The Importance of Monitoring Neurodevelopmental Outcomes for Preterm Infants: A Comparison of the AIMS, GMA, Pull to Sit Maneuver and ASQ-3
Bibliographic record
Abstract
BACKGROUND: Clinicians and parents should closely monitor the neurodevelopment of very preterm infants. The aim of our study was to compare whether neurodevelopmental assessments completed by parents and those done by specialists yielded similar outcomes. We wanted to check whether the assessments completed by specialists and parents were comparable in outcomes to emphasize the important roles of early assessment of a child and of the parents in their child's treatment and medical care. Another aim was to check whether or not the pull to sit maneuver from the Neonatal Behavioral Assessment Scale (NBAS) is still a parable item in well-known scales of neurodevelopment. METHODS: We assessed 18 preterm neonates in the fourth month of corrected age with scales such as the General Movement Assessment (GMA), the Alberta Infant Motor Scale (AIMS), and the pull to sit maneuver from the NBAS. Finally, we asked parents to complete the Ages and Stages Questionnaire, Third Edition (ASQ-3). RESULTS: We found that the respective assessments completed by specialists and parents are comparable in outcomes. We also found that the pull to sit item from the NBAS was still a valid test since it showed similar findings to those from the AIMS, the GMA, and the ASQ-3. CONCLUSIONS: The pull to sit item from the NBAS is an important item for assessment of very preterm infants. Specialists should also take into consideration the input and concerns of parents when planning for treatment and intervention.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".