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Record W7135071474 · doi:10.4187/respcare.20233940854

New Nasal Interface to Improve Breath Detection From Pulsed Oxygen Sources: Healthy Participant Study

2023· article· en· W7135071474 on OpenAlexaff
Cole Christianson, Efrem Violato, Mozhgan Sabz, Hossein Rouhani, Thomas Waring, Cliff Reeves, Andrew R. Martin

Bibliographic record

VenueRespiratory Care · 2023
Typearticle
Languageen
FieldMedicine
TopicAirway Management and Intubation Techniques
Canadian institutionsNorthern Alberta Institute of TechnologyUniversity of Alberta
Fundersnot available
KeywordsNasal cannulaSpirometerOxygenNoseVolunteerPulse (music)CannulaPulse oximetryOxygen deliverySIGNAL (programming language)

Abstract

fetched live from OpenAlex

Background: Pulsed oxygen sources rely on pressure triggering to detect inhalation: during inhalation, room air entrainment creates a small drop in pressure monitored through the cannula tubing, referred to herein as the signal pressure. When the signal pressure exceeds the triggering threshold of a pulsed-flow oxygen device, a pulse of oxygen is released. Patients may struggle to trigger oxygen delivery during sleep, oral breathing, or other circumstances characterized by low nasal inhalation flows. To address this issue, a new nasal interface that can provide higher and more consistent signal pressures is being developed. Methods: Eight volunteers ranging from 22-47 years old participated in the study. Each volunteer was asked to breathe at different flows through their nose while connected to an oxygen tank with a Philips SimplyGo Mini POC, an OxyGo Next POC via standard nasal cannula, or the new nasal interface. A Precision Medical Easy Pulse 5+6 oxygen conserving device was used with the tank. To monitor flows, a respiratory belt (Respiration Sensor, TTLP2HRVSYS, Bio-medical Instruments, MI) was strapped around each participant’s chest. The respiratory belt was calibrated using spirometer data (MicroLoop Spirometer, #ML3535-S, Micro Medical, ME). Tests were repeated while participants breathed through their mouths. Video recordings with a close-up view of the oxygen sources were used to detect pulse triggering. Each participant breath was retroactively matched with a pulse/no pulse response, and the number of pulses was divided by the number of breaths to calculate triggering success rates. A two-tailed t-test (P <.05) was conducted with triggering success rate as the dependent variable and cannula type as the independent variable. Ethics approval was granted by the NAIT Research Ethics Board. Results: Pooled across all study conditions, triggering success rates were significantly higher (P = .03) when using the new nasal interface (78.9%) compared to the standard nasal cannula (65.2%). When using a standard nasal cannula during oral breathing, mean triggering success rates were below 40% for all oxygen sources. Using the new nasal interface approximately doubled oral breathing triggering success rates. Conclusions: Reliable breath detection is an issue when using pulsed-flow oxygen sources, especially during oral breathing. Significantly improved breath detection was observed when healthy participants used the new nasal interface versus a standard nasal cannula.Figure 1: Average triggering success rates (%) when using a Standard Cannula and the New Nasal Interface. Error bars represent standard deviations. Data is pooled across all breathing patterns and oxygen sources.Figure 2: Triggering Success Rates during Oral Breathing sorted based on Cannula Type and Oxygen Source. Error bars represent standard errors.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.766
Threshold uncertainty score0.629

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.051
GPT teacher head0.347
Teacher spread0.296 · 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 designOther design
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

Citations0
Published2023
Admission routes1
Has abstractyes

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