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Record W4212841762 · doi:10.1093/jcag/gwab049.130

A131 ESOPHAGEAL MUCOSAL BIOPSIES FOR THE DIAGNOSIS OF NON-EROSIVE REFLUX DISEASE: A SYSTEMATIC REVIEW AND META-ANALYSIS

2022· review· en· W4212841762 on OpenAlexaff
David M. Rodrigues, Jay Kataria, Daniel Rivera

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2022
Typereview
Languageen
FieldMedicine
TopicEosinophilic Esophagitis
Canadian institutionsQueen's University
Fundersnot available
KeywordsNerdMedicineGERDGastroenterologyRefluxEsophagitisInternal medicineAsymptomaticAmbulatoryBiopsyHeartburnEndoscopyDisease

Abstract

fetched live from OpenAlex

Abstract Background Non-erosive reflux disease (NERD) accounts for over half of all cases of gastroesophageal reflux disease (GERD). It is characterized by symptoms of GERD with pathologic acid exposure on ambulatory pH monitoring and no evidence of erosive esophagitis on upper endoscopy. Symptoms and negative endoscopy alone are insufficient to diagnose NERD. Ambulatory pH monitoring is limited due to availability and patient tolerance. Conventional histologic analysis of mucosal esophageal biopsies has been studied in this context but there is no clear guidance as to its utility in diagnosing NERD. Aims The purpose of this study was to conduct a systematic review and meta-analysis to determine the sensitivity and specificity of esophageal biopsy histology in diagnosing NERD. Methods Data were obtained from Embase (1947- April 2021) and Ovid MEDLINE (1946 – April 2021). We included all studies where esophageal mucosal biopsies were taken and light microscopy was used to analyze histopathology in symptomatic adult NERD patients (i.e., no evidence of erosive esophagitis and ambulatory pH testing confirmed the presence of pathologic acid exposure). Papers were sorted in duplicate. Relevant data was extracted from papers meeting inclusion criteria, including histologic abnormalities and the location of the biopsy. Sensitivities and specificities were calculated from raw data and pooled using RevMan 5.4 software, using asymptomatic patients with no significant esophageal acid exposure and/or patients with functional heartburn (i.e., symptoms but no elevated acid exposure on ambulatory pH testing) as controls. Results The search yielded 2871 studies after the removal of duplicates, of which 158 were eligible for full text review. In total, 12 papers met our stringent inclusion criteria and contained raw data that allowed for sensitivity calculations. Histological abnormalities that were commonly reported included gross morphological scores, papillary elongation, basal cell hyperplasia and dilated intraepithelial spaces. Biopsies were taken at <3cm in 5 studies, ≥3cm in 5 studies, and at multiple sites in 2 studies, and all were reviewed by a blinded pathologist. When assessing for the presence of any abnormality in the histological analysis, biopsies taken at <3cm had a pooled sensitivity of 0.70 (95% CI 0.64 – 0.75) and specificity of 0.72 (95% CI 0.63 – 0.77). Biopsies taken at ≥3cm revealed a pooled sensitivity of 0.39 (95% CI 0.32 – 0.47) and specificity of 0.63 (95% CI 0.51 – 0.74). Conclusions Esophageal mucosal biopsies have poor sensitivity and specificity at diagnosing non-erosive gastroesophageal reflux disease. Biopsies taken below 3cm appear to have a higher sensitivity and specificity than those taken more proximally. Funding Agencies None

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.028
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0200.032
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.048
GPT teacher head0.326
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

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