Percutaneous cryoablation of abdominal wall endometriosis: a systematic literature review of safety and efficacy
Bibliographic record
Abstract
PURPOSE: To investigate over 10 years the safety and efficacy of percutaneous cryoablation for the treatment of abdominal wall endometriosis (AWE). METHODS: A systematic review was conducted of literature published between March 2014 and March 2024. Inclusion criteria focused on treatment efficacy studies, while exclusion criteria targeted case reports and studies lacking pertinent outcome data. Methodological quality was assessed using the Newcastle-Ottawa Scale for cohort studies. RESULTS: A total of eight studies were included. Local pain scores decreased from a median of 8/10 (interquartile range (IQR) 7-9) on the visual analog scale to 1/10 (IQR 0-2) at the last follow-up (p < 0.0001). Median complete local pain response rates ranged from 80% to 100%, with median local pain-free survival rates reaching 76.8% (IQR 55.3-83.8) at the longest follow-up. Notably, no patient reported a post-procedure pain score higher than that they reported pre-cryoablation. The studies indicated minor complications in 3.5 to 11% of cases, with major complications occurring in less than 2% of cases, graded following the guidelines of the Society of Interventional Radiology. CONCLUSION: In the last decade, percutaneous image-guided cryoablation has offered consistent results and appears to be a promising, minimally invasive option for AWE treatment. Prospective trials are now essential to establish cryoablation as a new standard in patient care for AWE. CRITICAL RELEVANCE STATEMENT: Over a decade-long study, percutaneous cryoablation has proven to be a safe and effective minimally invasive treatment for abdominal wall endometriosis, significantly reducing pain with minimal complications. KEY POINTS: Percutaneous cryoablation significantly reduced local pain scores for abdominal wall endometriosis. The procedure demonstrated a favorable safety profile with minor complications. Cryoablation has emerged as a minimally invasive alternative to traditional treatments.
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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 | 0.015 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".