Cephalic vein cutdown for totally implantable central venous port in children: a retrospective analysis of prospectively collected data
Bibliographic record
Abstract
BACKGROUND: The jugular vein cutdown for a totally implantable central venous port (TICVP) has 2 disadvantages: 2 separate incisions are needed and the risk for multiple vein occlusions. We sought to evaluate the feasibility of a cephalic vein (CV) cutdown in children. METHODS: We prospectively followed patients who underwent a venous cutdown for implantation of a TICVP between Jan. 1, 2002, and Dec. 31, 2006. For patients younger than 8 months, an external jugular vein cutdown was initially tried without attempting a CV cutdown. For patients older than 8 months, a CV cutdown was tried initially. We recorded information on age, weight, outcome of the CV cutdown and complications. RESULTS: During the study period, 143 patients underwent a venous cutdown for implantation of a TICVP: 25 younger and 118 older than 8 months. The CV cutdown was successful in 73 of 118 trials. The 25th percentile and median body weight for 73 successful cases were 15.4 kg and 28.3 kg, respectively. There was a significant difference in the success rate using the criterion of 15 kg as the cutoff. The overall complication rate was 8.2%. CONCLUSION: The CV cutdown was an acceptable procedure for TICVP in children. It could be preferentially considered for patients weighing more than 15 kg who require TICVP.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".