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Record W1969658697 · doi:10.1097/jpn.0b013e31825277e9

The 5-Minute Apgar Score

2012· article· en· W1969658697 on OpenAlexaff
Ann Gibbons Phalen, Sharon Kirkby, Kevin Dysart

Bibliographic record

VenueThe Journal of Perinatal & Neonatal Nursing · 2012
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsMerck Canada Inc. (Canada)
Fundersnot available
KeywordsApgar scoreMedicineBirth weightGestational ageLow birth weightPediatricsObstetricsExact testPregnancyInternal medicine

Abstract

fetched live from OpenAlex

The Apgar score is a standardized tool for evaluating newborns in the delivery room. Despite its long history and widespread use, debate remains over its reliability of predicting neonatal outcomes, especially in extremely low-birth-weight premature infants. The aim of the study was to examine the relationship between the 5-minute Apgar score of extremely low-birth-weight infants, as it relates to survival and morbidities associated with prematurity and length of hospital stay. A retrospective query of the Alere neonatal database from 2001 to 2011 examined all infants less than 32 weeks' gestation and less than 1000-g birth weight. The 5-minute Apgar score was divided into 2 groups, score of 4 or greater or less than 4. The study compared results of the 5-minute Apgar score and associated morbidities in surviving infants. Statistical analyses included chi-square, Fisher exact test, t test, and multivariate regression. The sample consisted of 3898 infants with an 86.4% (n = 3366) survival rate. Controlling for gestational age and birth weight, surviving infants with a 5-minute Apgar score of less than 4 were more likely to demonstrate nonintact survival. Infants with a low 5-minute Apgar score have greater risk for mortality and morbidities associated with prematurity.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.982
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.050
GPT teacher head0.379
Teacher spread0.329 · 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 designOther design
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

Citations18
Published2012
Admission routes1
Has abstractyes

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