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Record W2011111646 · doi:10.4021/gr284e

Esophageal Intraepithelial Neutrophil Infiltration is Common in Nigerian Patients With Non-Erosive Reflux Disease

2011· article· en· W2011111646 on OpenAlexvenueno aff
Sylvester Chuks Nwokediuko

Bibliographic record

VenueGastroenterology Research · 2011
Typearticle
Languageen
FieldMedicine
TopicGastroesophageal reflux and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsNerdMedicineRefluxGastroenterologyGERDInternal medicineEsophagitisBiopsyEsophagusInfiltration (HVAC)Reflux esophagitisDiseasePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Non-erosive reflux disease (NERD) is a variant of gastroesophageal reflux disease (GERD) in which patients with typical reflux symptoms have no evidence of erosive esophagitis at endoscopy. An objective diagnostic tool for NERD remains an unmet need for clinicians and researchers. This study was designed to determine the types of histological alterations seen in Nigerian patients with NERD. METHODS: This was a prospective cross-sectional study in which mucosal biopsy was taken from the lower esophagus in patients with NERD. Similar biopsy was also taken from patients with nonulcer dyspepsia who served as controls. The materials were processed and examined histologically. RESULTS: There were 68 patients with NERD and 60 patients with nonulcer dyspepsia. Intraepithelial neutrophil infiltration was significantly more frequent in patients with NERD compared to those with nonulcer dyspepsia (47.1% vs 13.3%, P = 0.0326). Epithelial proliferative chnges in the form of basal cell hyperplasia and papilla elongation were minimal (11.8% and 3.3% respectively). CONCLUSIONS: Nigerian patients with NERD have a high degree of esophageal intraepithelial neutrophil infiltration and a low prevalence of epithelial proliferative changes. This may be related to the relative rarity of Barrett's esophagus in Nigerians.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.858

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.319
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2011
Admission routes1
Has abstractyes

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