Gastric dysfunction in patients with chronic nausea and vomiting syndromes defined by a noninvasive gastric mapping device
Bibliographic record
Abstract
Chronic nausea and vomiting syndromes (NVSs) are prevalent and debilitating disorders. Putative mechanisms include gastric neuromuscular disease and dysregulation of brain-gut interaction, but clinical tests for objectively defining gastric motor function are lacking. A medical device enabling noninvasive body surface gastric mapping (BSGM) was developed and applied to evaluate NVS pathophysiology. BSGM was performed in 43 patients with NVS and 43 matched controls using Gastric Alimetry (Alimetry), a conformable high-resolution array (8 × 8 electrodes; 20-mm interelectrode spacing), wearable reader, and validated symptom-logging app. Continuous measurement encompassed a fasting baseline (30 minutes), 482-kilocalorie meal, and 4-hour postprandial recording, followed by spectral and spatial biomarker analyses. Meal responses were impaired in NVS, with reduced amplitudes compared to controls (median, 23.3 microvolts versus 38.0 microvolts, P < 0.001), impaired fed-fasting power ratios (1.1 versus 1.6, P = 0.02), and disorganized slow waves (spatial frequency stability, 13.6 versus 49.5; P < 0.001). Two distinct NVS subgroups were evident with indistinguishable symptoms (all P > 0.05). Most patients (62%) had normal BSGM studies with increased psychological comorbidities (43.5% versus 7.7%; P = 0.03) and anxiety scores (median, 16.5 versus 13.0; P = 0.035). A smaller subgroup (31%) had markedly abnormal BSGM, with biomarkers correlating with symptoms (nausea, pain, excessive fullness, early satiety, and bloating; all r > 0.35, P < 0.05). Patients with NVS share overlapping symptoms but comprise distinct underlying phenotypes as revealed by a BSGM device. These phenotypes correlate with symptoms, which should inform clinical management and therapeutic trial design.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".