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Record W4410603300 · doi:10.1089/respcare.12514

Evaluation of the Accuracy of a Mechanical Insufflation-Exsufflation Device’s Cough Peak Flow Measurement

2025· article· en· W4410603300 on OpenAlexaff
Neeraj Shah, Sophie Madden-Scott, Chloe Apps, Ema Swingwood, Harriet Shannon, Eui‐Sik Suh, Nicholas Hart, Georgios Kaltsakas, Leyla Osman, Patrick B. Murphy

Bibliographic record

VenueRespiratory Care · 2025
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsExsufflationMedicineInsufflationAnesthesia

Abstract

fetched live from OpenAlex

Background: Mechanical insufflation-exsufflation (MI-E) is used to augment secretion clearance in neuromuscular patients with weakened cough strength. Cough peak flow (CPF) is a measure of cough function that is used to assess a patient’s ability to clear secretions, with thresholds set that categorize cough as effective, ineffective or severely ineffective. MI-E is prescribed according to these thresholds, and CPF is used to assess titration of MI-E settings. The Clearway2 (Breas Medical, Stratford-upon-Avon, United Kingdom) displays a real-time CPF, measured by an internal pneumotachograph. This study sought to assess the agreement and repeatability of this displayed CPF, against the reference CPF measurement by a calibrated pneumotachograph. Methods: This study consisted of two phases (1) lung model (Group A) and (2) acutely unwell individuals with neuromuscular conditions (Group B) and clinically stable individuals with neuromuscular conditions (Group C). Simultaneous CPF measurements were recorded from the MI-E device (CPF MI-E ) and a calibrated pneumotachograph (CPF), which was inserted into the MI-E circuit. Bland-Altman analysis was used to assess agreement between methods of measurement, and repeatability was assessed using a repeated measures analysis of variance. Results: During phase 1, 805 simulated coughs were evaluated with the Clearway2. The mean bias toward CPF MI-E was 33 L/min (95% limits of agreement 6–60 L/min). During phase 2, the mean bias increased to 66 L/min (95% limits of agreement 13–119 L/min). CPF MI-E and CPF both had good repeatability in all groups. Conclusions: The Clearway2 MI-E device provided a real-time CPF measurement that was repeatable and systematically higher than CPF. It may therefore be a useful tool to measure change longitudinally, or in response to changes in MI-E settings, in an individual patient. Caution is advised if using the CPF MI-E to assess cough efficacy against clinical thresholds.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.085
GPT teacher head0.349
Teacher spread0.264 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations3
Published2025
Admission routes1
Has abstractyes

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