Efficacy of Tissue Plasminogen Activator for Thrombolysis in Central Venous Dialysis Catheters
Bibliographic record
Abstract
BACKGROUND: Low blood flow is a frequent complication of central-vein (CV) dialysis catheters. Since thrombotic occlusion accounts for many cases of reduced blood flow, it is common practice to administer empiric thrombolytic therapy in an attempt to restore catheter patency and improve function. METHODS: We prepared tissue plasminogen activator (tPA) from 50 mg lyophilized powder, which was diluted (1 mg/mL) in sterile water for injection. A volume of 1 mL was frozen in 3 cc polystyrene syringes at -20 degrees C and thawed at room temperature when needed. tPA was then administered into the arterial and venous ports of the central venous catheter in a volume equal to the manufacturer's stated luminal volume and was allowed to dwell for 30 minutes. RESULTS: tPA was administered 62 times in 25 patients with 30 catheters (11 Tesio, 17 PermCath, 2 Shiley) for treatment of low blood flow (pump speed < 250 mL/min). Complete restoration of patency was achieved in 23 episodes (mean blood flow pre-tPA 130 mL/min; post-tPA 320 mL/min); partial restoration of patency was achieved in 20 episodes (mean blood flow pre-tPA 69 mL/min; post-tPA 233 mL/min). tPA was just as likely to be effective in patients with complete catheter occlusion (i.e., no blood flow) as it was when some initial blood flow was present. Nineteen episodes failed to respond to tPA. These episodes occurred in 13 catheters, 12 of which ultimately underwent radiologic evaluation; an extraluminal cause for low blood flow was found in all 12 catheters (6 malpositioned, 6 fibrin sheaths). CONCLUSIONS: tPA at a dose of 1 mg/mL is effective for restoring patency in CV dialysis catheters. Failure to respond to tPA strongly suggests an extraluminal cause of catheter malfunction.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".