Intercellular space dilatations as histological markers in gastroesophageal reflux disease: a review.
Bibliographic record
Abstract
Abstract Despite its high prevalence in the general population, the diagnosis of Gastroesophageal Reflux Disease (GERD) remains a current challenge. The Montreal and Lyon consensus guidelines provide significant assistance in schematizing this problem; however, their recommendations and protocols cannot be applied in centers where the sophisticated methodology proposed does not exist, such as in Community Hospitals. For nearly six decades, the histological method has been used, with various approaches and success, as a useful procedure in the diagnosis of GERD. Nevertheless, although its description and methodology also date back to that time, the analysis and evaluation of Dilated Intercellular Spaces (DIS) as a histological marker of microscopic esophagitis has been scarcely considered. DIS appear wherever there is damage to the esophageal mucosa, generally caused by refluxed acid and/or alkali, regardless of whether endoscopic lesions are present or not. In this regard, they have been found in very high percentages in erosive GERD but also, with lower frequency, in non-erosive GERD, whether refractory to PPIs or not. The finding of DIS in Hypersensitive Esophagus (physiological pH-metry) is very surprising, and with much lower frequency, similar to that of controls, in Functional Heartburn. This could be explained by the high sensitivity of DIS, which appear even under conditions of minimal or physiological reflux. This review proposes the determination of DIS for the diagnosis of microscopic esophagitis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".