The effect of a sitting <i>vs</i> supine posture on normative esophageal pressure topography metrics and Chicago Classification diagnosis of esophageal motility disorders
Bibliographic record
Abstract
BACKGROUND: Although, the current protocol for high resolution manometry (HRM) using the Chicago Classification is based on the supine posture, some practitioners prefer a sitting posture. Our aims were to establish normative esophageal pressure topography data for the sitting position and to determine the effect of applying those norms to Chicago Classification diagnoses. METHODS: Esophageal pressure topography studies including test swallows in both a supine and sitting position of 75 healthy volunteers and 120 patients were reviewed. Integrated relaxation pressure (IRP), distal contractile integral (DCI), contractile front velocity (CFV), and distal latency were measured and compared between postures. Normative ranges were established from the healthy volunteers and the effect of applying sitting normative values to the patients was analyzed. KEY RESULTS: Normative values of IRP, DCI, and CFV all decreased significantly in the sitting posture. Applying normative sitting metrics to patient studies [27% reduction in IRP (15 to 11 mmHg), 69% reduction in DCI (8000-2500 mmHg-s-cm)] reclassified 13/120 (11%) patients as having abnormal esophagogastric junction relaxation and 26/120 (22%) as hypercontractile. Three patients with an abnormal supine IRP normalized when sitting with elimination of a vascular artifact. CONCLUSIONS & INFERENCES: Clinical HRM studies should include both a supine and sitting position to minimize misdiagnoses attributable to anatomical factors. However, until outcome studies demonstrating the significance of isolated abnormalities of IRP or DCI in the sitting position are available, the Chicago Classification of esophageal motility disorders should continue to be based on supine swallows using normative data from the supine posture.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".