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The Neurologic and Adaptive Capacity Score Is Not a Reliable Method of Newborn Evaluation

2001· article· en· W2122114189 on OpenAlexaff
Stephen H. Halpern, Judith Littleford, Nicole J. Brockhurst, Paul J. Youngs, Nariman Malik, Holly C. Owen

Bibliographic record

VenueAnesthesiology · 2001
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science CentreMount Sinai Hospital
Fundersnot available
KeywordsIntraclass correlationMedicineReliability (semiconductor)Confidence intervalTest (biology)Physical therapyPsychometricsInternal medicineClinical psychology

Abstract

fetched live from OpenAlex

BACKGROUND: The Neurologic and Adaptive Capacity Score (NACS) is a multi-item scale that was published in 1982 to measure the effects of intrapartum drugs on the neonate. Although this scoring system has been widely used in obstetric anesthesia research, studies confirming its reliability have not been published. The purpose of this study was to assess the reliability of the NACS. METHODS: Two teams of observers were trained to perform the NACS on healthy, term neonates born in the vertex presentation. Two examinations were performed on each neonate within the first 2.5 h of life. Simultaneous (or "split-half") reliability was assessed using the alpha coefficient. Test-retest reliability was assessed using the intraclass correlation coefficient. The test was considered to be reliable if a was greater than 0.7 and the intraclass correlation coefficient was greater than 0.6. RESULTS: Two hundred babies were studied. The a was 0.47 and the intraclass correlation coefficient was 0.38 (95% confidence interval, 0.24-0.52). CONCLUSIONS: The NACS had poor reliability both on simultaneous testing and in the test-retest situation when used to evaluate term, healthy neonates. The authors suggest that other measures need to be developed to evaluate the effect of intrapartum drug administration in the neonate. Health measurement scales should undergo rigorous assessment for reliability and validity before they are used in clinical practice or for research purposes.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.248

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.072
GPT teacher head0.308
Teacher spread0.237 · 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

Citations45
Published2001
Admission routes1
Has abstractyes

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