A282 RISK FACTORS ASSOCIATED WITH UNSUCCESSFUL HIGH-RESOLUTION MANOMETRY: FAILURE IS COMMON BUT WHAT CAN WE CHANGE
Bibliographic record
Abstract
Abstract Background High-resolution manometry (HRM) is a diagnostic tool used to evaluate esophageal motor function and diagnose motility disorders. A standardized protocol is used to make an accurate diagnosis based on the Chicago Classification. Some existing literature suggests that incomplete or imperfect manometry tests are common, however; there remains a paucity of data to evaluate risk factors for failure to help clinicians determine when a study may be difficult to perform. Purpose Our goal was to quantify how often failed tests occurred and determine specific factors that may be associated with failed HRM. Method We retrospectively evaluated records for HRM tests performed over 1 year at our academic centre. Based on clinical experience, we identified several factors that may be associated with the success of HRM testing including the following: indications and symptoms leading to testing, patient’s age and biological sex, previous esophageal manometry history, previous esophageal/gastric surgery, previous septal repair/deviated septum, history of significant nausea/vomiting, history of anxiety/depression, history of irritable bowel syndrome, and medication use (opioids, proton pump inhibitors, calcium channel blockers, nitrates). We then compared patients with successful HRM vs. unsuccessful HRM with regard to our pre-specified risk factors. Result(s) 29 HRM tests were unsuccessful from a total of 152 that were performed (19% failure rate). Reasons for failure included the inability to pass the probe through LES (55%) and the inability to tolerate the manometry probe for a minimum of 10 saline swallows (45%). After separating the failed cases from successful tests, both groups had a similar distribution of age and sex. Specific symptoms and indications did not have a significant association with unsuccessful tests. A previous history of failed manometry was associated with unsuccessful HRM (OR: 15, 95% CI 1.88 to 183.8, p=0.0156). Conversely, PPI usage was associated with fewer failed HRM tests (OR: 0.37, 95% CI 0.16 to 0.90, p=0.0343). Other medical history or medication use was not found to be associated with testing failure in our study. Conclusion(s) HRM is useful for diagnosing esophageal motility disorders, but incomplete tests are common. Although this study did not identify any factors in a patient’s medical history that could be used to predict failure in patients who have never had testing, further investigations may identify if PPI therapy can make HRM testing more tolerable. Additionally, the association between previous failed HRM and repeat failures suggests that endoscopic probe placement techniques should be considered instead of retrying conventional probe placement. Please acknowledge all funding agencies by checking the applicable boxes below None Disclosure of Interest None Declared
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".