Electrogastrography Abnormalities in Pediatric Gastroduodenal Disorders
Bibliographic record
Abstract
ABSTRACT: Electrogastrography (EGG) is a non-invasive method of measuring gastric electrophysiology. Abnormal gastric electrophysiology is thought to contribute to disease pathophysiology in patients with gastroduodenal symptoms but this has not been comprehensively quantified in pediatric populations. This study aimed to quantify the abnormalities in gastric electrophysiology on EGG in neonatal and pediatric patients.Databases were systematically searched for articles utilizing EGG in neonatal and pediatric patients (≤18 years). Primary outcomes were prevalence of abnormality, percentage of time in normal rhythm, and power ratio. Secondary outcomes were correlations between patient symptoms and abnormal gastric electrophysiology on EGG.A total of 33 articles (1444 participants) were included. EGG methodologies were variable. Pooled prevalence of abnormalities on EGG ranged from 61% to 86% in patients with functional dyspepsia (FD), gastro-esophageal reflux disease (GERD), and type 1 diabetes mellitus (T1DM). FD patients averaged 20.8% (P = 0.011) less preprandial and 21.6% (P = 0.031) less postprandial time in normogastria compared with controls. Electrophysiological abnormalities were inconsistent in GERD. T1DM patients averaged 46.2% (P = 0.0003) less preprandial and similar (P = 0.32) postprandial time in normogastria compared with controls, and had a lower power ratio (SMD -2.20, 95% confidence interval [CI]: -4.25 to -0.15; P = 0.036). Symptom correlations with gastric electrophysiology were inconsistently reported.Abnormalities in gastric electrophysiology were identifiable across a range of pediatric patients with gastroduodenal symptoms on meta-analysis. However, techniques have been inconsistent, and standardized and more reliable EGG methods are desirable to further define these findings and their potential utility in clinical practice.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".