Browsing by Subject "Gastric emptying"

Now showing 1 - 3 of 3
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    Baseline Predictors of Longitudinal Changes in Symptom Severity and Quality of Life in Patients with Suspected Gastroparesis
    (Elsevier, 2022) Lee, Allen A.; Rao, Krishna; Parkman, Henry P.; McCallum, Richard W.; Sarosiek, Irene; Nguyen, Linda A.; Wo, John M.; Schulman, Michael I.; Moshiree, Baharak; Rao, Satish; Kuo, Braden; Hasler, William L.; Medicine, School of Medicine
    Background & aims: Whether gastric emptying tests predict longitudinal outcomes in patients with symptoms of gastroparesis is unclear. We aimed to determine whether baseline gastric emptying tests and gut motility parameters could impact longitudinal symptom(s) and quality of life (QOL) in a prospective, observational cohort study of patients with symptoms of gastroparesis. Methods: One hundred fifty patients with gastroparesis symptoms underwent simultaneous scintigraphy (GES) and wireless motility capsule (WMC) measurement of gastric emptying and other motility parameters. Patient Assessment of Upper Gastrointestinal Symptoms and Quality of Life were administered at baseline, and 3 and 6 months after testing. Multivariable generalized linear marginal models were fit to determine which baseline parameters predict longitudinal changes in symptoms and QOL. Results: Overall upper GI symptoms and QOL scores were moderate in severity at baseline and significantly improved over 6 months. Clinical variables, including female gender, harder stools by Bristol stool form score, and presence of functional dyspepsia (FD) by Rome III criteria, were predictive of more severe upper GI symptoms. Even after controlling for these clinical factors, delayed gastric emptying by GES or WMC was associated with worse symptom severity and QOL scores. Low gastric and elevated small bowel contractile parameters by WMC were also independently associated with more severe upper GI symptoms and worse QOL scores. Conclusions: Baseline features, including demographic and clinical variables, delayed gastric emptying and abnormal gastrointestinal contractility, were independent predictors of more severe longitudinal symptoms and worse quality of life outcomes. These factors may help to risk stratify patients and guide treatment decisions.
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    Delayed Gastric Emptying Is Not Associated with a Microbiological Diagnosis of Small Intestinal Bacterial Overgrowth
    (Springer, 2021) Calderon, Gerardo; Siwiec, Robert M.; Bohm, Matthew E.; Nowak, Thomas V.; Wo, John M.; Gupta, Anita; Xu, Huiping; Shin, Andrea; Medicine, School of Medicine
    Background: Clinical symptoms of patients with small intestinal bacterial overgrowth (SIBO) may overlap with symptoms of gastroparesis. Prior studies suggest delayed small intestinal transit is associated with SIBO, but have not shown an association between delayed gastric emptying and SIBO. However, these studies have generally relied on the indirect method of breath testing to diagnose SIBO. Aims: The aim of this study was to examine the association between a microbiological diagnosis of SIBO and delayed gastric emptying by scintigraphy. Methods: In a single-center retrospective study of previous research participants who presented for small bowel enteroscopy for diagnostic evaluation of SIBO, we identified 73 participants who underwent gastric emptying study by scintigraphy. A microbiological diagnosis of SIBO was made in patients based on culture results of jejunal aspirates. Clinical symptoms were assessed using the total gastroparesis cardinal symptom index (GCSI) score. We compared delayed gastric emptying, 2- and 4-h gastric retention, and gastroparesis symptoms between patients with and without a microbiological diagnosis of SIBO. Key results: Among 29 participants with SIBO and 44 without SIBO, 33 (45%) had evidence of delayed gastric emptying. There was no significant association between a microbiological diagnosis of SIBO and delayed gastric emptying by scintigraphy. Percent retained at 2 and 4 h, and total GCSI scores did not differ significantly between those with and without SIBO. Conclusions: Although delayed gastric emptying is common in patients with suspected SIBO, gastric emptying is not associated with a microbiological diagnosis of SIBO.
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    Predicting Response to Neuromodulators or Prokinetics in Patients With Suspected Gastroparesis Using Machine Learning: The "BMI, Infectious Prodrome, Delayed GES, and No Diabetes" Model
    (Wolters Kluwer, 2024-09-01) Takakura, Will; Surjanhata, Brian; Nguyen, Linda Anh Bui; Parkman, Henry P.; Rao, Satish S. C.; McCallum, Richard W.; Schulman, Michael; Wo, John Man-Ho; Sarosiek, Irene; Moshiree, Baha; Kuo, Braden; Hasler, William L.; Lee, Allen A.; Medicine, School of Medicine
    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.