Survival and infection rates of microvascular free flaps in pediatric mandibular reconstruction: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Background Vascularized free tissue transfer has been established as an effective method in the reconstruction of mandibular defects. However, a limited understanding of its efficacy in pediatric patients persists due to its infrequent presentation. The aim of this study is to systematically consolidate the survival and infection rates of free flaps in pediatric mandibular reconstruction. Methods A systematic literature search was conducted on Ovid Medline, Embase, and Cochrane Library for studies published up to January 2024. We included peer‐reviewed studies reporting on survival and infection outcomes associated with free flap mandibular reconstruction in pediatric patients (<18 years). We performed a random‐effects meta‐analysis with the inverse‐variance weighted approach to estimate survival and infection rates. Heterogeneity was assessed by I 2 , and publication bias was examined using Egger's test. Results A total of 26 studies, reporting on 463 free flaps and 439 pediatric patients with a mean age of 10.7 years, were included in our study. Most free flaps originated from the fibula ( n = 392/463, 84.7%) and benign tumors were the most common cause for mandibular reconstruction ( n = 179/463, 38.7%). The pooled estimate for survival of flaps was 96% (95% CI: 93–97, I 2 = 0%), and recipient‐site infections were estimated to occur in 9% (95% CI: 6–13, I 2 = 0%) of cases. The most common reported complications within the study timeframe were early malocclusion ( n = 28/123, 21.4%) and bite abnormalities (18/131, 13.7%). Conclusion Free tissue transfer for mandibular reconstruction in pediatric patients is effective and safe. Further research is required to explore functionality following mandibular reconstruction in diverse pediatric populations.
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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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.041 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".