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Record W1980831382 · doi:10.1177/08830738030180080901

Independent Walking After Neonatal Arterial Ischemic Stroke and Sinovenous Thrombosis

2003· article· en· W1980831382 on OpenAlexafffund
Meredith R. Golomb, Gabrielle deVeber, Daune MacGregor, Trish Domi, Hilary Whyte, Derek Stephens, Paul T. Dick

Bibliographic record

VenueJournal of Child Neurology · 2003
Typearticle
Languageen
FieldMedicine
TopicCerebral Venous Sinus Thrombosis
Canadian institutionsSickKids FoundationHospital for Sick Children
FundersHospital for Sick Children
KeywordsMedicineConfidence intervalHazard ratioStroke (engine)GaitProportional hazards modelPediatricsCohortCardiologyPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

Few studies have examined walking after neonatal arterial ischemic stroke and sinovenous thrombosis. We looked at the development of walking in a retrospective and consecutive cohort study of 88 term and near-term neonates. We used Kaplan-Meier survival curves and Cox proportional hazards models to assess (1) sex, (2) stroke type (arterial ischemic stroke or sinovenous thrombosis), (3) number of cerebral hemispheres with infarction, and (4) presence of neonatal comorbidity as predictors of the probability over time of starting to walk independently. These variables were assessed as predictors of parent-reported gait normality using the chi-square test on 2 x 2 contingency tables. Seventy-five of 83 survivors (90.4%, 95% confidence interval = 81.9-95.7) walked with a median time of first steps at 13 months of age (95% confidence interval = 12-14). Only bilateral strokes were associated with a lower probability over time of initiating independent walking (hazard ratio = 0.41, P = .04). Parents reported normal gait for 58 of 75 walkers (77.3%, 95% confidence interval = 67.8-86.8). No variables predicted parent-reported gait normality. Our findings suggest that most survivors of neonatal arterial ischemic stroke and sinovenous thrombosis walk with a gait that appears normal to parents, but bilateral infarctions decrease the probability over time of starting to walk independently.

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)0.000
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 score0.316
Threshold uncertainty score0.799

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.232
Teacher spread0.224 · 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

Citations44
Published2003
Admission routes2
Has abstractyes

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