Buccal Mucosal Grafts as a Novel Treatment for the Repair of Rectovaginal Fistulas: Protocol for an Upcoming Prospective Single-Surgeon Case Series (Preprint)
Bibliographic record
Abstract
BACKGROUND Rectovaginal fistulas (RVFs) are abnormal communications between the rectum/anus and the vagina. They are most frequently formed a result of obstetric injury and have deleterious effects on patients’ quality of life. Despite several treatment modalities, RVFs remain difficult problems to manage, and many patients fail multiple attempts at surgical repair. Buccal mucosal grafts (BMGs) may be a solution to this problem. A BMG is an oral mucosal tissue harvested from the inner cheek. There are 2 case reports that describe the successful use of BMGs in the repair of RVFs. OBJECTIVE Our objective is to validate these findings with a prospective case series while also addressing the key issues of indication, technical details, procedure safety, and short-term outcomes. METHODS A prospective single-surgeon case series will be undertaken at a university-affiliated academic tertiary care hospital in Calgary, Alberta (Canada). The estimated recruitment is between 3 and 5 patients. Patients will undergo surgical repair of their RVFs with an autologous BMG. Data on patient characteristics, fistula characteristics, and surgical variables will be collected and analyzed prospectively. The primary outcome is fistula closure. This study has been approved by the Conjoint Health Research Ethics Board at the University of Calgary (REB20-1123). RESULTS Two previous case reports have described the successful use of BMGs in the repair of RVFs. We have received ethics approval to attempt to validate these findings through a prospective case series. CONCLUSIONS RVFs cause significant patient morbidity and are difficult problems to manage. Bolstered by the successful use of BMGs in urologic surgery and the previously published case reports demonstrating success in RVFs, we believe that BMGs may be a solution to RVFs. INTERNATIONAL REGISTERED REPORT PRR1-10.2196/31003
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 | 0.011 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.008 |
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".