Thoracic epidural catheters via the caudal and lumbar approaches using styletted multiple port catheters in pediatric patients: a report of three cases
Bibliographic record
Abstract
Advancing catheters from the lumbar and caudal epidural spaces to the thoracic level has been reported to be an alternative to the direct thoracic approach. However, as children grow, the threading of catheters in the epidural space becomes increasingly difficult. This report describes three cases of thoracic epidural placement using a multiport catheter threaded from the caudal and lumbar spaces using electrical stimulation guidance. In the first case, a multiport catheter was threaded 22 cm from the lumbar space to T8 following a failed attempt with a single-port catheter in a 9-year-old boy scheduled to undergo a right nephrectomy. In the second case, a multiport catheter was threaded 26 cm from the caudal space to T9 in a 3-year-old girl undergoing fundoplication. In the last case, a multiport catheter was inserted at the completion of a fundoplication in a 2-year-old girl after it had been confirmed that the single-port catheter inserted prior to surgery had not advanced to the desired thoracic level. The multiport catheter was threaded 17 cm without resistance from the caudal space to T9. In all cases, electrical stimulation was used to confirm the location of the catheter tip at the time of insertion. The position of the catheters was later confirmed by X-ray. The multiport catheter incorporates a stylet, which extends to a closed distal tip, within a catheter body that ejects fluid from three lateral holes in a direction perpendicular to the advancing catheter. These properties may facilitate the reliable advancement of catheters in the epidural space.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".