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Record W2802819217 · doi:10.1055/s-0038-1637763

New Ventilator Strategies: High-Frequency Oscillatory Ventilation Combined with Volume Guarantee

2018· review· en· W2802819217 on OpenAlexaff
Noelia González‐Pacheco, Jaques Belik, Martín Santos, F.J. Tendillo, Manuel Sánchez Luna

Bibliographic record

VenueAmerican Journal of Perinatology · 2018
Typereview
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineTidal volumeHigh-frequency ventilationVentilation (architecture)WashoutPulmonary complianceCompliance (psychology)AnesthesiaVolume (thermodynamics)LungMechanical ventilationRespiratory systemInternal medicine

Abstract

fetched live from OpenAlex

Abstract High-frequency oscillatory ventilation (HFOV) has been proposed as an alternative method of invasive ventilation in immature infants to prevent ventilator lung injury. To better control the size of the high-frequency tidal volume and to prevent large tidal volumes, a new strategy of controlling the tidal volume during HFOV (VThf) has been developed, HFOV–volume guarantee (VG). Data from preclinical, neonatal animal studies in normal and surfactant-depleted lungs have demonstrated the feasibility of this technique to directly control the VThf in the normal compliance and low compliance situations. Different I:E ratios also can modify the effect of CO2 washout during HFOV combined with VG in a different way as without the VG modality. Finally, clinical use of this technique in newborn infants has demonstrated the possibility of using very high frequency combined with constant very low VThf to decrease the risk of lung trauma related to the ventilator.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.036
GPT teacher head0.380
Teacher spread0.344 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations28
Published2018
Admission routes1
Has abstractyes

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