Ultrasound‐guided left internal jugular vein cannulation: Advantages of a lateral oblique axis approach
Bibliographic record
Abstract
INTRODUCTION: Retrospective observational study to evaluate the technique of cannulation guided by ultrasound of the left internal jugular vein (LIJV) using a lateral oblique axis (LOAX) approach with variable angulation in the placement of tunneled central venous catheters (CVC) for hemodialysis. METHODS: Seventy-one patients with 77 LIJV vascular accesses aged 16 or older who needed CVC for hemodialysis were evaluated. The catheters were inserted, guided by LOAX ultrasound with variable angulation, depending on the angulation of the left brachiocephalic trunk. The success rate, additional instrumentation needs, and number of immediate and late complications were analyzed. FINDINGS: Central venous catheters placement was possible in all cases and none of the peelable introducers folded. A placement guide was needed in only eight patients, whose brachiocephalic trunk elongation and angulation was 90°. We found no major complications, and only five cases of minor complications (6.5%): four periprocedural and one displacement of the catheter a week after placement. DISCUSSION: Tunneled CVC percutaneous cannulation in LIJV guided by ultrasound with the LOAX approach with variable angulation provides very good results, allows visualization of the needle and the vascular structures at the same time, and reduces the number of manoeuvers required for placement and complications that might arise.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".