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Record W3171967615 · doi:10.1007/s12325-021-01790-y

Disease Behaviour During the Peri-Diagnostic Period in Patients with Suspected Interstitial Lung Disease: The STARLINER Study

2021· article· en· W3171967615 on OpenAlexaff
Marlies Wijsenbeek, Elisabeth Bendstrup, Claudia Valenzuela, Michael T. Henry, Catharina C. Moor, S. Jouneau, Alessandro Giuseppe Fois, Onofre Moran‐Mendoza, Syed Anees, Mirela Mirt, Monica Bengus, Frank Gilberg, Klaus-Uwe Kirchgaessler, Carlo Vancheri

Bibliographic record

VenueAdvances in Therapy · 2021
Typearticle
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsUniversity of WindsorQueen's University
FundersF. Hoffmann-La Roche
KeywordsMedicineSpirometryInterstitial lung diseaseIdiopathic pulmonary fibrosisVital capacityQuartileInternal medicinePhysical therapyLungDiffusing capacityAsthmaLung functionConfidence interval

Abstract

fetched live from OpenAlex

INTRODUCTION: Disease behaviour may guide diagnosis and treatment decisions in patients with interstitial lung disease (ILD). STARLINER aimed to characterise disease behaviour in patients with suspected ILD during the peri-diagnostic period using real-time home-based assessments. METHODS: STARLINER (NCT03261037) was an international, multicentre study. Patients ≥ 50 years old with suspected ILD were followed throughout the peri-diagnostic period, consisting of a pre-diagnostic period (from enrolment to diagnosis) and a post-diagnostic period (from diagnosis to treatment initiation). Study length was variable (≤ 18 months). The primary endpoint was time-adjusted semi-annual forced vital capacity (FVC) change measured during the peri-diagnostic period using daily home spirometry in patients with idiopathic pulmonary fibrosis (IPF). Secondary outcomes included changes in FVC (home spirometry) in patients with non-IPF ILD, changes in FVC (site spirometry), changes in physical functional capacity measured by daily home accelerometry and site 6-min walk distance (6MWD), and changes in patient-reported outcomes (PROs) in IPF or non-IPF ILD. RESULTS: Of the 178 patients enrolled in the study, 68 patients were diagnosed with IPF, 62 patients were diagnosed with non-IPF ILD, 9 patients received a non-ILD diagnosis and 39 patients did not receive a diagnosis. Technical and analytical issues led to problems in applying the prespecified linear regression model to analyse the home FVC data. Time-adjusted median (quartile [Q]1, Q3) semi-annual FVC change during the peri-diagnostic period measured using home and site spirometry, respectively, was - 147.7 (- 723.8, 376.2) ml and - 149.0 (- 314.6, 163.9) ml for IPF and 19.1 (- 194.9, 519.0) ml and - 23.4 (- 117.9, 133.5) ml in non-IPF ILD. A greater decline in steps per day was observed for IPF versus non-IPF ILD, whereas an increase in 6MWD was observed for patients with IPF versus a decline in 6MWD for patients with non-IPF ILD. No clear patterns of disease behaviour were observed for IPF versus non-IPF ILD for PROs. CONCLUSIONS: Despite home spirometry being feasible for most patients and centres, technical and analytical challenges in the home-based assessments prevented firm conclusions regarding disease behaviour. This highlights that further optimisation of the technology and analysis methods is required before widespread implementation. TRIAL REGISTRATION: NCT03261037.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.251
Teacher spread0.247 · 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".

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Citations17
Published2021
Admission routes1
Has abstractyes

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