Research protocol for the Paraesophageal hernia symptom tool, a prospective multi-center cohort study to identify the need and threshold for surgery and assess the symptom response to surgery
Bibliographic record
Abstract
Large hiatus hernias with a significant paraesophageal component (types II-IV) have a range of insidious symptoms. Management of symptomatic hernias includes conservative treatment or surgery. Currently, there is no paraesophageal hernia disease-specific symptom questionnaire. As a result, many clinicians rely on the health-related quality of life questionnaires designed for gastro-esophageal reflux disease (GORD) to assess patients with hiatal hernias pre- and postoperatively. In view of this, a paraesophageal hernia symptom tool (POST) was designed. This POST questionnaire now requires validation and assessment of clinical utility. Twenty-one international sites will recruit patients with paraesophageal hernias to complete a series of questionnaires over a five-year period. There will be two cohorts of patients-patients with paraesophageal hernias undergoing surgery and patients managed conservatively. Patients are required to complete a validated GORD-HRQL, POST questionnaire, and satisfaction questionnaire preoperatively. Surgical cohorts will also complete questionnaires postoperatively at 4-6 weeks, 6 months, 12 months, and then annually for a total of 5 years. Conservatively managed patients will repeat questionnaires at 1 year. The first set of results will be released after 1 year with complete data published after a 5-year follow-up. The main results of the study will be patient's acceptance of the POST tool, clinical utility of the tool, assessment of the threshold for surgery, and patient symptom response to surgery. The study will validate the POST questionnaire and identify the relevance of the questionnaire in routine management of paraesophageal hernias.
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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 | 0.047 | 0.042 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.099 | 0.029 |
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".