Contracture Severity at Hospital Discharge in Children: A Burn Model System Database Study
Bibliographic record
Abstract
Contractures can complicate burn recovery. There are limited studies examining the prevalence of contractures following burns in pediatrics. This study investigates contracture outcomes by location, injury, severity, length of stay, and developmental stage. Data were obtained from the Burn Model System between 1994 and 2003. All patients younger than the age of 18 with at least one joint contracture at hospital discharge were included. Sixteen areas of impaired movement from the shoulder, elbow, wrist, hand, hip, knee, and ankle joints were examined. Analysis of variance was used to assess the association between contracture severity, burn size, and length of stay. Age groupings were evaluated for developmental patterns. A P value of less than .05 was considered statistically significant. Data from 225 patients yielded 1597 contractures (758 in the hand) with a mean of 7.1 contractures (median 4) per patient. Mean contracture severity ranged from 17% (elbow extension) to 41% (ankle plantarflexion) loss of movement. Statistically significant associations were found between active range of motion loss and burn size, length of stay, and age groupings. The data illustrate quantitative assessment of burn contractures in pediatric patients at discharge in a multicenter database. Size of injury correlates with range of motion loss for many joint motions, reflecting the anticipated morbidity of contracture for pediatric burn survivors. These results serve as a potential reference for range of motion outcomes in the pediatric burn population, which could serve as a comparison for local practices, quality improvement measures, and future research.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".