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Record W1971767574 · doi:10.1164/ajrccm.162.6.9912053

Noninvasive Assessment of Inspiratory Muscle Function during Exercise

2000· article· en· W1971767574 on OpenAlexaff
Maurice Hayot, Michèle Ramonatxo, Stéfan Matecki, J. Milic‐Emili, Christian Préfaut

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2000
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineCOPDCardiologyIsometric exerciseInternal medicinePhysical therapy

Abstract

fetched live from OpenAlex

The use of esophageal and gastric balloons limits measurement of the tension-time index of inspiratory muscles (TTI) during exercise. The aim of this study was to assess whether a noninvasive tension-time index, TT(0.1), given by P(0.1)/PI(max) x TI/Ttot (where P(0.1) is mouth occlusion pressure, PI(max) is maximal inspiratory pressure, and TI/Ttot is duty cycle) could reliably assess TTI during exercise. In seven healthy young men and nine patients with COPD we measured TT(0.1) and TTI (i.e., Pes/Pes(max) x TI/Ttot where Pes is mean esophageal pressure and Pes(max) is maximal static Pes) at rest and during an incremental exercise test. A significant linear correlation (p < 0.02) was found between TT(0.1) and TTI in all normal subjects and patients with COPD. An equation for estimating TTI from TT(0.1) was established for each group. In the normal subjects there was good agreement between estimated and observed data. In five additional normal males studied prospectively, the agreement was also satisfactory and reproducible. In the COPD patients the agreement was poor. In conclusion, in young healthy subjects the changes in TT(0.1) during exercise reflect the changes in TTI, allowing satisfactory estimation of TTI from noninvasive measurements of TT(0.1).

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)0.000
metaresearch head score (Gemma)0.002
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0010.000

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 head0.016
GPT teacher head0.327
Teacher spread0.311 · 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

Citations35
Published2000
Admission routes1
Has abstractyes

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