Use of the GMFCS in infants with CP: the need for reclassification at age 2 years or older
Bibliographic record
Abstract
The stability of the Gross Motor Function Classification System (GMFCS) over time is described in 77 infants (41 boys, 36 girls) with cerebral palsy (CP; mean age 19.4mo [SD 1.6 mo]; 27 unilateral spastic, 42 bilateral spastic, eight dyskinetic type) and in the same children at follow-up at age 2 to 4 years. The overall level of agreement over time (linear weighted kappa) was 0.70 (95% confidence interval [CI] 0.61-0.79). The overall percentage of children whose GMFCS level changed one or two levels was 42%, of which the majority were reclassified to a less functional level (McNemar's Chi(2) test p=0.11). The chance that children initially classified in the combination of GMFCS Levels I, II, and III would subsequently be classified in the same level in early childhood was 96% (positive predictive value [PPV] 0.96, 95% CI 0.85-0.99), whereas the PPV for the combination of Levels I and II was 0.88, 95% CI 0.70-0.96. These findings indicate that GMFCS classification in infants is less precise than classification over time in older children. In conclusion, children can be classified by the GMFCS early on, but there is a need for reclassification at age 2 or older as more clinical information becomes available.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".