DEVELOPMENT AND PRECLINICAL TESTING OF A PROTOTYPE LEVOBUPIVACAINE-ELUTING DEVICE FOR THE TREATMENT OF POSTOPERATIVE PAIN FOLLOWING INGUINAL HERNIA REPAIR
Bibliographic record
Abstract
Background and AimsInguinal hernia repair is a common surgical procedure [1], after which up to 40% of patients report significant acute pain and 10% develop chronic pain [2,3]. We aim to develop a collagen-based mesh system to elute levobupivacaine to effectively manage acute pain.MethodsCollagen and levobupivacaine were chosen based on their desirable safety/biocompatibility/efficacy. Elution experiments tested collagen alone (2-10mg/ml) and crosslinked by various concentrations of EDC/NHS (0.1-1000mM).Twenty-three rats (n=5-6/group) underwent sham procedure, hernioplasty alone or with the collagen/mesh device loaded with 50mg or 100mg levobupivacaine. Open Field (OF) and Von Frey (VF) testing occurred at baseline(-24hrs), and 4, 24 & 48hrs post-surgery. Locomotor activity was also assessed in the homecage. Animals were euthanised 48hrs post-surgery.ResultsFollowing optimisation, elution of the maximum loadable drug was achieved over 48hrs. Surgery reduced locomotor activity in the OF 4hrs post-surgery and in the homecage during the first 4hrs post-surgery. Surgery also significantly increased responsiveness to VF filaments at 24 hrs. Reduced locomotor activity and increased responsiveness in the VF are important pain-related phenotypes in this model. Homecage and OF locomotor activity was unaffected by the 50 and 100mg devices. The 100mg device significantly reduced responsiveness in the VF test compared to controls at 24 hrs. ConclusionsThese data suggest that the device may be effective in alleviating mechanical allodynia following inguinal hernia repair. Improved effectiveness may be achieved by increasing the dose or testing alternative analgesics. AcknowledgementsFinancial support from Science Foundation Ireland (SFI) and co-funded under the European Regional Development Fund, Grant Number 13/RC/2073.References[1] Jenkins & Ou2019Dwyer, (2008) BMJ, 336(7638); 269-272.[2] McGrath et al., (2008) Canadian Journal of Anaesthesia, 51(9); 886-91.[3] Aasvang (2005) British Journal of Anaesthesia, 95(1); 67-96
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".