MR scan evaluation of pelvic organ prolapse mesh complications and agreement with intra-operative findings
Bibliographic record
Abstract
INTRODUCTION: An increasing number of women are presenting with symptoms after the placement of mesh implants for prolapse which may be attributable to a mesh implant complication. MRI imaging can be used to evaluate abdominally placed mesh but there is no published research evaluating the use of MRI in this group of women. The objective of our study was to report our experience as a tertiary centre in evaluating abdominal mesh with MR imaging and the agreement of MR reports with surgical findings. STUDY DESIGN: A retrospective observational cohort study (Canadian Task Force classification II-2) of all women referred to our tertiary unit who underwent an MR scan for investigation of symptoms of mesh complication following an abdominally placed mesh implant between June 2006 and September 2018 was performed. The reports of MR images were compared with the findings at surgery. RESULTS: MR scan was performed in 87 with suspected mesh complications. MR scan detected mesh failure in 42.1% of women (37/87), infection in 12.6% (11/87), compression in 2.3% (2/87), exposure in 12.6% (11/88), bowel extrusion in 2.3% (2/87) and inflammation in 11.5% (10/87). Agreement between MR scan report and surgical diagnosis was almost perfect for mesh failure, infection and compression, whilst agreement was only moderate for mesh erosion and signs of inflammation (failure κ = 0.97, infection κ = 0.94, compression κ = 1.0, exposure κ = 0.58 and inflammation κ = 0.24). CONCLUSION: These data provide information on the role of MR imaging in the investigation of women presenting with suspected intra-abdominal POP mesh complications including recurrence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.002 | 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 teacher head, 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".