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The effect of a PEEP valve on a Laerdal neonatal self‐inflating resuscitation bag

2009· article· en· W1974179540 on OpenAlexaff
Colin J. Morley, Jennifer A. Dawson, Michael J. Stewart, Farhat Naz Hussain, Peter G. Davis

Bibliographic record

VenueJournal of Paediatrics and Child Health · 2009
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsRoyal Ottawa Mental Health Centre
Fundersnot available
KeywordsMedicinePositive end-expiratory pressureResuscitationAnesthesiaVentilation (architecture)Neonatal resuscitationMechanical ventilation

Abstract

fetched live from OpenAlex

BACKGROUND: Self-inflating bags are used to provide ventilation during neonatal resuscitation. However, they cannot provide positive end expiratory pressure (PEEP) unless a PEEP valve is attached. The ability of Laerdal neonatal self-inflating bags fitted with PEEP valves to reliably deliver PEEP is unclear. The aim of this study was to measure the delivered PEEP at different set PEEP levels and inflation rates. METHODS: We connected disposable and non-disposable 240 mL Laerdal self-inflating resuscitation bags fitted with PEEP valves to a leak-free test lung. We measured PEEP delivered with the valve set at 5, 7 and 10 cm H(2)O whilst inflating the test lung at rates of 20, 40 and 60 min. Studies were done with 8 L/min of gas flow and with no gas flow. RESULTS: The PEEP delivered was close to the set level immediately after inflation but declined rapidly between inflations. The mean PEEP was higher with faster ventilation rates. When PEEP was set at 7 cm H(2)O, using a non-disposable bag, and an inflation rate of 60/min the mean (SD) PEEP was 5.4 (0.19) cm H(2)O. The PEEP delivered was unrelated to the gas flow into the device. CONCLUSION: The 240 mL Laerdal self-inflating bag with a PEEP valve delivers PEEP that loses pressure quickly. The level of PEEP delivered is less than that set, particularly at rates below 40/min.

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)0.004
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.967
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
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 integrity0.0000.001
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 head0.012
GPT teacher head0.345
Teacher spread0.333 · 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

Citations59
Published2009
Admission routes1
Has abstractyes

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