Pediatric Diaphyseal Forearm Fracture Management with Biodegradable Poly-L-Lactide-Co-Glycolide (PLGA) Intramedullary Implants: A Longitudinal Study
Bibliographic record
Abstract
Background: Pediatric forearm fractures represent a substantial proportion of childhood injuries, requiring effective and minimally invasive treatments. Our study investigated the mid-term outcomes of biodegradable poly-L-lactide-co-glycolide (PLGA) intramedullary implants in managing diaphyseal forearm fractures in children. Methods: A follow-up cohort study was conducted with 38 patients treated with PLGA implants. Control examinations were performed one year post-operation, assessing bone healing through radiographic evaluations and functional outcomes using injured and uninjured limb range of motion (ROM) comparisons. Scarring was evaluated employing the Vancouver Scar Scale (VSS), and satisfaction via a questionnaire. Results: Children were predominantly female (76.4%), with a mean age of 9.71 (SD: 2.69) years. Effective fracture stabilization and bone healing were found in all patients, with a minor reduction (mean difference of -1.5°, p = 0.282) in elbow flexion on the operated side (139.3°) compared to the intact (140.8°). Elbow extension presented negligible average changes (0.2°, p= 0.098). Forearm movements were slightly reduced on the operated side (mean pronation: 80.8° vs. 83.7°, p= 0.166; average supination: 83.5° vs. 85.7°, p= 0.141). Wrist palmar flexion and dorsiflexion showed no significant differences. VSS ratings indicated minimal scarring (mean guardian and doctor scores were 1.13 and 0.55, respectively, p= 0.020), and all patients reported satisfaction with the treatment outcomes. Conclusion: Biodegradable implants are effective for pediatric forearm fractures, providing stable bone healing while preserving functional ROM with minimal scarring and high patient satisfaction. PLGA proved to be a viable alternative to traditional metal implants, eliminating secondary removal surgeries.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".