High Intraepithelial Eosinophil Counts in Esophageal Squamous Epithelium Are Not Specific for Eosinophilic Esophagitis in Adults
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: The histologic criterion of >20 eosinophils per high power field (hpf) is presently believed to establish the diagnosis of idiopathic eosinophilic esophagitis (IEE). This is based on data that the number of intraepithelial eosinophils in gastroesophageal reflux disease (GERD) is less than 20/hpf. This study tests this belief. METHODS: Pathology records were searched for patients who had an eosinophil count >20/hpf in an esophageal biopsy. This patient population was biased toward adults with GERD who had routine multilevel biopsies of the esophagus. The clinical, radiological, and manometric data and biopsies were studied. RESULTS: Forty patients out of a total of 3,648 reports examined had an eosinophil count >20/hpf in squamous epithelium of an esophageal biopsy. Analysis of these 40 cases indicated that 6 (15%) patients had IEE, 2 (5%) had coincident IEE and GERD, 28 (70%) had GERD, and 2 (5%) each had achalasia and diverticulum. There was no significant difference among these groups in terms of maximum eosinophil number, biopsy levels with >20 esoinophils/hpf, presence of eosinophilic microabscesses, involvement of surface layers by eosinophils, and severity of basal cell hyperplasia and dilated intercellular spaces. CONCLUSION: All histologic features presently ascribed to IEE can occur in other esophageal diseases, notably GERD. As such, the finding of intraepithelial eosinophilia in any number is not specific for IEE. When a patient with GERD has an esophageal biopsy with an eosinophil count >20/hpf, it does not mean that the patient has IEE.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it