Intraluminal pressure patterns in the human colon assessed by high-resolution manometry
Bibliographic record
Abstract
Assessment of colonic motor dysfunction is rarely done because of inadequate methodology and lack of knowledge about normal motor patterns. Here we report on elucidation of intraluminal pressure patterns using High Resolution Colonic Manometry during a baseline period and in response to a meal, in 15 patients with constipation, chronically dependent on laxatives, 5 healthy volunteers and 9 patients with minor, transient, IBS-like symptoms but no sign of constipation. Simultaneous pressure waves (SPWs) were the most prominent propulsive motor pattern, associated with gas expulsion and anal sphincter relaxation, inferred to be associated with fast propagating contractions. Isolated pressure transients occurred in most sensors, ranging in amplitude from 5-230 mmHg. Rhythmic haustral boundary pressure transients occurred at sensors about 4-5 cm apart. Synchronized haustral pressure waves, covering 3-5 cm of the colon occurred to create a characteristic intrahaustral cyclic motor pattern at 3-6 cycles/min, propagating in mixed direction. This activity abruptly alternated with erratic patterns resembling the segmentation motor pattern of the small intestine. High amplitude propagating pressure waves (HAPWs) were too rare to contribute to function assessment in most subjects. Most patients, dependent on laxatives for defecation, were able to generate normal motor patterns in response to a meal.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".