Can the Clinical History Distinguish Between Organic and Functional Dyspepsia?
Bibliographic record
Abstract
CONTEXT: Upper gastrointestinal symptoms occur in 40% of the population. An accurate diagnosis would help rationalize investigation and treatment. OBJECTIVE: To systematically review the literature of the accuracy of primary care physicians, gastroenterologists, or computer models in diagnosing organic dyspepsia. DATA SOURCES: A search of Cochrane Controlled Trials Register (December 2003), MEDLINE (1966-December 2003), EMBASE (1988-December 2003), and CINAHL (1982-December 2003) for studies that reported on cohorts of patients attending for endoscopy that had symptoms, clinical opinion, or both recorded before investigation. STUDY SELECTION: Studies that prospectively compared the diagnosis reached by a clinician, computer model, or both with results of upper gastrointestinal endoscopy in adult patients with upper gastrointestinal symptoms. DATA EXTRACTION: Two authors independently assessed studies (n = 79) for eligibility and abstracted data for estimating likelihood ratios (LRs) of clinical opinion, computer models, or both in diagnosing an organic cause for dyspepsia. DATA SYNTHESIS: Fifteen studies were identified that evaluated 11 366 patients, with 4817 patients (42%) classified as having organic dyspepsia. The computer models performed similarly to the clinician; therefore, the 2 approaches were combined. The diagnosis reached by the clinician or computer model suggesting organic dyspepsia had an LR of 1.6 (95% confidence interval [CI], 1.4-1.8), and a negative result decreased the likelihood of organic dyspepsia (LR, 0.46; 95% CI, 0.38-0.55). A diagnosis of peptic ulcer disease performed similarly with an LR of 2.2 (95% CI, 1.9-2.6), but an evaluation that suggested the absence of peptic ulcer disease had an LR of 0.45 (95% CI, 0.38-0.53). A clinical history suggesting esophagitis had an LR of 2.4 (95% CI, 1.9-3.0) vs a negative history that had an LR of 0.50 (95% CI, 0.42-0.60). CONCLUSION: Neither clinical impression nor computer models that incorporated patient demographics, risk factors, history items, and symptoms adequately distinguished between organic and functional disease in patients referred for endoscopic evaluation of dyspepsia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".