Effects of Age on Esophageal Motility: A High-Resolution Manometry Study
Bibliographic record
Abstract
BACKGROUND: Studies have found possible physiologic changes to esophageal motility with aging currently not taken into account in routine high-resolution manometry (HRM) interpretation. We aimed to quantify the relationship between these physiologic changes and aging to improve HRM interpretation. METHODS: We conducted a retrospective analysis of patients who underwent HRM at a tertiary hospital center between 2015 and 2019. Inclusion criteria were patients aged ≥18 years with normal HRM. Exclusion criteria were abnormal HRM, abnormal upper digestive endoscopy or imagery. Outcomes were median integrated relaxation pressure (IRP), lower esophageal sphincter (LES) pressure, distal contractal integral (DCI), distal latency (DL), and peristaltic break (PB) according to the v4.0 Chicago classification criteria. Effect of age was examined through univariate and multivariate linear regression analysis. RESULTS: We identified 1,917 patients with HRM and included 722 patients with normal exams (median age 56 years (interquartile range (IQR) 46 - 66), 63.8% female). Indications for HRM included dysphagia (39.6%), gastroesophageal reflux disease (29.5%), and chest pain (11.5%). There was statistically significant relationship between age and IRP (r = 0.20, P < 0.0001) as well as DCI (r = 0.12, P = 0.001) and DL (r = -0.09, P = 0.02). No statistically significant relationship was found between age and LES pressure or PB. CONCLUSION: We found that IRP, DCI, and to a lesser extent, DL, are significantly correlated with the normal aging process in symptomatic patients. These findings should be taken into consideration when interpreting esophageal HRM.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".