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Record W2764332447 · doi:10.1093/pch/20.5.e53b

57: Neonatal Morbidities in Small for Gestational Age Preterm Neonates: Is it Really Double Trouble?

2015· article· en· W2764332447 on OpenAlexaboutno aff
Siladitya Bhattacharya, Bryan S. Richardson, O da Silva

Bibliographic record

VenuePaediatrics & Child Health · 2015
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGestational agePediatricsSmall for gestational ageBirth weightNeonatal intensive care unitPopulationNeonatologyRetinopathy of prematurityGestationLow birth weightNeonatal sepsisObstetricsSepsisPregnancyInternal medicine

Abstract

fetched live from OpenAlex

Small for gestational age premature (SGA) neonates are an important subset among the preterm population. SGA preterm infants may suffer from complications of both prematurity and intrauterine growth retardation. There is considerable controversy in the literature, with some studies reporting an increase in neonatal mortality and morbidity in SGA premature neonates; while other studies reporting no risk difference. The varying results could be due to use of different growth standards, or inclusion based on liberal birth weight criteria. Given the uncertainty we designed a study, in a well defined sample, with sex specific, valid, population based growth standards, in order to evaluate neonatal morbidities affecting SGA neonates born at less than 31 weeks of gestation. To compare the rate of neonatal morbidities in SGA and AGA neonates born at less than 31 weeks of gestation. This was a hospital based cohort study of infants admitted or transferred into the neonatal intensive care unit at a tertiary referral center in South western Ontario, Canada. All neonates less than 31 weeks of gestation, born between January 1, 2000 to Dec 31, 2012, and who survived till discharge, were identified retrospectively. The neonates were classified as AGA (10th to 90th percentile) or SGA (<10th percentile) as per their birth percentile based on Kramer et al. Infants with major congenital anomalies were excluded. Maternal and neonatal demographic data and data regarding neonatal morbidities such as RDS, BPD, Mechanical Ventilation, PDA, PDA treatment, NEC, IVH, PVL, Sepsis, ROP, treatment for ROP were extracted from the Neonatal Perinatal Database. A total of 923 neonates met the inclusion criteria of which 9.5% were SGA and 87.6% were AGA. As expected maternal PIH rate was higher in the SGA group (51.1%) compared to the AGA group (51.1% vs. 14.0%; P<0.001). A higher proportion of SGA babies were delivered via Cesarean section (89.8% vs. 60.2%; P<0.001). Neonatal morbidities like RDS, BPD, sepsis, NEC, Sepsis, ROP, IVH and PVL were found to be statistically no different in the two groups. Hemodynamically significant PDA was significantly lower in SGA infants (39.8% vs. 53,8%; P=0.01). The need for mechanical ventilation was also found to be lower in SGA infants (68.2% vs. 78.6%; P=0.03). Days on oxygen and number of days to full feed were comparable in the two groups. SGA preterm infants born at less than 31 weeks of gestation were found to have similar rates of neonatal morbidities such as RDS, BPD, NEC, ROP as their AGA peers. SGA infants had lower rates of mechanical ventilation and hemodynamically significant PDA.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.117
GPT teacher head0.386
Teacher spread0.269 · 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 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
Published2015
Admission routes1
Has abstractyes

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