The Neurologic and Adaptive Capacity Score Is Not a Reliable Method of Newborn Evaluation
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".