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The practical management of patients with gastroesophageal reflux: an Italian survey

2023· article· en· W4377030350 on OpenAlexaff
Andrea Anderloni, Edoardo Savarino, Rocco Maurizio Zagari, S E Aragona, Giorgio Ciprandi

Bibliographic record

VenueGazzetta Medica Italiana Archivio per le Scienze Mediche · 2023
Typearticle
Languageen
FieldMedicine
TopicGastroesophageal reflux and treatments
Canadian institutionsUniversity Hospital Foundation
Fundersnot available
KeywordsGERDMedicineRefluxDiseaseInternal medicineClinical PracticeGastroenterologyMedical historyClinical trialFamily medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Gastroesophageal reflux disease (GERD) is a prevalent medical condition in clinical practice. However, its management is still controversial and debated. An Italian survey involved a group of gastroenterologists in describing their clinical approach.METHODS: A panel of Italian gastroenterologists participated in the survey. The survey included questions concerning professional characteristics and patient management in clinical practice.RESULTS: Sixty-five gastroenterologists completed the questionnaire. GERD diagnosis is usually established by history and PPI Test (commonly for 4 or 8 weeks with a single dose). After reassessment, PPI is usually associated with mucosal protectors, alginates, and antacids. Gastroenterologists were particularly satisfied (88.4%) with the combination of PPI (single dose) plus mucosal protectors, while 43.5 preferred the single PPI approach.CONCLUSIONS: The present Italian survey showed that the work-up in GERD patients is essentially based on history and PPI Trial. After reassessment, PPIs are commonly prescribed, but they are frequently associated with mucosal protectors, alginates, and antacids, preferring the former.

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)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
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 head0.031
GPT teacher head0.319
Teacher spread0.288 · 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
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

Citations0
Published2023
Admission routes1
Has abstractyes

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