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Optimization of manual ventilation quality using respiratory function monitoring in neonates: A two-phase intervention trial

2024· article· en· W4401263090 on OpenAlexaff
Robyn Dvorsky, Katharina Bibl, Andrea Lietz, Moritz Haderer, Katrin Klebermaß-Schrehof, Tobias Werther, Georg M. Schmölzer, Angelika Berger, M. Wagner

Bibliographic record

VenueResuscitation · 2024
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsRoyal Alexandra HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicineVentilation (architecture)Intensive care medicineEmergency medicineRespiratory systemInternal medicine

Abstract

fetched live from OpenAlex

ObjectiveThe aim of this study is the evaluation of the impact of a respiratory function monitor (RFM, Neo100, Monivent AB, Gothenburg, Sweden) on the quality of ventilation in neonates.MethodsThis single-center two-phase intervention study was conducted at the Neonatal Intensive Care Unit and the delivery room of the Medical University of Vienna. Patients with clinical need for positive pressure ventilation were included in either of two consecutive study phases: (i) patients were ventilated with a hidden RFM (control) or (ii) visible RFM (intervention) during manual positive pressure ventilations. The duration of each phase was approximately six months. The primary outcome was the percentage of ventilations within a tidal volume range of 4–8 ml/kg (pVTe).ResultsA total of 90 patients (GA 22–66 weeks) were included. The primary outcome was significantly higher in the intervention group with a visible RFM (53.7%, SD 22.6) than in the control group without the monitor (37.3%, SD 20.5); (p < 0.001, mean difference [i.e., change in percentage points]: 16,95% CI: 7.4–35). In terms of secondary outcomes, excessive tidal volumes (>8ml/kg), previously associated with an increased risk of brain injury, could be significantly reduced when a RFM was visible during ventilation (10.9% [IQR 26.4] vs. 29.5% [IQR 38.1]; p = 0.004). Furthermore, mask leakage could be significantly decreased (37.3% [SD 22.7] vs. 52.7% [SD 23.0]; p = 0.002).ConclusionOur results suggest that the clinical application of a RFM for manual ventilation of preterm and term infants leads to a significant improvement in ventilation parameters.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.097
GPT teacher head0.435
Teacher spread0.337 · 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

Citations10
Published2024
Admission routes1
Has abstractyes

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