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Record W4402335402 · doi:10.1016/j.gastha.2024.09.002

A Standardized Classification Scheme for Gastroduodenal Disorder Evaluation Using the Gastric Alimetry System: Prospective Cohort Study

2024· article· en· W4402335402 on OpenAlexaff
Chris Varghese, Gabriel Schamberg, Emma Uren, Stefan Calder, Mikaela Law, Daphne Foong, Vincent Ho, Billy Wu, I‐Hsuan Huang, Peng Du, Thomas L. Abell, Charlotte Daker, Christopher N. Andrews, Armen A. Gharibans, Gregory O’Grady

Bibliographic record

VenueGastro Hep Advances · 2024
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsUniversity of Calgary
FundersHealth Research Council of New ZealandNational Institutes of HealthRoyal Australasian College of Surgeons
KeywordsMedicineProspective cohort studyCohortInternal medicineGastroenterology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score0.793

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.035
GPT teacher head0.356
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2024
Admission routes1
Has abstractyes

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