Manometric parameters, when measured with the 3‐dimensional high‐definition anorectal manometry probe, poorly predict prolonged balloon expulsion time
Bibliographic record
Abstract
BACKGROUND: There are little data evaluating the performance of the 3-dimensional high-definition anorectal manometry (3D-HDAM) system in the diagnosis of dyssynergic defecation. Physical properties of the thicker, rigid, 3D-HDAM probe may have implications on the measurements of anorectal pressures. AIM: Our aim was to compare 3D-HDAM to balloon expulsion test and magnetic resonance (MR) defecography. METHODS: Consecutive constipated patients referred for anorectal function testing at the Calgary Gut Motility Centre (Calgary, Canada) between 2014 and 2019 were assessed. All patients underwent anorectal manometry with the 3D-HDAM probe, and a subset underwent BET or MR defecography. Anorectal manometric variables were compared between patients who had normal and abnormal BET. RESULTS: Over the study period, 81 patients underwent both 3D-HDAM and BET for symptoms of constipation. 52 patients expelled the balloon within 3 minutes. Patients with abnormal BET had significantly lower rectoanal pressure differential (RAPD) (-61 vs. -31 mmHg for normal BET, p = 0.03) and defecation index (0.29 vs. 0.56, p = 0.03). On logistic regression analysis, RAPD (OR: 0.99, 95% CI: 0.97-0.99, p = 0.03) remained a negative predictor of abnormal BET. On ROC analysis, RAPD had an AUC of 0.65. There was good agreement between dyssynergic patterns on 3D-HDAM and defecographic evidence of dyssynergia (sensitivity 80%, specificity 90%, PLR 9, NLR 0.22, accuracy 85%). CONCLUSIONS: Manometric parameters, when measured with the 3D-HDAM probe, poorly predict prolonged balloon expulsion time. RAPD remains the best predictor of prolonged balloon expulsion time. The 3D-HDAM probe may not be the ideal tool to diagnose functional defecatory disorders.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".