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Record W2939866825 · doi:10.1101/609313

Improvements in upper extremity function in children with unilateral spastic cerebral palsy after intensive training correlates with interhemispheric connectivity

2019· preprint· en· W2939866825 on OpenAlexaboutno aff
Maxime T. Robert, Jennifer Gutterman, Claudio L. Ferre, Karen Chin, Marina B. Brandão, Andrew M. Gordon, Kathleen M. Friel

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsCorpus callosumSpleniumPhysical medicine and rehabilitationDiffusion MRIConstraint-induced movement therapyMedicinePsychologyRehabilitationPhysical therapyUpper limbMagnetic resonance imagingNeuroscienceRadiology

Abstract

fetched live from OpenAlex

Abstract AIMS The corpus callosum (CC) regulates signalling between the two hemispheres and plays an important role in upper limb functions. There is limited evidence on the relationships between the integrity of the CC and upper limb functions in children with USCP. Furthermore, the extent of how much the CC can be used as a biomarker to predict hand functions following intensive interventions remains unknown. We examined 1) the relationship between hand function and tractography of the CC, and 2) the associations between the integrity of the CC and changes in hand function following intensive intervention. METHODS Forty-four participants received 90 hours of intensive therapy and were randomly allocated in one of two training groups: Hand-arm Bimanual Intensive Therapy (HABIT) or Constraint-Induced Movement Therapy (CIMT). Hand functions were assessed pre-and post-intervention by a blinded clinician using the Jebsen-Taylor of Hand Function (JTTHF), Assisting Hand Assessment (AHA), and Box and Blocks test (BBT). Functional goals and daily functioning were measured using the Canadian Occupational Performance Measure and the Abilhand-Kids. CC tractography was reconstructed using diffusion tensor imaging (DTI). Corpus callosum was segmented into three regions of interest (genu, midbody and splenium). Linear regression and pearson correlations were used to assess the relationships between bimanual outcomes and DTI parameters. RESULTS Both groups demonstrated improvement of hand function (p<0.05). JTTHF, AHA and BBT significant correlated with DTI variables for all ROIs (p<0.05). Bimanual and perceived manual ability of children changes following CIMT were negatively correlated with number of streamlines and number of voxel for the whole CC (r=-.442, p=0.05), midbody (r=-.458, p=0.042) and spelnium (r=-.512, p=0.021). No significant correlation was observed for the HABIT group. INTERPRETATION Tractography of the CC was found to be associated with unimanual and bimanual functions at baseline. Children with reduced integrity of the CC and with greater bimanual impairments improve more from CIMT. On the contrary, all children in the HABIT group had similar improvements independent of the CC integrity.

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)0.002
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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.000

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 head0.009
GPT teacher head0.204
Teacher spread0.195 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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