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Respiratory oscillometry in infants: methodological aspects

2024· article· en· W4404090867 on OpenAlexaboutno aff
Zoltán Hantos, Jeffrey Bjerregaard, Christina Tiller, Laura Amos, Gergely Makan, Robert I. Tepper

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicHuman Health and Disease
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceMedicineIntensive care medicine

Abstract

fetched live from OpenAlex

Background: Oscillometry in infant lung function is of emerging potential but is challenged by special conditions (sleep, position, nasal breathing and high mechanical impedance) not encountered in older age groups. Aims: To investigate the effects of face mask positioning and head support on respiratory impedance (Zrs) in infants. Methods: Sedated infants (n=21) who were born preterm (25-37 wk gestational age) were evaluated longitudinally as outpatients at corrected-ages of 5-6 (visit 1; V1) and 12 months (V2). A device in development (N-100; Thorasys Inc., Montreal, CA) was employed to measure Zrs in the 7-41-Hz range. The head/mask support was accomplished with 1 hand (1H) or 2 hands (2H); >3 regular segments of 7 s were collected in each condition. The Zrs spectra were processed to correct (corr) for the face mask shunt. Mean resistance (R), compliance (C), and resonance frequency (fres) were estimated via model fitting. Results: Uncorrected Zrs failed to exhibit fres in 12 (V1) and 1 (V2) subjects and resulted in unexpectedly low C values. V1 and V2 results reflected growth (Table 1). There was no significant difference in any measure with 1H and 2H support (signed rank test). erj;64/suppl_68/PA1462/TB1 T1 TB1 V1 V1corr V2 V2corr R (cmH2O.s/L) 31.9 [27.2;36.3] 33.4 [28.9;39.2]* 25.7 [19.8;29.8]# † 23.2 [19.7;27.5]* †† C (mL/cmH2O) 1.08 [0.86;1.32] 1.56 [1.13;1.90]** 1.62 [1.23;2.10]# † 1.89 [1.56;2.84]** † fres (Hz) 53.1 [39.3;61.0] 17.6 [16.1;23.6]* 28.6 [23.1;37.8]# 16.4 [13.4;18.0]** † Table 1. Median [25%;75%] values of Zrs measures. p corr vs uncorr: <0.05*, <0.001**; V2 vs V1: <0.05†, <0.001†† Conclusion: Correction for the face mask shunt impedance provided more realistic Zrs spectra and derived measures, especially at high Zrs values.

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)0.018
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.018
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.195
GPT teacher head0.461
Teacher spread0.266 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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
Published2024
Admission routes1
Has abstractyes

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