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Record W2121971036 · doi:10.1017/s1047951115000797

Motor skills of 5-year-old children who underwent early cardiac surgery

2015· article· en· W2121971036 on OpenAlexaff
Beverley Eldridge, Susan R. Harris, Michael M.H. Cheung

Bibliographic record

VenueCardiology in the Young · 2015
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsUniversity of British Columbia
FundersHeartKids AustraliaAustralian GovernmentWilson Foundation
KeywordsMedicineCohortGross motor skillPediatricsMotor skillCohort studyPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

UNLABELLED: Aims To describe the motor proficiency of 5-year-old children who underwent early infant cardiac surgery and had atypical infant gross motor development. To identify risk factors for motor dysfunction at 5 years of age. METHODS: A total of 33 children (80.5% participation rate) were re-assessed by a physiotherapist blinded to the diagnosis and previous clinical course, using standardised motor assessment tools. RESULTS: Motor proficiency was categorised as below average or well below average in 41% of the study patients. Approximately 30% of the cohort had balance deficits. Motor abilities at 4 months and 2 years of age were associated with motor proficiency at age 5; however, atypical motor development in infancy was not predictive of below-average or well below-average scores at age 5. Risk factors associated with motor ability at age 5 included respiratory support and intensive care length of stay in the 1st year of life, asymmetrical crawling in infancy, and cyanotic CHD at age 5. CONCLUSIONS: Despite differences from other reported studies in terms of cohort diagnoses and age at surgery, the rate of motor dysfunction was similar, with rates much higher than expected in typical children. Further assessment is needed in later childhood to determine the significance of these findings.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.246
Teacher spread0.230 · 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 source (direct Gemma or distilled Codex), 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

Citations11
Published2015
Admission routes1
Has abstractyes

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