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A Strategy to Enhance Confidence in Respiratory Chemoreflex Characterization by Modified Rebreathing

2022· article· en· W4225303707 on OpenAlexafffund
Nasimi A. Guluzade, Randi R. Keltz, Joshua D. Huggard, Daniel A. Keir

Bibliographic record

VenueThe FASEB Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsToronto General HospitalLawson Health Research InstituteWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordspCO2AnesthesiaRespirationMedicineVentilation (architecture)Respiratory systemCardiologyInternal medicineNuclear medicineAnatomyPhysics

Abstract

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Modelling breath‐by‐breath ventilation (V̇ E ) in response to carbon dioxide rebreathing in hyperoxic and hypoxic conditions (modified rebreathing) is used to characterize the central and peripheral respiratory chemoreflexes in humans. However, breath‐to‐breath variability produces uncertainty in the estimation of model parameters. We explored whether signal‐averaging of repeated rebreathing trials would improve chemoreflex sensitivity parameter estimation and confidence. Seven healthy males (age: 27±5 years) performed 6 repetitions of modified rebreathing tests in isoxic‐hypoxic (end‐tidal PO 2 (P ET O 2 )=50 mmHg) and ‐hyperoxic conditions (P ET O 2 =150 mmHg) over the course of 4 days. End‐tidal PCO 2 (P ET CO 2 ), P ET O 2 and V̇ E were measured breath‐by‐breath by dual gas analyser and pneumotach. The slope of the V̇ E vs P ET CO 2 relationship above the P ET CO 2 threshold in the hyperoxic test gave the central chemoreflex sensitivity (L∙min ‐1 ∙mmHg ‐1 ) and the difference in hypoxic versus hyperoxic test slopes provided peripheral chemoreflex sensitivity. Chemoreflex slopes modelled from a single trial versus ensemble‐average of 6 trials were compared by paired t‐test and effect size (Cohen’s d). Breath‐by‐breath data from the 6 trials were aligned to the same starting P ET CO 2 , linearly interpolated to 0.1 mmHg of P ET CO 2 , ensemble‐averaged, and averaged into 0.2 mmHg bins. Central chemoreflex sensitivity did not differ (p=0.94) between single (4.10±2.98 L∙min ‐1 ∙mmHg ‐1 , 95%CI: 3.82–4.39) versus ensemble‐averaged data (4.13±2.14 L∙min ‐1 ∙mmHg ‐1 , 95%CI: 3.99–4.27) but the 95%CI was reduced (p=0.031) by 0.29 L∙min ‐1 ∙mmHg ‐1 (effect size=1.5) with the ensemble‐averaged approach. Similarly, peripheral chemoreflex sensitivity did not differ (p=0.83) between single (1.69±1.14 L∙min ‐1 ∙mmHg ‐1 , 95%CI: 1.54–1.84) versus ensemble‐averaged data (1.58±1.32 L∙min ‐1 ∙mmHg ‐1 , 95%CI: 1.5 –1.66); 95%CI of the ensemble‐averaged data was 0.15 L∙min ‐1 ∙mmHg ‐1 lower than a single trial but this was not different (p=0.38; effect size=0.5). Signal averaging of multiple modified rebreathing trials reduces the confidence interval of respiratory chemoreflex sensitivity. This strategy could enhance the ability to detect differences in respiratory chemoreflex control in comparative or interventional studies where modified rebreathing is used.

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)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
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 head0.026
GPT teacher head0.301
Teacher spread0.275 · 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 designBench or experimental
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".

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Citations2
Published2022
Admission routes2
Has abstractyes

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