A Standardized Classification Scheme for Gastroduodenal Disorder Evaluation Using the Gastric Alimetry System: Prospective Cohort Study
Bibliographic record
Abstract
Background and Aims Gastric Alimetry™ (Alimetry, New Zealand) is a new clinical test for gastroduodenal disorders involving simultaneous body surface gastric electrical mapping and validated symptom profiling. Studies have demonstrated a range of distinct pathophysiological profiles, and a classification scheme is now required. We used Gastric Alimetry spectral and symptom profiles to develop a mechanism-based test classification scheme, then assessed correlations with symptom severity, psychometrics, and quality of life. Methods We performed a multicenter prospective cohort study of patients meeting the Rome IV criteria for functional dyspepsia and chronic nausea and vomiting syndromes. Patients underwent Gastric Alimetry profiling, and a standardized digital classification framework was devised and applied to separate patients into those with a) abnormal spectral analyses (ie aberrant gastric frequencies, amplitudes, and rhythms); and normal spectral analyses with b) symptoms correlated to gastric amplitude (subgroups: sensorimotor, postgastric, and activity-relieved), and c) symptoms independent of gastric amplitude (subgroups: continuous, meal-relieved, meal-induced). Results Two hundred ten patients were included (80% female, median age 37), of whom 169 met the criteria for chronic nausea and vomiting syndromes and 206 met the criteria for functional dyspepsia (79% meeting both criteria). Overall, 83% were phenotyped using the novel scheme, with 79/210 (37.6%) classified as having a spectral abnormality. Of the remainder, the most common phenotypes were "continuous pattern" (37, 17.6%), "meal-induced pattern" (28, 13.3%), and "sensorimotor pattern" (15, 7.1%). Symptom patterns independent of gastric amplitude were more strongly correlated with depression and anxiety (Patient Health Questionnaire 2: exp(β) 2.38, P = .024, State-Trait Anxiety Inventory Short-Form score: exp(β) 1.21, P = .021). Conclusion A mechanistic classification scheme for assessing gastroduodenal disorders is presented. Classified phenotypes showed independent relationships with symptom severity, quality of life, and psychological measures. The scheme is now being applied clinically and in research studies.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".