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Record W2943722528 · doi:10.1097/mog.0000000000000543

The potential role of potassium-competitive acid blockers in the treatment of gastroesophageal reflux disease

2019· review· en· W2943722528 on OpenAlexaff
Carmelo Scarpignato, Richard H. Hunt

Bibliographic record

VenueCurrent Opinion in Gastroenterology · 2019
Typereview
Languageen
FieldMedicine
TopicGastroesophageal reflux and treatments
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsGERDMedicineHeartburnGastric acidGastroenterologyRefluxInternal medicineDiseaseEsophagitisEsophagusPathogenesisSecretion

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Gastroesophageal reflux disease (GERD) is primarily a motor disorder, but its pathogenesis is multifactorial. Although gastric acid secretion is usually normal in GERD patients, treatment with proton pump inhibitors (PPIs) has become the standard of care, despite increasing awareness of their shortcomings. In this article, a new class of antisecretory drugs (namely potassium-competitive acid blockers, P-CABs), developed to overcome these limitations, is discussed. RECENT FINDINGS: P-CABs block the K exchange channel of the proton pump, resulting in rapid, competitive, reversible inhibition of acid secretion. These drugs offer a more rapid elevation of intragastric pH than PPIs, while maintaining similar antisecretory effect, the duration of which is dependent on half-life and can be prolonged with extended release formulations. Thus, P-CABs offer advances in the treatment of GERD including rapid heartburn relief, faster and more reliable healing of severe grades of erosive esophagitis, as a consequence of better control of nighttime acid secretion than PPIs. SUMMARY: P-CABs overcome many of the drawbacks of PPIs. The unique antisecretory effects of vonoprazan might be especially useful in the long-term treatment of patients with Barrett's esophagus.

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 score0.733
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.046
GPT teacher head0.367
Teacher spread0.321 · 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

Citations49
Published2019
Admission routes1
Has abstractyes

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