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Record W4393115134 · doi:10.1016/j.semperi.2024.151890

Weaning from mechanical ventilation and assessment of extubation readiness

2024· article· en· W4393115134 on OpenAlexaff
Guilherme SantʼAnna, Wissam Shalish

Bibliographic record

VenueSeminars in Perinatology · 2024
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsMcGill UniversityMontreal Children's Hospital
Fundersnot available
KeywordsMedicineMechanical ventilationWeaningNeonatologyGestational ageVentilation (architecture)PopulationIntensive care medicineGestationPediatricsAnesthesiaPregnancyInternal medicine

Abstract

fetched live from OpenAlex

Tremendous advancements in neonatal respiratory care have contributed to the improved survival of extremely preterm infants (gestational age ≤ 28 weeks). While mechanical ventilation is often considered one of the most important breakthroughs in neonatology, it is also associated with numerous short and long-term complications. For those reasons, clinical research has focused on strategies to avoid or reduce exposure to mechanical ventilation. Nonetheless, in the extreme preterm population, 70-100% of infants born 22-28 weeks of gestation are exposed to mechanical ventilation, with nearly 50% being ventilated for ≥ 3 weeks. As contemporary practices have shifted towards selectively reserving mechanical ventilation for those patients, mechanical ventilation weaning and extubation remain a priority yet offer a heightened challenge for clinicians. In this review, we will summarize the evidence for different strategies to expedite weaning and assess extubation readiness in preterm infants, with a particular focus on extremely preterm infants.

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 score0.931
Threshold uncertainty score0.475

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 head0.039
GPT teacher head0.423
Teacher spread0.384 · 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

Citations7
Published2024
Admission routes1
Has abstractyes

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