Guideline Adherence in Dyspepsia Investigation and Treatment
Bibliographic record
Abstract
Introduction: The impact of dyspepsia guidelines on clinical practice may be poor. Provider adherence with dyspepsia guidelines was examined to determine their impact on clinical practice. Methods: Provider adherence with the 2005 American College of Gastroenterology Guidelines for the Management of Dyspepsia and the 2017 American College of Gastroenterology and Canadian Association of Gastroenterology joint Dyspepsia Management Guidelines was assessed on a national level using data from the National Ambulatory Medical Care Survey (NAMCS). Patient visit data, including reason for visit of dyspepsia, diagnosis of dyspepsia, or diagnosis of H. pylori infection from NAMCS years 2012 through 2015, were used. Provider adherence with dyspepsia management guidelines was determined based upon provision of at least one recommended test or treatment for dyspepsia. Results: Providers appeared to adhere to the 2005 ACG guidelines for 49.7% of patient visits. Providers appeared to adhere to the 2017 ACG/CAG guidelines for 51.0% of patient visits. Conclusions: Provider adherence with the 2005 ACG and the 2017 ACG/CAG Dyspepsia Management Guidelines was determined to be low in this study, highlighting the need to increase evidence-based medical treatment and efficient resource use for dyspepsia.
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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 | 0.028 | 0.118 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".