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Record W2891184698 · doi:10.1111/pan.13389

Artificial ventilation during transport: A randomized crossover study of manual resuscitators with comparison to mechanical ventilators in a simulation model

2018· article· en· W2891184698 on OpenAlexaff
Malcolm J. Lucy, Jonathan Gamble, Andrew Peeling, Jimmy T.H. Lam, Lloyd Balbuena

Bibliographic record

VenuePediatric Anesthesia · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineAnesthesiaMean airway pressurePeak inspiratory pressureVentilation (architecture)AirwayMechanical ventilatorMechanical ventilationCrossover studyResuscitationTidal volumeRespiratory systemInternal medicineMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Background Positive‐pressure ventilation in critically ill patients is commonly administered via a manual resuscitation device or a mechanical ventilator during transport. Our group previously compared delivered ventilation parameters between a self‐inflating resuscitator and a flow‐inflating resuscitator during simulated in‐hospital pediatric transport. However, unequal group access to inline pressure manometry may have biased our results. In this study, we examined the performance of the self‐inflating resuscitator and the flow‐inflating resuscitator, both equipped with inline manometry, and several mechanical ventilators to deliver prescribed ventilation parameters during simulated pediatric transport. Methods Thirty anesthesia providers were randomized to initial resuscitator device used to hand ventilate a test lung. The resuscitators studied were a Jackson‐Rees circuit (flow‐inflating resuscitator) or a Laerdal pediatric silicone resuscitator (self‐inflating resuscitator), both employing manometers. The scenario was repeated using several mechanical transport ventilators (Hamilton‐T1, LTV® 1000, and LTV® 1200). The primary outcome was the proportion of total breaths delivered within the predefined target PIP/PEEP range (30 ± 3, 10 ± 3 cm H2O). Results The Hamilton‐T1 outperformed the other ventilators for breaths in the recommended range (χ2 = 2284, df = 2, P < .001) and with no breaths in the unacceptable range (χ2 = 2333, df = 2, P < .001). Hamilton‐T1 also outperformed all human providers in proportion of delivered acceptable and unacceptable breaths (χ2 = 4540, df = 3, P < .001 and χ2 = 639, df = 3, P < .001, respectively). Compared with the flow‐inflating resuscitator, the self‐inflating resuscitator was associated with greater odds of breaths falling outside the recommended range (Odds ratio (95% CI): 1.81 (1.51‐2.17)) or unacceptable (Odds ratio (95% CI): 1.63 (1.48‐1.81)). Conclusion This study demonstrates that a majority of breaths delivered by manual resuscitation device fall outside of target range regardless of provider experience or device type. The mechanical ventilator (Hamilton‐T1) outperforms the other positive‐pressure ventilation methods with respect to delivery of important ventilation parameters. In contrast, 100% of breaths delivered by the LTV 1200 were deemed unacceptable.

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)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.017
GPT teacher head0.312
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations10
Published2018
Admission routes1
Has abstractyes

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