MétaCan
Menu
Back to cohort
Record W2118680314 · doi:10.1017/s0950268815001181

The diagnosis and treatment of<i>Helicobacter pylori</i>infection in Arctic regions with a high prevalence of infection: Expert Commentary

2015· review· en· W2118680314 on OpenAlexaff
Brian J. McMahon, Michael G. Bruce, Anders Koch, Karen J. Goodman, В. В. Цуканов, Gert Mulvad, Malene Landbo Børresen, Frank Sacco, David A. Barrett, Simon Westby, Alan J. Parkinson

Bibliographic record

VenueEpidemiology and Infection · 2015
Typereview
Languageen
FieldMedicine
TopicHelicobacter pylori-related gastroenterology studies
Canadian institutionsUniversity of Alberta
FundersAgency for Toxic Substances and Disease RegistryCenters for Disease Control and Prevention
KeywordsHelicobacter pyloriMedicineInternal medicineGastroenterologyMALT lymphomaDiseaseChronic gastritisLymphomaGastritisHelicobacter pylori infectionPeptic ulcerPepticImmunologyIntensive care medicine

Abstract

fetched live from OpenAlex

Helicobacter pylori infection is a major cause of peptic ulcer and is also associated with chronic gastritis, mucosa-associated lymphoid tissue (MALT) lymphoma, and adenocarcinoma of the stomach. Guidelines have been developed in the United States and Europe (areas with low prevalence) for the diagnosis and management of this infection, including the recommendation to 'test and treat' those with dyspepsia. A group of international experts performed a targeted literature review and formulated an expert opinion for evidenced-based benefits and harms for screening and treatment of H. pylori in high-prevalence countries. They concluded that in Arctic countries where H. pylori prevalence exceeds 60%, treatment of persons with H. pylori infection should be limited only to instances where there is strong evidence of direct benefit in reduction of morbidity and mortality, associated peptic ulcer disease and MALT lymphoma and that the test-and-treat strategy may not be beneficial for those with dyspepsia.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.433
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.090
GPT teacher head0.358
Teacher spread0.269 · 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 designObservational
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

Citations55
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueEpidemiology and InfectionSame topicHelicobacter pylori-related gastroenterology studiesFrench-language works237,207