Bibliographic record
Abstract
PURPOSE OF REVIEW: A variety of organic diseases can cause dyspepsia, but most patients with epigastric pain have functional dyspepsia. As dyspepsia is common and usually has a benign cause, it is not possible to fully investigate everyone with epigastric pain. Current recommendations suggest that young patients without alarm symptoms can be treated empirically with Helicobacter pylori test and treat and proton pump inhibitor therapy can be offered to those who are negative or remain symptomatic despite treatment for their H. pylori. Patients who remain symptomatic with this strategy may be investigated with endoscopy, but most will have functional dyspepsia. RECENT FINDINGS: There are a large number of trials for prokinetic therapy in functional dyspepsia, but treatment efficacy is uncertain, as there is evidence of publication bias. There are very limited data for the effectiveness of tricyclic antidepressants in functional dyspepsia. There has been recent interest in the observation that patients with functional dyspepsia have increased eosinophils in the duodenum and this may be accompanied by other subtle manifestations of upregulated mucosal immunity. It is possible that this is being driven by a dietary substance or by a change in the upper gut microbiome. SUMMARY: The initial management of dyspepsia is well established, but how to manage those who do not respond is a challenge. Future studies evaluating diet and altering the gut microbiome may give clinicians more therapeutic options.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
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".