Treatment Strategies for Refractory Catheter‐Related Central Venous Occlusive Disorders: Review
Bibliographic record
Abstract
BACKGROUND: Catheter-related central vein occlusive disease (CVOD) is a frequent complication in hemodialysis patients and significantly affects their prognosis. Current treatment options for catheter-related CVOD include standard guidewire and catheter techniques, radiofrequency ablation, and sharp recanalization. However, large-scale clinical trials evaluating these techniques are lacking, making CVOD management challenging. This article reviews current treatment strategies for catheter-related CVOD. METHODS: A comprehensive literature review was conducted via PubMed, focusing on studies evaluating the effectiveness and safety of various treatment modalities for CVOD. The following keywords were used in PubMed: "hemodialysis", "central vein occlusion", "central vein stenosis", and "catheter". RESULTS: The treatment methods for refractory CVOD in hemodialysis patients are diverse, including sharp recanalization, radiofrequency ablation, and percutaneous superior vena cava puncture. Complications and success rates vary widely across treatments, and evidence is generally limited to small studies or case series. However, a standardized treatment protocol is still lacking. CONCLUSIONS: While several techniques show promise in treating catheter-related CVOD, high-quality clinical studies are necessary to identify the more effective and safe procedure. The choice of treatment should be based on individual patient characteristics, extent of the occlusion, and available resources. Percutaneous SVC puncture may be a feasible alternative after failed sharp recanalization for refractory CVOD.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".