Surgical placement of rectus sheath catheters in a cadaveric cystectomy model
Bibliographic record
Abstract
Introduction Surgically inserted rectus sheath catheters (RSCs) are used increasingly for analgesia after cystectomy and other abdominal surgery. Currently, there is little information on the optimal positioning of RSCs to allow maximal spread of local anaesthetic. This study sought to assess the spread of dye injected via RSCs and to highlight the extent of its coverage in a fresh unembalmed cadaveric cystectomy model in order to confirm the nerve endings that are likely to be anaesthetised with RSCs. Methods Four cadavers underwent lower midline incision with limited bladder mobilisation. A RSC was inserted into the eight hemiabdomens. The RSCs were positioned either anterior (n=5) or posterior to the rectus muscle (n=3). Dye was injected down the RSCs to evaluate spread. The eight hemiabdomens were dissected anatomically to determine the surface area of dye spread and nerve root involvement. Results The mean surface area of dye spread with anteriorly placed RSCs was 30.6cm2 anterior and 25.9cm2 posterior to the rectus muscle. The mean surface area of dye spread with posteriorly placed RSCs was 11.3cm2 anterior and 37.3cm2 posterior to the rectus muscle. The mean number of nerve roots stained with anteriorly and posteriorly placed RSCs was 3.8 and 2.7 respectively. Subcutaneous spread of dye was seen with one anterior RSC insertion. Peritoneal spread was seen with one anteriorly positioned RSC. Conclusions This study has demonstrated efficient nerve root infiltration with anteriorly and posteriorly positioned RSCs. It appears that dye spreads between the fibres of the rectus muscle rather than out laterally to the nerve roots when spreading from its initial compartment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".