A Canadian Experience With Off-the-Shelf, Aseptically Processed, Costal Cartilage Segment Allografts in Complex Rhinoplasty
Bibliographic record
Abstract
Background: Complex primary and secondary rhinoplasties usually necessitate grafting materials when native nasal cartilage is inadequate for reconstruction. Fresh frozen, aseptically processed, and nonterminally sterilized costal cartilage segment allografts (CCSAs) are a novel grafting material for such cases that avoid donor-site morbidity, improve operating efficiency, and mitigate the postoperative risks. Objectives: To report the early experience using fresh frozen, aseptically processed, and nonterminally sterilized CCSAs used in complex primary and secondary rhinoplasties, in Canada. Methods: We retrospectively reviewed 21 patients (17 female and 4 male patients) who underwent a primary or secondary rhinoplasty surgery using CCSAs from June 2019 to April 2022. Results: ). Of the 21 procedures, 11 were primary (52.4%) and 10 were secondary (47.6%) rhinoplasties. The mean operative time was 185 min (range, 85-330 min), with a mean follow-up time of 15.0 months (range, 2.0-37.8 months). At follow-up, 19 patients (90.5%) reported being "very satisfied" with their aesthetic results, and only 2 (9.5%) underwent revision surgery. No serious complications were reported, and only 1 case showed evidence of graft resorption. Conclusions: Based on early experience, this CCSA avoids donor-site morbidity and reduces operative time while maintaining a low complication rate, providing a viable alternative to the use of autologous costal cartilage when indicated in complex primary or secondary rhinoplasties with inadequate native nasal cartilage.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".