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Record W2462000645 · doi:10.1007/s00408-016-9912-1

First Data on Efficacy and Safety of Nintedanib in Patients with Idiopathic Pulmonary Fibrosis and Forced Vital Capacity of ≤50 % of Predicted Value

2016· article· en· W2462000645 on OpenAlexaff
Wim Wuyts, Martin Kolb, Susanne Stowasser, Wibke Stansen, John T. Huggins, Ganesh Raghu

Bibliographic record

VenueLung · 2016
Typearticle
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsMcMaster University
FundersBoehringer Ingelheim
KeywordsNintedanibVital capacityIdiopathic pulmonary fibrosisMedicineInternal medicineValue (mathematics)Pulmonary fibrosisCardiologyFibrosisLungLung functionStatisticsMathematicsDiffusing capacity

Abstract

fetched live from OpenAlex

In the Phase III INPULSIS(®) trials, 52 weeks' treatment with nintedanib reduced decline in forced vital capacity (FVC) versus placebo in patients with idiopathic pulmonary fibrosis (IPF). Patients who completed the INPULSIS(®) trials could receive nintedanib in an open-label extension trial (INPULSIS(®)-ON). Patients with FVC <50 % predicted were excluded from INPULSIS(®), but could participate in INPULSIS(®)-ON. In patients with baseline FVC ≤50 % and >50 % predicted at the start of INPULSIS(®)-ON, the absolute mean change in FVC from baseline to week 48 of INPULSIS(®)-ON was -62.3 and -87.9 mL, respectively (n = 24 and n = 558, respectively). No new safety signals were identified in INPULSIS(®)-ON compared with INPULSIS(®). The decline in FVC in INPULSIS(®)-ON in both subgroups by baseline FVC % predicted was similar to that in INPULSIS(®), suggesting that nintedanib may have a similar effect on disease progression in patients with advanced disease as in less advanced disease.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.223
Teacher spread0.214 · 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 designNon-randomized trial
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

Citations120
Published2016
Admission routes1
Has abstractyes

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