Comparison of Distraction Osteogenesis and Single-Stage Remodeling for Correction of Unilateral Coronal Craniosynostosis
Bibliographic record
Abstract
BACKGROUND: Unilateral coronal craniosynostosis is a challenging condition in craniofacial surgery. Frontoorbital advancement by single-stage resorbable remodeling and distraction osteogenesis (DO) techniques have known intraoperative differences, but their comparative outcomes are less well characterized. METHODS: A systematic literature search of the MEDLINE, EMBASE, LILACS, and Web of Science databases was conducted. The search was performed using terms related to craniosynostosis and its operative management. The primary outcome of interest was the Whitaker classification. Secondary outcomes included cranial volume or cranial index change, and infection and reoperation rates. RESULTS: A total of 6978 eligible articles were identified of which 26 met inclusion criteria. A total of 292 patients were included in the studies, with 223 undergoing a single-stage remodeling procedure (76.4%) and 69 DO procedures (23.6%). There was a trend toward patients with DO having better Whitaker aesthetic outcomes. Only 2 studies reported volumetric changes. There was a substantial difference in planned and unplanned reoperation rates but not in infection rates. CONCLUSION: The results of this systematic review suggest that the techniques have similar outcomes and complications, although there was a trend toward better Whitaker outcomes with DO procedures. Inherent to the DO technique is the need for multiple operations to both insert and remove internal hardware which may affect the overall cost effectiveness.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".