Complications Associated with Cervical Cerclage
Bibliographic record
Abstract
Cervical cerclages are associated with improved live birth rates and have low short- and long-term risks. However, there have been reports of fistula formation or erosion of cerclage into the surrounding tissue. Those complications are uncommon and yet are serious. The risk factors associated with its development are still unclear. The purpose of our study was to evaluate the incidence of fistula formation or erosion following transvaginal cervical cerclage and the associated clinical and sociodemographic factors. We conducted a systematic search of PubMed, Medline, and Embase databases to retrieve articles related to transvaginal or transabdominal cervical cerclage. Databases were searched up to July 2021. The study protocol was registered (PROSPERO ID 243542). A total of 82 articles were identified describing cervical cerclage and erosion or fistula formation. A total of 9 full-text articles were included. There were seven case reports and series that described 11 patients who experienced late complications following cervical cerclage. Many of the cerclage procedures were done electively (66.7%). The most common type of cerclage was McDonald (80%). While all cases reported fistula formation, the main location was vesicovaginal fistulas (63.6%). One patient (9.1%) had erosion of their cerclage and another (9.1%) had bladder calculi. Of 75 patients who underwent cerclage in two retrospective case reviews, the overall incidence of fistula was 1.3% and abscess was also 1.3%. Although rare, the most common long-term complication of cervical cerclage placement is fistula formation, particularly vesicovaginal fistulas.
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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 | 0.002 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".