Comparison of alteplase (tissue plasminogen activator) high‐dose vs. low‐dose protocol in restoring hemodialysis catheter function: The <scp>ALTE‐DOSE</scp> study
Bibliographic record
Abstract
Hemodialysis catheter (HDC) dysfunction due to thrombosis is common, and dysfunction incidence can reach up to 50% within 1 year of use. Although administration of intraluminal alteplase (tissue plasminogen activator [tPA]) is the standard of practice to pharmacologically restore HDC function, there are no evidence-based guidelines concerning the optimal tPA dose. The purpose of this study was to compare the efficacy of 1.0-mg vs. 2.0-mg tPA dwell protocols in restoring the HDC function in thrombotic dysfunctional catheters. A retrospective, single-center study was conducted on two independent cohorts of patients; the first (n = 129) received 2.0 mg tPA/catheter lumen, while the second (n=108) received 1.0 mg tPA/catheter lumen. Kaplan-Meier and Cox regression analyses were performed to compare the catheter survival time between patients who received 1.0 mg tPA and those who received 2.0 mg tPA. Catheter removal occurred in 25 (19.4%) of those catheters treated with 1.0 mg tPA compared with 11 (10.2%) of catheters treated with 2.0 mg tPA (P = 0.05). The hazard ratio (HR) for catheter removal was 2.75 (95% confidence interval [(95%) CI] = 1.25-6.04) for the 1.0-mg tPA cohort compared with the 2.0-mg tPA cohort. Correction added on 3 December 2012, after first online publication: The tPA cohort values were changed. Female gender (HR = 2.51; (95%) CI = 1.20-5.27) and age (HR = 0.96; (95%) CI = 0.94-0.98) were also associated with catheter survival. Our findings suggest that treatment of dysfunctional HDC with 2.0-mg tPA dwells is superior to 1.0-mg tPA dwells.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".