The true pelvic volume change with various corrective osteotomy techniques for exstrophy-epispadias complex spectrum: the value of computer-assisted virtual surgery
Bibliographic record
Abstract
Pelvic osteotomies are essential to approximate widened symphysis pubis in the exstrophy-epispadias complex, yet it is unknown which osteotomy type has the greatest effect on pelvic volume. We therefore used virtual surgery to study pelvic volume change with anterior, oblique, and posterior iliac osteotomies. Preoperative CT scans of two cloacal and one classic bladder exstrophy patients were used. Simulations were free-hand or constrained to keep minimal strain in the sacrospinous SSL and sacrotuberous STL ligaments. Changes in inter-pubic distance, pelvic volume, SSL and STL strains were measured. Mean pelvic volume decreased by 10% with free hand compared to 23% with constrained simulations ( P = 0.171) and decreased by 7% with posterior, 17% with diagonal and 26% with horizontal osteotomies ( P = 0.193). SSL and STL were strained by 20% and 26%, respectively, with free-hand simulations. A statistically significant moderate positive correlation was found between the decrease in inter-pubic distance and reduction in pelvic volume (r = 0.6, P = 0.004). Mean pelvic volume decreased 0.05, 0.37 and 0.62% for each mm of pubic symphysis approximation with posterior, diagonal and horizontal osteotomies, respectively. Differences in effect on pelvic volume were identified between the osteotomies using virtual surgery which predicted residual diastasis in actual cloacal exstrophy surgical reconstructions. Oblique osteotomies are a compromise, avoiding difficulties with posterior osteotomies and excessive pelvic volume reduction with horizontal osteotomies. Understanding how osteotomy type affects pelvic morphology with virtual surgery may be an effective adjunct to pre-operative planning in exstrophy spectrum.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".