O56 An evaluation of gastric alimetry® body surface gastric mapping compared to electrogastrography spectral analysis
Bibliographic record
Abstract
Background Although Electrogastrography (EGG) is a non-invasive method of evaluating gastric motility, it has limited clinical utility. Gastric Alimetry® (GA) is a novel diagnostic test that aims to address the limitations of the EGG through the combination of high-resolution body surface gastric mapping (BGSM) and validated symptom profiling. To measure performance differences in spectral analysis, the current study directly evaluated EGG with BSGM. Methods 178 subjects (110 controls; 68 nausea and vomiting (NVS) and/or type 1 diabetes (T1D)) completed the standard methodologies for GA BSGM and EGG, with identical data collection. Protocolized evaluations were completed between tests, with statistical evaluations for group-level differences, symptom correlations, and patient-level classifications. The BSGM tests gave Gastric Alimetry Rhythm IndexTM (GA-RI), Principal Gastric Frequency (PGF), BMI-Adjusted Amplitude, and Fed:Fasted Amplitude Ratio, while EGG tests gave the% time normal frequency, dominant frequency, amplitude, and amplitude ratio as final spectral metrics. A blinded consensus panel reference standard1 and published reference values2 were used for the patient-level classifications. Results Group-level: BSGM showed tighter frequency ranges vs EGG in controls (median 3.04 cpm (IQR 2.90–3.18) vs 2.88 (1.50–3.12); p<0.0001). Both tests were able to detect rhythm instability in NVS (p<0.001) and T1D (p<0.05), but EGG displayed opposing frequency effects in T1D (2.50 vs controls 2.88; p=0.28) to BSGM (3.15 vs 3.04; p=0.0004). Symptom correlations: GA-RI correlated with nausea, pain, bloating, and total symptom burden; PGF deviation with excessive fullness, pain and bloating;% time in normal frequency correlated with bloating (p<0.05). Patient-level: EGG sensitivity was 1.0, specificity 0.38; BSGM sensitivity 1.0, specificity 0.96 (figure 1). Conclusions and Inferences The limited clinical utility of EGG is demonstrated by its ability to detect group-level differences but not the correlations between symptoms or accurate patient-level classification. Therefore, compared to EGG, BSGM showed considerable improvements across each area. References Gharibans AA, et al. Sci Transl Med. Varghese C, et al. Am J Gastroenterol.
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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 | 0.002 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".