Kuo, Braden

ABSTRACT Introduction Chronic gastroduodenal disorders remain challenging to manage, and new diagnostic approaches are needed to better delineate underlying causes and guide therapeutic decisions. Body Surface Gastric Mapping (BSGM) technologies combine high‐resolution gastric myoelectrical activity measurements with symptom and psychological profiling to provide mechanistic insights into gastric motor and sensory dysfunction. An International Working Group convened to derive the first consensus classification of BSGM phenotypes (the “Auckland Classification”). Methods A Technical Group conducted a systematic literature and clinical database review to identify objective test biomarkers and candidate disease mechanisms. Evidence was synthesized across 50 studies (primarily in gastroparesis, chronic nausea and vomiting, and functional dyspepsia), and BSGM phenotypes were mapped to existing treatment guidelines. Subsequently, iterative review and development of consensus was performed by a Consensus Group composed of international clinical experts familiar with BSGM. Eleven statements underlying the classification were then derived and circulated as a final survey to establish agreement. Results Six BSGM phenotypes were endorsed: three defined by myoelectrical abnormalities (Dysrhythmic, High Frequency, and Low Meal Response) and three by characteristic symptom associations (Sensorimotor, Continuous, and Delayed Onset Symptoms). Published studies plausibly linked these phenotypes to mechanisms including interstitial cell of Cajal depletion, vagal impairment, hypomotility, visceral hypersensitivity, gut‐brain dysregulation, and small bowel dysfunction. Phenotypes were also mapped to existing mechanism‐based treatment guidelines. Ten out of the eleven statements had > 80% agreement. Conclusions The Auckland Classification, derived by international consensus, presents a structured framework for BSGM‐defined patient phenotypes. Evidence and mechanism‐based treatment options are suggested for each phenotype to provide a foundation for research, further validation, and a pathway for integrating BSGM into clinical care.

ABSTRACT Background Patients with gastroparesis (Gp) can have a variety of symptoms. Apart from use of prokinetics, symptomatic therapies for the predominant symptom (PrS) are used. Aims (1) To classify Gp patients based on their PrS; (2) To determine differences in Gp symptoms, gastric emptying (GE), quality of life (QOL), treatments, and symptom improvement among Gp patients with different PrS. Methods Gp patients were enrolled in a multicenter registry and followed for 96‐weeks. Patients recorded their PrS and completed questionnaires assessing symptoms and QOL at enrollment and at follow up visits. Results Of 1013 Gp patients (361 diabetic, 607 idiopathic, 45 post‐fundoplication), the PrS were nausea (31%), vomiting (20%), abdominal pain (20%), bloating (9%), fullness (4%), GERD (4%), constipation (3%). Abdominal pain was more often a PrS in idiopathics, whereas vomiting was more often a PrS in diabetics. QOL scores were lower in the abdominal pain PrS group. PrS was associated with greater use of directed symptomatic treatment (antiemetic agents and gastric electrical stimulation for nausea and vomiting, prokinetic agents for vomiting and fullness, and constipation medications for constipation). Of 555 patients followed over 48 weeks, GCSI improved by ≥ 1 in 26% overall, more often in patients with initial PrS of nausea (32%) and bloating (35%) and less often for initial PrS of fullness (13%) or abdominal pain (15%). Conclusions In Gp patients, the most common PrS were nausea, vomiting, and abdominal pain. PrS is associated with QOL, treatments utilized, and patient outcomes. Thus, the PrS of a patient with Gp provides useful information about their present condition and future outcome.

ABSTRACT Recent advances in the diagnosis and management of reflux disease were the central focus of the inaugural Gatherings in Esophagology (GiE), which convened experts across gastroenterology, surgery, otolaryngology, pulmonology, and basic research. The sessions highlighted innovations in reflux monitoring—including high‐resolution manometry, wireless pH monitoring, and novel salivary biomarkers—while critically evaluating their diagnostic accuracy and clinical utility. Presentations explored the limitations of traditional proton‐pump inhibitor therapy, the emergence of potassium‐competitive acid blockers as a new class of acid suppressants, and the evolving role of adjunctive treatments such as mucosal protectants, reflux reducers, and neuromodulators for refractory symptoms. The discourse extended to advanced interventional procedures, including transoral incisionless fundoplication, magnetic sphincter augmentation, and the RefluxStop device, with discussion of patient selection, efficacy, and complication management. Discussants emphasized the pathophysiology and management of extraesophageal manifestations of reflux, the interplay between reflux and pulmonary disease, and the diagnostic challenges in pediatric populations. The meeting also addressed the integration of behavioral therapies, the role of the microbiome, and the application of artificial intelligence in reflux diagnostics. Collectively, these insights underscore a shift toward precision medicine in reflux disease, emphasizing individualized diagnostic strategies and tailored therapeutic approaches to improve patient outcomes.

