ABSTRACT Background Patients with gastric dysmotility exhibit abnormal transit and reduced contractility, for which quantification is limited with current methodologies. The Atmo Capsule is a wireless motility capsule that measures regional gastrointestinal transit. We tested its technical capabilities to evaluate gastric contractility by detecting changes in capsule acceleration during transit. Methods Data from 91 healthy controls and 182 patients with suspected dysmotility who ingested the Atmo Capsule following a standardized protocol were included. Gastric emptying times (GET) ≥ 5 h were considered delayed. Contraction frequencies (cycles per minute [cpm]) and amplitudes (as arbitrary units [au]) were identified following Fast Fourier Transformation of accelerometer data using 5‐min windows and were assessed in 30‐min windows post‐ingestion (early gastric phase) and before gastric emptying (late gastric phase). Data were compared via ANOVA, using Bonferroni corrections, between healthy controls, patients with normal gastric emptying, and patients with delayed gastric emptying. Key Results Gastric emptying was delayed in 53/182 (29%) patients. Three cpm contraction frequencies were identified across both gastric phases in controls and patients. Contraction amplitudes did not differ between groups in the early gastric phase. In the late phase, mean amplitudes were lower in patients with delayed gastric emptying (6.4 au) compared with subjects with normal gastric emptying (controls, 9.7 au, p < 0.0001; patients, 8.6 au, p < 0.0001). Conclusions & Inference The Atmo Capsule enables precise quantification of gastric contraction profiles, permitting differentiation of normal from pathological motor patterns. Findings of this technical assessment support its potential for evaluating gastric physiology and detecting pathophysiological patterns of gastric dysmotility.
Impact of Constipation Therapies on Severity of Gastroparesis and Constipation Symptoms in Relation to Gastric and Colonic Transit
ABSTRACTIntroductionStudies demonstrate an overlap of constipation with gastroparesis and functional dyspepsia, but the impact of treatments that target constipation on improving upper gastrointestinal (UGI) symptoms is unexplored. We quantified the effects of constipation medication therapies on UGI and constipation symptom severity in subjects presenting with symptoms of gastroparesis.MethodsFifty‐six subjects with symptoms of gastroparesis underwent concurrent wireless motility capsule and gastric emptying scintigraphy and were recommended to receive either a new medication therapy for constipation or a change in constipation therapy based on investigator interpretation of test results. Gastroparesis Cardinal Symptom Index (GCSI), upper abdominal pain, and constipation scores were compared between baseline and 6 months. Data were compared between delayed or non‐delayed gastric emptying and the presence or absence of slow colonic transit.Key ResultsSubjects with slow colonic transit had improvements in GCSI (p = 0.007) and constipation scores (p = 0.004) after treatment with a new or changed constipation medication, with the delayed emptying subgroup driving GCSI improvements (p = 0.004). Reductions in nausea/vomiting (p = 0.02) and early satiety/fullness subscores (p = 0.002) with trends to improved bloating/distention subscores (p = 0.06) were observed in this subgroup, but upper abdominal pain was unchanged. Subjects with normal colonic transit showed no improvement in GCSI scores regardless of gastric emptying status (p > 0.05).Conclusions and InferencesIdentifying and treating delayed colonic transit in gastroparetic (delayed gastric emptying) subjects improves global UGI symptoms as well as selected individual symptoms. Evaluation of whole gut motility as well as recognizing and managing extragastric delay may promote improved outcomes in these patients.Trial RegistrationClinicalTrials.gov: NCT02022826
Predicting Response to Neuromodulators or Prokinetics in Patients With Suspected Gastroparesis Using Machine Learning: The “BMI, Infectious Prodrome, Delayed GES, and No Diabetes” Model
INTRODUCTION: Pharmacologic therapies for symptoms of gastroparesis (GP) have limited efficacy, and it is difficult to predict which patients will respond. In this study, we implemented a machine learning model to predict the response to prokinetics and/or neuromodulators in patients with GP-like symptoms. METHODS: Subjects with suspected GP underwent simultaneous gastric emptying scintigraphy (GES) and wireless motility capsule and were followed for 6 months. Subjects were included if they were started on neuromodulators and/or prokinetics. Subjects were considered responders if their GP Cardinal Symptom Index at 6 months decreased by ≥1 from baseline. A machine learning model was trained using lasso regression, ridge regression, or random forest. Five-fold cross-validation was used to train the models, and the area under the receiver operator characteristic curve (AUC-ROC) was calculated using the test set. RESULTS: Of the 150 patients enrolled, 123 patients received either a prokinetic and/or a neuromodulator. Of the 123, 45 were considered responders and 78 were nonresponders. A ridge regression model with the variables, such as body mass index, infectious prodrome, delayed gastric emptying scintigraphy, no diabetes, had the highest AUC-ROC of 0.72. The model performed well for subjects on prokinetics without neuromodulators (AUC-ROC of 0.83) but poorly for those on neuromodulators without prokinetics. A separate model with gastric emptying time, duodenal motility index, no diabetes, and functional dyspepsia performed better (AUC-ROC of 0.75). DISCUSSION: This machine learning model has an acceptable accuracy in predicting those who will respond to neuromodulators and/or prokinetics. If validated, our model provides valuable data in predicting treatment outcomes in patients with GP-like symptoms.
Predictors of irritable bowel syndrome‐like symptoms in quiescent inflammatory bowel disease
AbstractBackgroundMany patients with quiescent inflammatory bowel disease (IBD) suffer from irritable bowel syndrome (IBS)‐like symptoms. Although these symptoms cause significant reductions in quality of life, evidence‐based treatments are lacking as risk factors and pathophysiology of these symptoms are not clearly defined. We aimed to identify risk factors for development of IBS‐like symptoms in IBD patients with quiescent disease.MethodsWe performed a single‐center retrospective cohort study of adults with IBD from 2015 to 2021. Quiescent IBD was defined by a fecal calprotectin level <250 μg/g of stool or endoscopic evidence of quiescent disease. Cox regression was performed to identify variables that were independently associated with the incident development of IBS‐like symptoms in IBD patients.Key ResultsA total of 368 IBD patients were included for analysis, including 278 patients with UC and 88 with Crohn's disease. 15.5% of quiescent IBD patients developed IBS symptoms, with an incidence rate of (95% CI 48.0–82.0) 63.3 per 1000 person‐years. In the multivariate model, mood disorders (including anxiety and depression) and Crohn's disease were associated with increased risk for developing IBS symptoms. Male sex and higher iron levels conferred lower risk for developing IBS symptoms. Results from the multivariable model were similar in sensitivity analysis with quiescent IBD defined by fecal calprotectin level <150 mcg/g.Conclusions & InferencesMood disorder and Crohn's disease were positively associated with IBS‐like symptoms in quiescent IBD, whereas male sex and iron levels were protective. Our results were robust to different fecal calprotectin levels, arguing against inflammation as a mechanism for IBS‐like symptoms. This data suggests noninflammatory mechanisms may be important in the pathogenesis of IBS‐like symptoms in quiescent IBD. Future work may address whether modifying these risk factors may alter disease course.