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Evaluation of SnIII parameters as outcome measures of multiple breath washout (MBW) in preschool children with cystic fibrosis

2021· article· en· W3216320226 on OpenAlexaff
Marie‐Pier Dumas, Nicholas Karsli, Renée Jensen, Félix Ratjen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineCystic fibrosisVentilation (architecture)CardiologyWashoutInternal medicineNuclear medicine

Abstract

fetched live from OpenAlex

Scond and Sacin are alternative MBW indices that reflect regional variations in ventilation homogeneity. Verger et al (2020) suggest the use of Scond* and Sacin*, measured from the second breath to 3-TO, in subjects with LCI ≥9 to account for the plateau effect in normalized phase III slopes (SnIII) associated with high ventilation inhomogeneity. Further validation in preschool children with cystic fibrosis (CF) is required. We retrospectively analyzed data collected as part of a longitudinal observational study in preschool age children, where MBW (Exhalyzer® D, EcoMedics AG) was performed at all study visits, to assess SnIII parameters (Scond, Sacin, Scond* and Sacin*). To date, 38 (19 HC; 19 CF) participants have been analyzed (mean age 5 years, SD 0.8). Breath-by-breath quality control was performed per the ERS/ATS consensus statements for inert gas washout (Robinson et al 2013, 2018). Scond and Sacin were acceptable in 79% (30/38) of preschool children, similar to previously reported feasibility. Our results suggest that Scond, Scond*, Sacin and Sacin* differentiate health and disease (p<0.05, paired t test) in early CF disease. Further analysis of this large, longitudinal dataset to determine how these parameters track over time is ongoing. Funded by NHLBI.

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)0.002
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 score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.055
GPT teacher head0.347
Teacher spread0.292 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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