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Record W1907596508 · doi:10.1111/resp.12622

Under‐recognised co‐morbidities in idiopathic pulmonary fibrosis: A review

2015· review· en· W1907596508 on OpenAlexaff
Kaïssa de Boer, Joyce Lee

Bibliographic record

VenueRespirology · 2015
Typereview
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineIdiopathic pulmonary fibrosisPulmonary hypertensionPulmonary fibrosisDepression (economics)DiseaseIntensive care medicineInternal medicineQuality of life (healthcare)Lung

Abstract

fetched live from OpenAlex

Co-morbidities in idiopathic pulmonary fibrosis are common. These co-morbidities include obstructive sleep apnoea, gastro-oesophageal reflux disease, pulmonary hypertension and depression. The presence of co-morbidities among patients with idiopathic pulmonary fibrosis contributes to worse quality of life, morbidity and mortality. Despite the high prevalence of certain co-morbidities in idiopathic pulmonary fibrosis, the optimal screening and management of many of these conditions remains unclear. The impact of co-morbidities on this patient population is becoming more apparent. Their relevance will only increase as significant effort is being made to develop novel therapeutics that will alter the disease trajectory of patients with idiopathic pulmonary fibrosis. The purpose of this review is to focus on the epidemiology, pathophysiology, diagnosis and management of select co-morbidities, including obstructive sleep apnoea, gastro-oesophageal reflux disease, pulmonary hypertension and depression, in idiopathic pulmonary fibrosis.

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 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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.081
GPT teacher head0.395
Teacher spread0.314 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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

Citations12
Published2015
Admission routes1
Has abstractyes

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