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Neurodevelopmental outcomes of preterm infants after randomisation to initial resuscitation with lower (FiO<sub>2</sub> &lt;0.3) or higher (FiO<sub>2</sub> &gt;0.6) initial oxygen levels. An individual patient meta-analysis

2021· review· en· W3208010774 on OpenAlexaff
Ju Lee Oei, Vishal Kapadia, Yacov Rabi, Ola Didrik Saugstad, Denise Rook, M. Vermeulen, Nuria Boronat, Valerie Thamrin, William Tarnow‐Mordi, John Smyth, Ian Wright, Kei Lui, Johannes B. van Goudoever, Val Gebski, Máximo Vento

Bibliographic record

VenueArchives of Disease in Childhood Fetal & Neonatal · 2021
Typereview
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsUniversity of Calgary
FundersEuropean Regional Development FundInstituto de Salud Carlos IIINational Institutes of Health
KeywordsMedicineGestationPediatricsBayley Scales of Infant DevelopmentResuscitationIntensive careOdds ratioAnesthesiaInternal medicinePregnancyCognitionPsychomotor learningIntensive care medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: ) for resuscitation on death and/or neurodevelopmental impairment (NDI) in infants <32 weeks' gestation. DESIGN: Meta-analysis of individual patient data from three randomised controlled trials. SETTING: Neonatal intensive care units. PATIENTS: 543 children <32 weeks' gestation. INTERVENTION: . OUTCOME MEASURES: ) below or at/above 80%. RESULTS: ≥80% (odds (95% CI) 09.62, 0.98 to 0.96) and gestation (0.52, 0.41 to 0.65), relative to children without death or NDI. CONCLUSION: was not associated with difference in risk of disability/death at 2 years in infants <32 weeks' gestation but CIs were wide. Substantial benefit or harm cannot be excluded. Larger randomised studies accounting for patient differences, for example, gestation and gender are urgently needed.

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)0.011
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.017
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0140.040
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.069
GPT teacher head0.363
Teacher spread0.295 · 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 designMeta-analysis
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

Citations16
Published2021
Admission routes1
Has abstractyes

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