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.

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

AbstractIntroductionThe American Neurogastroenterology and Motility Society Gastroparesis Cardinal Symptom Index‐Daily Diary (ANMS GCSI‐DD) is a patient‐reported outcome (PRO) instrument for gastroparesis. This study evaluated the psychometric properties of the ANMS GCSI‐DD and determined a meaningful change threshold using the data from a phase 2b trial in adults with moderate‐to‐severe idiopathic or diabetic gastroparesis (DG).MethodsThe psychometric properties of ANMS GCSI‐DD were analyzed using other clinician‐ and patient‐reported outcomes from 242 patients during the 12‐week trial. Trial exit interviews were conducted in a cohort of 32 patients to capture their perspectives on meaningful change from the trial.ResultsANMS GCSI‐DD demonstrated good performance: unidimensionality scores exhibited good fit; internal consistency reliability was >0.70; test–retest reliability was above 0.90, and convergent validity showed strong correlations (0.70–0.90) with overall severity rating and moderate correlations (0.30–0.70) with other outcomes. ANMS GCSI‐DD scores discriminated among groups with varying severity of gastroparesis symptoms in known‐groups validity (p < 0.001) and were responsive to symptom improvement. Triangulation of the quantitative anchor‐based estimates of 0.9–1.4 category points as a meaningful change in the ANMS GCSI‐DD composite score, and the qualitative exit interview findings of 0.5–1.5 as meaningful change, supports a one‐point change on a five‐point scale (0–4) as the meaningful change threshold.ConclusionThe ANMS GCSI‐DD is a reliable and valid PRO instrument to employ in clinical development for patients with moderate‐to‐severe idiopathic or DG, and a one‐point score change in the ANMS GCSI‐DD composite score is recommended as a meaningful change threshold of symptom change.

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.

AbstractBackgroundGastroparesis (GP) is characterized by delayed gastric emptying in the absence of mechanical obstruction.ObjectiveGenetic predisposition may play a role; however, investigation at the genome‐wide level has not been performed.MethodsWe carried out a genome‐wide association study (GWAS) meta‐analysis on (i) 478 GP patients from the National Institute of Diabetes and Digestive and Kidney Diseases Gastroparesis Clinical Research Consortium (GpCRC) compared to 9931 population‐based controls from the University of Michigan Health and Retirement Study; and (ii) 402 GP cases compared to 48,340 non‐gastroparesis controls from the Michigan Genomics Initiative. Associations for 5,811,784 high‐quality SNPs were tested on a total of 880 GP patients and 58,271 controls, using logistic mixed models adjusted for age, sex, and principal components. Gene mapping was obtained based on genomic position and expression quantitative trait loci, and a gene‐set network enrichment analysis was performed. Genetic associations with clinical data were tested in GpCRC patients. Protein expression of selected candidate genes was determined in full thickness gastric biopsies from GpCRC patients and controls.ResultsWhile no SNP associations were detected at strict significance (p ≤ 5 × 10−8), nine independent genomic loci were associated at suggestive significance (p ≤ 1 × 10−5), with the strongest signal (rs9273363, odds ratio = 1.4, p = 1 × 10−7) mapped to the human leukocyte antigen region. Computational annotation of suggestive risk loci identified 14 protein‐coding candidate genes. Gene‐set network enrichment analysis revealed pathways potentially involved in immune and motor dysregulation (pFDR ≤ 0.05). The GP risk allele rs6984536A (Peroxidasin‐Like; PXDNL) was associated with increased abdominal pain severity scores (Beta = 0.13, p = 0.03). Gastric muscularis expression of PXDNL also positively correlated with abdominal pain in GP patients (r = 0.8, p = 0.02). Dickkopf WNT Signaling Pathway Inhibitor 1 showed decreased expression in diabetic GP patients (p = 0.005 vs. controls).ConclusionWe report preliminary GWAS findings for GP, which highlight candidate genes and pathways related to immune and sensory‐motor dysregulation. Larger studies are needed to validate and expand these findings in independent datasets.