Measuring dyspepsia-related health in randomized trials: the Severity of Dyspepsia Assessment (SODA) and its use in treatment with NSAIDs and COX-2-specific inhibitors
Bibliographic record
Abstract
Dyspepsia is a common problem that is important from the perspectives of both patient health and economics. While there has been variability in the definitions used to describe dyspepsia, there have also been few standardized outcomes tools designed to measure dyspepsia-related health, especially in relation to changes in dyspepsia over time. An evaluative tool was developed, the Severity of Dyspepsia Assessment (SODA), which takes into account the multidimensional nature of dyspepsia using three scales (Pain, Non-pain Symptoms, and Satisfaction with Dyspepsia-related Health) and demonstrates good psychometric properties with respect to validity, reliability and sensitivity to change in the measurement of dyspepsia-related health. Although originally developed for the assessment of uninvestigated dyspepsia, the validation of SODA for use in clinical trials suggested its ability to compare treatment effects of non-specific non-steroidal anti-inflammatory drugs (NSAIDs) and cyclooxygenase (COX)-2-specific inhibitors. In comparative trials of celecoxib or valdecoxib with non-specific NSAIDs, COX-2-specific inhibitors were demonstrated to have superior dyspepsia tolerability than non-specific NSAIDs. These data demonstrate that SODA is an effective instrument for measuring dyspepsia-related health with a broad range of applications.
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 | 0.171 | 0.222 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".