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The relationship of cerebral palsy subtype and functional motor impairment: a population‐based study

2009· article· en· W1560006339 on OpenAlexafffundabout
Michael Shevell, Lynn Dagenais, Nicholas R. Hall

Bibliographic record

VenueDevelopmental Medicine & Child Neurology · 2009
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsMontreal Children's HospitalCentre Hospitalier Universitaire Sainte-JustineMcGill University
FundersFondation de l'Hôpital de Montréal pour enfantsChildren's Hospital FoundationUniversité Laval
KeywordsGross Motor Function Classification SystemCerebral palsySpasticMedicinePhysical therapyPopulationGross motor skillPhysical medicine and rehabilitationMotor impairmentPediatricsConfidence intervalPsychologyMotor skillInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

AIM: Traditionally, cerebral palsy (CP) had been classified according to the distribution and quality of motor impairment. A standardized functional classification of gross motor skills has recently been validated - the Gross Motor Function Classification System (GMFCS). The relationship between the neurological subtype of CP and GMFCS level remains undefined in CP. METHOD: The Quebec Cerebral Palsy Registry (Registre de la paralysie cérébrale au Québec [REPACQ]) over a 4-year birth interval (1999-2002 inclusive) identified 301 children with CP. Information on both CP subtype and GMFCS level was available for 243 children (138 males, 105 females) with final data extraction at a mean age of 44 months (SD 14mo, range 24-79mo). Proportions of children with a particular CP subtype at GMFCS levels I to III versus levels IV to V were determined and compared. RESULTS: CP subtype versus GMFCS levels I to III or IV to V was distributed proportionally as follows: spastic diplegic, 51/52 (98%) versus 1/52 (2%); spastic quadriparetic, 20/85 (24%) versus 65/85 (76%); spastic hemiplegic, 76/77 (99%) versus 1/77 (1%); dyskinetic, 4/16 (25%) versus 12/16 (75%); other (triplegic or ataxic-hypotonic), 10/13 (77%) versus 3/13 (23%). These distributions (proportions) all yielded significant (p<0.001) Pearson chi(2) values. INTERPRETATION: Neurological subtype is a powerful predictor of functional status related to ambulation. This has implications for counseling families.

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 score0.023
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.021
GPT teacher head0.260
Teacher spread0.239 · 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

Citations178
Published2009
Admission routes3
Has abstractyes

Explore more

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