Alteplase vs. urokinase for occluded hemodialysis catheter: A randomized trial
Bibliographic record
Abstract
Introduction Thrombosis of tunneled central venous catheters (CVC) in hemodialysis (HD) patients is common and it can lead to the elimination of vascular sites. To compare the efficacy of alteplase vs. urokinase in reestablishing adequate blood flow through completely occluded vascular catheters. Methods In this randomized study, patients with completely occluded tunneled HD catheters received 40 minutes intracatheter dwell with alteplase (1 mg/mL) or urokinase (5000 IU/mL). Primary endpoint was the proportion of patients with occluded catheters achieving post-thrombolytic blood flow of ≥250 mL/min. Safety endpoints included the incidence of hemorrhagic and infectious complications. Findings Eligible adult patients (n = 100) were treated with alteplase (n = 44) or urokinase (n = 56). The two groups were similar in gender (male: 51.8% vs. 56.8%, P = 0.35), age (60 ± 12 vs. 59 ± 13 years, P = 0.71), time on dialysis (678 ± 203 vs. 548 ± 189 days, P = 0.77), diabetes and cardiovascular disease (55.6% vs. 70.4%, P = 0.08 and 17.8% vs. 22.7%, P = 0.38, respectively), jugular vein as main vascular access (54.8% vs. 62.5%, P = 0.57), and time of CVC (278 ± 63 vs. 218 ± 59 days, P = 0.67). Primary success with alteplase and urokinase occurred in 42/44 (95%) vs. 46/56 (82%), P = 0.06. Success was not achieved after the second dose of alteplase and urokinase in 1 and 7 cases, respectively (2% vs. 12%, P = 0.075). Serious adverse effects were not observed in both groups. There was no difference between the two groups in infectious complications (P = 0.94). Discussion Alteplase and urokinase are effective thrombolytic agents for restoring HD catheter patency. Our study has revealed a likely slight superiority of alteplase over urokinase for unblocking central lines, but which has enrolled too few patients to be able to detect a difference of this size.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".