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Record W2118543777 · doi:10.1136/ebn.6.2.41

High frequency oscillatory ventilation was not more effective than conventional ventilation in preterm infants

2003· letter· en· W2118543777 on OpenAlexaff
Carol Cheng, Prakesh S. Shah

Bibliographic record

VenueEvidence-Based Nursing · 2003
Typeletter
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsMedicineHigh-frequency ventilationWeb of sciencePediatricsVentilation (architecture)Gestational ageLung diseaseMechanical ventilationGynecologyAnesthesiaInternal medicinePregnancyLungMeta-analysis

Abstract

fetched live from OpenAlex

Johnson AH, Peacock JL, Greenough A, et al, for the United Kingdom Oscillation Study Group. High-frequency oscillatory ventilation for the prevention of chronic lung disease of prematurity. N Engl J Med2002 ; 347 : 633 –42 [OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] QUESTION: In preterm infants who are 23–28 weeks gestational age, does high frequency oscillatory ventilation (HFOV) reduce death and chronic lung disease when compared with conventional ventilation (CV)? Randomised (unclear allocation concealment), unblinded, controlled trial with 8–13 weeks of follow up for the primary outcome. 25 centres: 22 in the UK and 1 each in Australia, Ireland, and Singapore. 870 infants were randomised before or just after delivery. 804 surviving infants who required endotracheal intubation from birth and ongoing intensive care were included. Exclusion criteria were transfer to another hospital for intensive care shortly after birth or major congenital abnormality. 797 infants (92%) … [1]: {openurl}?query=rft.jtitle%253DNew%2BEngland%2BJournal%2Bof%2BMedicine%26rft.stitle%253DNEJM%26rft.aulast%253DJohnson%26rft.auinit1%253DA.%2BH.%26rft.volume%253D347%26rft.issue%253D9%26rft.spage%253D633%26rft.epage%253D642%26rft.atitle%253DHigh-Frequency%2BOscillatory%2BVentilation%2Bfor%2Bthe%2BPrevention%2Bof%2BChronic%2BLung%2BDisease%2Bof%2BPrematurity%26rft_id%253Dinfo%253Adoi%252F10.1056%252FNEJMoa020432%26rft_id%253Dinfo%253Apmid%252F12200550%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1056/NEJMoa020432&link_type=DOI [3]: /lookup/external-ref?access_num=12200550&link_type=MED&atom=%2Febnurs%2F6%2F2%2F41.atom [4]: /lookup/external-ref?access_num=000177675500002&link_type=ISI

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.003
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 head0.058
GPT teacher head0.377
Teacher spread0.318 · 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.

Study designObservational
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

Citations0
Published2003
Admission routes1
Has abstractyes

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