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Record W3048561837 · doi:10.1136/thoraxjnl-2020-214817

Paediatric reproducibility limits for the forced expiratory volume in 1 s

2020· article· en· W3048561837 on OpenAlexaff
Sanja Stanojevic, Nicole Filipow, Félix Ratjen

Bibliographic record

VenueThorax · 2020
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsSickKids FoundationUniversity of TorontoDalhousie University
FundersVertex Pharmaceuticals
KeywordsReproducibilitySpirometryMedicineConfidence intervalLung functionPulmonary function testingVital capacityLung volumesLimits of agreementPhysical therapyStatisticsLungInternal medicineNuclear medicineAsthmaMathematicsDiffusing capacity

Abstract

fetched live from OpenAlex

BACKGROUND: Current reproducibility standards for spirometry were derived using a small adult dataset and may not be optimal for interpretation of repeated measurements of lung function in children. OBJECTIVE: ) change that represent the normal within-subject between-visit variability in healthy children and evaluate these limits as a tool to monitor children with cystic fibrosis (CF). METHODS: measurements (3 months to 5 years apart) from healthy children from the Global Lung Function Initiative data repository were used to derive a conditional change score. Spirometry and clinical data from a CF clinical database was used to verify utility in clinical practice. RESULTS: measures from 7885 healthy children 6-18 years of age. The simple algorithm, which is conditional on the initial measurement, also accounts for age and time interval between measurements. The change score limits of reproducibility were much narrower than currently used cut-offs. Specifically, changes, considered as improvements using either a 12% or 10% relative change from baseline, are too wide for children. In CF, there was overall agreement between different approaches, with the distinct advantage that the change score was not biased by regression to the mean. CONCLUSIONS: Compared with current approaches to interpretation of repeated lung function measurements, the proposed change score was less biased and provides a simple alternative to reduce misinterpretation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.071
GPT teacher head0.350
Teacher spread0.279 · 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 teacher head, not a consensus.

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

Citations21
Published2020
Admission routes1
Has abstractyes

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