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Inspiration plus: baseline characteristics of the canadian registry for IPF patients on pirfenidone

2016· article· en· W2555124420 on OpenAlexaffabout
Francois Sincholle, Martin Kolb, H. Manganas, Rabea El Keeb, Marc Newton, Neerav Monga

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsLakeridge HealthSouth Bruce Grey Health CentreUniversité de MontréalMcMaster University
Fundersnot available
KeywordsPirfenidoneMedicineIdiopathic pulmonary fibrosisQuality of life (healthcare)PopulationDiseaseClinical PracticeClinical trialIntensive care medicineInternal medicinePhysical therapyEnvironmental healthLung

Abstract

fetched live from OpenAlex

Background: Idiopathic pulmonary fibrosis (IPF) is a progressive, irreversible and fatal disease. The primary aim of this national multicenter non-interventional study known as the INSPIRATION PLUS registry, is to describe the real world effectiveness and safety of pirfenidone and the clinical management practices in Canada. Methods: The patients included had a confirmed diagnosis in accordance with the 2011 international guidelines. Data are collected approximately every 3 to 6 months for a minimum of 2 years. The primary objective is to describe and assess the disease course and outcomes in pirfenidone-treated IPF patients in routine clinical practice. The drug utilization patterns will also be described. A validity assessment of the ATAQ-IPF questionnaire will be done compared to three validated but non-specific to IPF Quality of life measures. Results: Conclusion: The characteristics of this IPF population at the initiation of pirfenidone indicate that pirfenidone is being used in a wide spectrum of IPF patients in Canada. Follow up data will be presented at a later time.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.270

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.235
Teacher spread0.223 · 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 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
Published2016
Admission routes2
Has abstractyes

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