUSION: Cognitive and emotional function were more severely affected in patients with IBS than in HCs. The weak correlation between the two functional areas suggests that both should be assessed as part of a clinical examination of patients with IBS.

Cognitive and emotional function should be assessed in patients with IBS.Cognitive impairment was less closely related to symptoms of anxiety/depression and severity of GI symptoms than expected.An independent contribution of both emotional symptoms and cognitive function should be considered when developing treatment programs for patients with IBS.

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

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 ( n = 49 ) and HCs ( n = 28 ) 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 K = 3 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.

Assessment of Self-Reported Executive Function in Patients with Irritable Bowel Syndrome Using a Machine-Learning Framework.

Introduction: Irritable bowel syndrome (IBS) is characterized as a disorder of the gut-brain interaction (DGBI). Here, we explored the presence of problems related to executive function (EF) in patients with IBS and tested the relative importance of cognitive features involved in EF. Methods: A total of 44 patients with IBS and 22 healthy controls (HCs) completed the Behavior Rating Inventory of Executive Function (BRIEF-A), used to identify nine EF features. The PyCaret 3.0 machine-learning library in Python was used to explore the data, generate a robust model to classify patients with IBS versus HCs and identify the relative importance of the EF features in this model. The robustness of the model was evaluated by training the model on a subset of data and testing it on the unseen, hold-out dataset. Results: The explorative analysis showed that patients with IBS reported significantly more severe EF problems than the HC group on measures of working memory function, initiation, cognitive flexibility and emotional control. Impairment at a level in need of clinical attention was found in up to 40% on some of these scales. When the nine EF features were used as input to a collection of different binary classifiers, the Extreme Gradient Boosting algorithm (XGBoost) showed superior performance. The working memory subscale was consistently selected with the strongest importance in this model, followed by planning and emotional control. The goodness of the machine-learning model was confirmed in an unseen dataset by correctly classifying 85% of the IBS patients. Conclusions: The results showed the presence of EF-related problems in patients with IBS, with a substantial impact of problems related to working memory function. These results suggest that EF should be part of an assessment procedure when a patient presents other symptoms of IBS and that working memory function should be considered a target when treating patients with the disorder. Further studies should include measures of EF as part of the symptom cluster characterizing patients with IBS and other DGBIs.