Immediate and Long-Term Outcomes of Autologous and Alloplastic Cranioplasty in Pediatric Population
Bibliographic record
Abstract
Conventionally, alloplastic implants have been discouraged in pediatric cranioplasty due to concerns of infection and growth restriction. With the increasing development of patient-specific implants, this study compares the outcomes of pediatric cranioplasties using autologous grafts and alloplastic materials. A retrospective review was performed on all pediatric cranioplasties at a single institution between 2011 and 2024. The primary outcome measure was the conversion rate from autologous to alloplastic reconstruction. Secondary outcomes included assessment of age, sex, indication for surgery, defect size, location, operative time, medical history, and need for blood transfusion in cranioplasty groups. Over ∼13 years, 68 cranioplasties were identified in 57 patients. The mean patient age was 8.5 (range: 1.4-18.5). Twenty-nine cranioplasties were performed using autologous grafts (banked frozen bone flap or split thickness calvarial graft) and 39 used alloplastic implants, including titanium, polymethyl methacrylate, polyethylene titanium, and cadaveric allograft. The autologous cranioplasty group had a significantly greater complication rate (7/29), compared with the alloplastic group (3/39; P<0.05). The adjusted mean surface area defect was significantly greater in the alloplastic cranioplasty group, while no significant differences were observed in the location of the calvarial defect. When combined, the patients' age at the time of surgery was significantly higher in the cranioplasty group that had a complication compared with the cranioplasty group without any complications. The use of alloplastic implants in pediatric cranioplasties at our centre is not associated with a higher frequency of complications relative to autologous bone grafts.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".