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Record W2748263090 · doi:10.1055/s-0037-1606351

Neurodevelopment and Growth of a Cohort of Very Low Birth Weight Preterm Infants Compared to Full-Term Infants in Brazil

2017· article· en· W2748263090 on OpenAlexaboutno aff
Rubia do Nascimento Fuentefria, Rita C. Silveira, Renato S. Procianoy

Bibliographic record

VenueAmerican Journal of Perinatology · 2017
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePediatricsCohortTerm (time)Birth weightCohort studyLow birth weightFull TermObstetricsPregnancyInternal medicine

Abstract

fetched live from OpenAlex

Objective The objective of this study was to investigate the neurodevelopment and growth of very low birth weight (BW) preterm infants, at 8 and 18 months corrected age (CA), compared with full term in Brazil. Methods Prospective cohort study including 83 preterm infants with BW ≤ 1,500 g and gestational age ≤ 32 weeks, and 52 full-term control infants. Preterm infants free from significant sensory and motor disability, and from congenital anomalies were included. Alberta infant motor scale (AIMS) and Brunet–Lèzini scale (BLS) were used to evaluate the neurodevelopment at 8 and 18 months. Anthropometric measurements were collected to evaluate the growth in both age groups. Results At 8 months CA, preterm infants scored significantly lower in total AIMS score (p = 0.001). At 18 months, they scored significantly lower on the stand subscale from AIMS (p = 0.040) and exhibited poor psychomotor development in the BLS (p = 0.006). The nutritional status showed significant differences between the groups, in both age groups (p < 0.001). There were positive correlations between nutritional status and AIMS (r = 0.420; p < 0.001) and BLS (r = 0.456; p < 0.001) at 8 months, and between head circumference and BLS (r = 0.235; p < 0.05) at 8 months and AIMS (r = 0.258; p < 0.05) at 18 months. Conclusion Very low BW preterm infants at 8 and 18 months CA showed significant differences in the neurodevelopment and growth pattern when compared with their full-term peers.

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 score0.013
Threshold uncertainty score0.698

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 studies0.0000.001
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 head0.008
GPT teacher head0.273
Teacher spread0.264 · 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

Citations15
Published2017
Admission routes1
Has abstractyes

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