BODY SURFACE GASTRIC MAPPING DELINEATES SPECIFIC PATIENT PHENOTYPES IN ADOLESCENTS WITH FUNCTIONAL DYSPEPSIA AND GASTROPARESIS
Bibliographic record
Abstract
ABSTRACT Importance Persistent upper gastroduodenal symptoms, such as nausea, vomiting, bloating, and abdominal pain, are widespread among pediatric patients. Multiple overlapping symptoms complicate the diagnostic process, necessitating the development of novel gastric function tests with actionable biomarkers. Body Surface Gastric Mapping (BSGM) has emerged as a promising diagnostic tool for gastroduodenal disorders, and this is the first detailed evaluation in adolescents. Objective This study aimed to assess the utility of BSGM in delineating specific patient phenotypes among adolescents with functional dyspepsia (FD) and gastroparesis in order to guide clinical decision-making. Design A prospective cross-sectional study recruited adolescents aged 12 to 21 between 2022 and 2024. Setting Controls were recruited from New Zealand (controls) and Patients from the Children’s Hospital of Philadelphia, USA. Participants Prospectively recruited participants included controls without gastroduodenal symptoms or motility-related medication usage and patients diagnosed with either gastroparesis (delayed gastric emptying test (GET)) or FD according to ROME IV criteria and a normal GET. Procedures BSGM was performed using a standardized protocol, including simultaneous symptom reporting and the completion of validated symptom, psychometric and physical health questionnaires. Main Outcome The primary outcome was to evaluate if BSGM could delineate specific patient phenotypes and provide clinically meaningful distinctions between gastroparesis and FD diagnoses, utilizing BSGM spectral outcome data. Results Fifty-six subjects were recruited (31 controls, 25 patients); median age 16; 96% of patients were female. Control data showed that adult reference intervals provided an acceptable interpretation framework. Patients with FD (n=10) and gastroparesis (n=15) had common symptoms, mental health, quality of life and functional disability (all p>0.05). Three distinct BSGM phenotypes were identified: BSGM Normal (n=10), BSGM Delay (n=8), and Low Stability/Low Amplitude (n=7), having spectral differences in BMI-Adjusted Amplitude 34.6 vs 39.1 vs 19.9 ( p =.01) and Gastric Alimetry Rhythm Index: 0.45 vs 0.45 vs 0.19 ( p =.003). BSGM phenotypes demonstrated differences in symptoms (nausea p =0.04), physical health ( p =.04) and psychometrics (anxiety p =.03). Conclusion and Relevance Adolescent patients with FD and gastroparesis have overlapping clinical profiles, making individualized treatment challenging. Conversely, employing BSGM to categorize patients into distinct phenotypes revealed clinically relevant differences, offering potential avenues for individualized therapeutic pathways.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".