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Record W2615898888 · doi:10.2223/jped.1741

Evaluation of motor performance of preterm newborns during the first months of life using the Alberta Infant Motor Scale (AIMS)

2008· article· en· W2615898888 on OpenAlexaboutno aff
Magda Lahorgue Nunes

Bibliographic record

VenueJornal de Pediatria · 2008
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGestational ageBirth weightSupine positionPediatricsPercentileSittingCohortNeonatal intensive care unitMotor skillProspective cohort studyPregnancyAnesthesiaSurgeryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To evaluate the motor performance of premature neonates using the Alberta Infant Motor Scale (AIMS) and to investigate the influence of birth weight on motor acquisition. METHODS: A cross-sectional study was carried out of a prospective cohort of 44 premature newborn infants with gestational ages from 32 to 34 weeks, without neurological disorders, selected from the neonatal intensive care unit at the Pontifícia Universidade Católica's Hospital São Lucas in Rio Grande do Sul, Brazil. The neonates studied were stratified by birth weight and assessed using the AIMS scale at the 40th week of postconceptional age, and at 4 and 8 months of corrected age. RESULTS: The preterm infants studied exhibited a progressive sequence of motor ability acquisition in all of the positions tested (prone, supine, sitting, standing), which occurred variable manner, expressed by the mean percentile of 43.2 to 45.7%, but within the limits of normality defined by the AIMS. It was observed that there was a clear increase in AIMS scores from the first to the last of the three postnatal observation points. The rate at which these scores increased was similar for both groups, irrespective of birth weight category (<1,750 g or >or= 1,750 g). CONCLUSIONS: The motor performance of the sample of premature infants studied here was normal according to the AIMS and their scores on that scale were not influenced by birth weight.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.340

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 head0.022
GPT teacher head0.258
Teacher spread0.236 · 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

Citations40
Published2008
Admission routes1
Has abstractyes

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