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Record W2155392873 · doi:10.1177/088307380001501002

Prediction of Outcome at School Age in Neonatal Intensive Care Unit Graduates Using Neonatal Neurologic Tools

2000· review· en· W2155392873 on OpenAlexafffund
Annette Majnemer, Bernard Rosenblatt

Bibliographic record

VenueJournal of Child Neurology · 2000
Typereview
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsMcGill UniversityMontreal Children's Hospital
FundersHealth Canada
KeywordsNeonatal intensive care unitMedicineOutcome (game theory)PediatricsIntensive care medicine

Abstract

fetched live from OpenAlex

Prediction of outcome for neonatal intensive care unit graduates is clinically useful to counsel families effectively and target those who may benefit from early interventions. Evoked potentials have proven prognostic value of neurologic outcomes in early childhood; however, their long-term predictive validity remains to be determined. The objective of this prospective study was to determine the long-term predictive value of three neonatal neurologic assessments: brainstem auditory evoked potentials, somatosensory evoked potentials, and the Einstein Neonatal Neurobehavioral Assessment Scale. Seventy-eight high-risk newborns and 28 healthy controls were recruited and were assessed in the newborn period using these tests. At 8 to 9 years of age, 42 subjects and 13 controls were re-evaluated for developmental progress using a range of psychologic, sensorimotor, and neurologic measures. Findings indicated that the somatosensory evoked potential was most accurate at predicting outcome at school age, with high specificity (83-100%) across all domains tested and good sensitivity (80-100%) for intellectual performance and sensorimotor abilities. The brainstem auditory evoked potential was limited by false-negatives, whereas the neonatal neurobehavioral assessment yielded many false-positives. This study provides new evidence that associations between neonatal somatosensory evoked potentials and developmental sequelae continue to be significant at school age.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.904
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
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 head0.099
GPT teacher head0.331
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.

Study designOther design
Domainnot available
GenreReview

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

Citations29
Published2000
Admission routes2
Has abstractyes

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