P095 ARE POLYPROPYLENE MESH IMPLANTS ASSOCIATED WITH SYSTEMIC AUTOIMMUNE/INFLAMMATORY SYNDROMES?
Bibliographic record
Abstract
Abstract Aim Worldwide there is a lot of commotion about the effects and complications of mesh implants. The surgical implantation of polypropylene (PP) meshes has been linked to the occurrence of systemic autoimmune disorders (SAIS). We performed a systematic review to determine whether PP implants for inguinal, ventral hernia or pelvic floor surgery are associated with the development of SAIS. Material and Methods We searched Embase, Medline, Web of Science, Scopus, Cochrane library, clinicaltrialsregister.eu, clinicaltrails.gov and WHO-ICTR platform. Forward and backward reference searching was performed to avoid missing relevant papers. All types of studies, except case studies, reporting SAIS in patients having a PP implant for either pelvic floor surgery, ventral or inguinal hernia repair were included. Animal studies were excluded. We intended to perform a meta-analysis. The quality of evidence was assessed with the Newcastle-Ottawa Scale. This study was registered at Prospero (CRD42020220705). Results Of 1938 records identified, 3 were eligible. Two studies involving retrospective matched cohorts focused on mesh surgery for vaginal prolapse or inguinal hernia compared to hysterectomy and colonoscopy, respectively. These reports had a low risk of bias. The third study was a case-series with a high risk of bias, with a sample of 714 patients with systemic disease, 40 of them had PP mesh implanted. A meta-analysis showed no association when comparing systemic disease between mesh and control groups. Calculated Risk Ratio was 0.9 (95%CI 0.78-1.04). Conclusions To date, there is no evidence to suggest a causal relationship between being implanted with a PP mesh and the occurrence of SAIS.
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".