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Record W2802073505 · doi:10.1183/13993003.00376-2018

The effect of anti-acid therapy on survival in idiopathic pulmonary fibrosis: a methodological review of observational studies

2018· review· en· W2802073505 on OpenAlexaff
Tanja Tran, Samy Suissa

Bibliographic record

VenueEuropean Respiratory Journal · 2018
Typereview
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineObservational studyPulmonary fibrosisIdiopathic pulmonary fibrosisIntensive care medicineInternal medicineFibrosisLung

Abstract

fetched live from OpenAlex

International treatment guidelines for idiopathic pulmonary fibrosis (IPF) give a conditional recommendation for anti-acid therapy. As some observational studies reported discrepant findings on the effectiveness of anti-acid therapy on mortality in IPF, we reviewed all studies to evaluate whether immortal time bias explains these discrepancies.We searched the Embase and MEDLINE databases up to July 2017 for observational studies assessing the effectiveness of anti-acid therapy on mortality in IPF. Hazard ratios of mortality with anti-acid therapy were pooled across studies using random-effect models, stratified by the presence of immortal time bias.We identified 10 observational studies. Four of the five studies reporting beneficial effects of anti-acid therapy use on mortality were affected by immortal time bias (pooled hazard ratio 0.46; 95% CI 0.30-0.69), while it was unclear whether the fifth was affected. The five studies that avoided immortal time bias reported no effect of anti-acid therapy on mortality (pooled hazard ratio 0.99; 95% CI 0.81-1.22).The apparent beneficial effects of anti-acid therapy on mortality in patients with IPF result from observational studies affected by immortal time bias. Thus, the effectiveness of anti-acid therapy in IPF remains uncertain and needs to be reassessed with more accurate observational study methods and randomised trials.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptMeta-epidemiology (narrow)Meta-epidemiology (broad)Metaresearch
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.067
metaresearch head score (Gemma)0.197
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.933
Threshold uncertainty score0.353

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0670.197
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.013
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.289
GPT teacher head0.442
Teacher spread0.153 · 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

Labeled directly by 2 models reading the full record.

Meta-epidemiology (narrow)Meta-epidemiology (broad)Metaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designSystematic review
DomainMethods
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

Citations50
Published2018
Admission routes1
Has abstractyes

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