Botulinum Toxin and Progressive Pneumoperitoneum in Loss of Domain Ventral Hernias: A Systematic Review
Bibliographic record
Abstract
Introduction: Preoperative progressive pneumoperitoneum (PPP) and botulinum toxin A (BTX) have been used together in the preoperative preparation of patients with loss of domain hernias. This study aims to evaluate the efficacy and safety of the combined use of PPP and BTX. Methods: A systematic electronic search was performed according to the PRISMA criteria. A literature search of scientific articles was conducted up to December 2023. Articles were chosen based on the reference to BTX and PPP in loss of domain ventral hernias with a defect width greater than 10 cm before surgery. The GRADE methodology and the modified Newcastle-Ottawa scale were used to assess the quality of the studies. Results: The research yielded seven articles, with 217 patients analysed in total. BTX was performed 29.5 ± 1.7 days before surgery and PPP was inflated 14.8 ± 5.8 days before surgery. PPP complications were reported in 25.6% of patients, The average reduction of the volume of hernia (VH)/volume of the abdominal cavity (VAC) ratio was 7.6% (range 0.9%–15%). Only 40 patients (18.4%) required a PCS or TAR to repair the loss of domain hernias. The SSI and SSO rates were 17.5% and 26.2%, respectively. No differences in SSI and SSO rates were found between the different repair techniques. The recurrence rate was 5.9% (13/217). Recurrence was significantly higher in patients who underwent IPOM repair than other techniques (p < 0.001). Conclusion: BTX and PPP may be useful tools for the management of loss of domain hernias presenting lower SSI and SSO. The combination of BTX and PPP reduces the use of more invasive repair techniques.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".