The Value of Alarm Features in Identifying Organic Causes of Dyspepsia
Bibliographic record
Abstract
The unaided clinical diagnosis of dyspepsia is of limited value in separating functional dyspepsia from clinically relevant organic causes of dyspepsia (gastric and esophageal malignancies, peptic ulcer disease and complicated esophagitis). The identification of one or more alarm features, such as weight loss, dysphagia, signs of gastrointestinal bleeding, an abdominal mass or age over 45 years may help identify patients with a higher risk of organic disease. This review summarizes the frequency of alarm symptoms in dyspeptic patients in different settings (such as the community, primary care and specialist clinics). The prevalence of alarm features in patients diagnosed with upper gastrointestinal malignancy or peptic ulcer disease is described. The probability of diagnosing clinically relevant upper gastrointestinal disease in patients presenting with alarm features and other risk factors is discussed. Alarm features such as age, significant weight loss, use of nonsteroidal anti-inflammatory drugs, signs of bleeding and dysphagia may help stratify dyspeptic patients and help optimize the use of endoscopy resources.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".