Natural history of gait patterns in untreated children with bilateral cerebral palsy in a low‐income country setting
Bibliographic record
Abstract
AIM: To assess a group of ambulant, untreated children with bilateral spastic cerebral palsy, in a resource-poor setting, who had never been assessed by a health care professional or received any treatment, to help establish the natural history of gait patterns in this condition. METHOD: At CURE Children's Hospital of Ethiopia, 46 children with no prior health care contact were assessed in a cross-sectional cohort study, through a detailed history, clinical examination, and instrumented gait analysis using a motion capture system. RESULTS: There was a large spread in the data reflecting the high natural heterogeneity in this population. The severity of gait pathology did not correlate with age; however, a small but significant reduction in sagittal hip and knee range of motion with increasing age was observed. There was also a trend towards reduced passive knee extension with age. INTERPRETATION: Improved understanding of the aspects of gait that are likely to naturally improve, deteriorate, or remain stable over time helps guide treatment decisions in this population.
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 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".