Gross motor change after inpatient rehabilitation for children with acquired brain injury: A 10‐year retrospective review
Bibliographic record
Abstract
AIM: To estimate gross motor change in inpatient school-aged children with subacute acquired brain injury (ABI), identify factors associated with gross motor change, and describe inpatient physiotherapy focus. METHOD: This retrospective chart review involved inpatient children (5-18 years) with subacute ABI who had either two Gross Motor Function Measure (GMFM-88) assessments or one GMFM-88 with another pre/post gross motor outcome measure. Outcome change scores and Goal Attainment Scaling (GAS) T scores were calculated. Regression analyses examined factors predicting gross motor change. GAS goal areas were analysed to determine physiotherapy focus. RESULTS: Of the 546 charts screened, 266 (118 female) met study criteria. The GMFM-88 was generally administered first, followed by other measures. GMFM-88 (n = 202), Community Balance and Mobility Scale (n = 89), and Six-Minute Walk Test (6MWT) (n = 98) mean change scores were 18.03% (SD 19.34), 17.85% (SD 10.77), and 142.3 m (SD 101.8) respectively. The mean GAS T score was 55.06 (SD 11.50). Lower baseline scores and increased time between assessments were most predictive of greater GMFM-88 change (r ≥ 0.40). Twenty-five percent of GAS goals were ambulation-based. INTERPRETATION: Appropriate outcome measure selection is integral to detecting gross motor change in pediatric inpatient ABI rehabilitation. Mean change score estimates can be used to compare standard inpatient rehabilitation with new treatment approaches.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".