Parameters for quantifying bolus retention with high‐resolution impedance manometry
Bibliographic record
Abstract
BACKGROUND: This study aimed to develop a methodology for quantifying esophageal bolus retention using a high-resolution esophageal impedance topography (EIT) technique. METHODS: The ability of impedance to quantify bolus retention was validated by comparison with concurrent fluoroscopic imaging (barium bolus) in 10 healthy subjects. High-resolution impedance manometry (HRIM) studies without fluoroscopy were performed in another 15 healthy subjects to define normal values using saline. HRIM data from each subject were analyzed using a MATLAB program customized for calculating the esophageal impedance integral (EII) prior to the contraction wave front as EII1 and after the contraction as EII2, and presented as a ratio of EII2/EII1, which was compared to the percent of barium areas retained in the esophagus on fluoroscopy determined by a blinded reviewer. KEY RESULTS: In 93% (37/40) of barium swallows, the results from the EIT method were in agreement with fluoroscopy results with one of three patterns: (1) 25 normal bolus transit, (2) eight bolus stasis, and (3) four retrograde escape or reflux. Three swallows (8%) had slight retention identified by EIT, but no retention detected by fluoroscopy. The correlation between percent of bolus retained in the esophagus detected by fluoroscopy and percent of bolus retention (EII2/EII1) after swallows with EIT method was r = 0.96 (p < 0.001) in supine and r = 0.69 (p < 0.001) in upright position. CONCLUSIONS & INFERENCES: The EII ratio (EII2/EII1) is a surrogate for the fraction of retained bolus after a swallow and this metric may be useful in better defining esophageal function.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".