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Record W1999072969 · doi:10.1055/s-2008-1078762

Triplet Infants with Birthweight ≤ 1250 Grams: How Well Do They Compare with Twin and Singleton Infants at 36 to 48 Months of Age?

2008· article· en· W1999072969 on OpenAlexaff
Wendy Yee, Matthew Hicks, Sophie Chen, Heather Christianson, Reg Sauvé

Bibliographic record

VenueAmerican Journal of Perinatology · 2008
Typearticle
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsHealth CanadaUniversity of Calgary
Fundersnot available
KeywordsSingletonMedicinePediatricsObstetricsPregnancy

Abstract

fetched live from OpenAlex

The purpose of this study was to determine if triplet infants with birthweight < or = 1250 g were at increased risk of long-term disability compared with similar birthweight and gestational age singletons and twins. This was a retrospective cohort study of < or = 1250-g infants admitted to a regional neonatal intensive care unit from 1986 to 2001 with follow-up to 36 to 48 months corrected gestational age. Outcomes studied were cognitive ability, cerebral palsy, and neurosensory impairment at 36 to 48 months. Enrollment was 1717 infants: 59 triplets, 402 twins, and 1256 singletons. Triplet infants differed from twin or singleton infants because they were more likely to have older, married mothers (relative risk [RR] 3.62, 95% CI 1.31, 5.94), be products of assisted reproductive technology pregnancies (RR 29.59, 95% CI 13.97, 62.68), be exposed to antenatal steroids (RR 1.55, 95% CI 1.38, 1.75), and were all delivered by cesarean section. Triplet infants had lower risk of having intraventricular hemorrhage (RR 0.19, 95% CI 0.05, 0.75). The risk of cerebral palsy, cognitive delay, total major disability, or chronic lung disease was similar in triplet and twin infants compared with singleton infants. The lower risk of having intraventricular hemorrhage in triplet infants may have been due to the use of antenatal corticosteroids and cesarean section delivery.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.732

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.011
GPT teacher head0.242
Teacher spread0.231 · 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 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

Citations9
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of PerinatologySame topicAssisted Reproductive Technology and Twin PregnancyFrench-language works237,207