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Record W2043299344 · doi:10.1097/mog.0b013e32832c1504

Evolving issues in the management of reflux disease?

2009· review· en· W2043299344 on OpenAlexaff
Yuhong Yuan, Richard H. Hunt

Bibliographic record

VenueCurrent Opinion in Gastroenterology · 2009
Typereview
Languageen
FieldMedicine
TopicGastroesophageal reflux and treatments
Canadian institutionsMcMaster University Medical Centre
Fundersnot available
KeywordsGERDHeartburnMedicineDiseaseRefluxIntensive care medicineNerdEsophagitisReflux esophagitisGastroenterologyQuality of life (healthcare)Internal medicineClinical trialRefractory (planetary science)Proton-pump inhibitor

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Gastroesophageal reflux disease (GERD) is a common chronic disorder often successfully treated, although there are several evolving issues in management. We reviewed the issues related to unmet needs over the past 12 months. RECENT FINDINGS: A substantial number of patients fail to respond adequately to once or even twice daily proton pump inhibitor (PPI). There is no standard definition of PPI failure in GERD; a universally accepted definition for treatment success is also not available. Differentiation between erosive esophagitis and nonerosive reflux disease can be made but requires endoscopy; but studies still confuse functional heartburn and nonerosive reflux disease, which impacts management. Acid reflux plays an important role in GERD pathogenesis and the precise role of acid requires more studies of differences between erosive esophagitis and nonerosive reflux disease symptom generation and the implication of nocturnal acidification. Several possible mechanisms may explain GERD refractory to PPIs. SUMMARY: Management of PPI nonresponders remains a challenge. Objective and precise evaluation of symptoms and treatment response requires study in high-quality trials. New therapeutic approaches are under investigation to answer unmet needs and improve erosive esophagitis healing rates and symptom control.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.861
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
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 head0.091
GPT teacher head0.431
Teacher spread0.341 · 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.

Study designOther design
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

Citations25
Published2009
Admission routes1
Has abstractyes

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