Systemic Anticoagulation and Prevention of Hemodialysis Catheter Malfunction
Bibliographic record
Abstract
Although chronic anticoagulation is commonly prescribed to prevent thrombosis and malfunction of hemodialysis tunneled cuffed catheters (TCC), there are only limited data regarding its efficacy. The aim of this prospective study was to evaluate whether anticoagulation with adjusted-dose warfarin targeting an international normalized ratio (INR) of 1.5-2.0 is associated with improved catheter outcome in long-term patients at high risk of TCC malfunction. Among the 65 patients included in the study, 35 were considered at high risk (i.e., patients with a history of previous TCC thrombosis requiring catheter replacement and/or with TCC malfunction occurring within 2 weeks after catheter insertion in the absence of mechanical problems) and were prescribed warfarin, whereas 30 low-risk patients did not receive anticoagulation. During follow-up, TCC malfunction, defined as the need for inversion of catheter lines and/or recombinant tissue-type plasminogen activator infusion, was observed in 61.5% of patients. Among patients receiving warfarin, 19 (54.3%) achieved adequate anticoagulation (i.e., > 80% of follow-up INR values and INR value at the time of malfunction within target range). Anticoagulation was considered inadequate in 16 patients (45.7%). Malfunction-free catheter survival at 9 months was 47.1% in patients with adequate anticoagulation compared with 8.1% in patients with inadequate anticoagulation (p = 0.01). This difference remained statistically significant after adjustment for aspirin intake. These results suggest that achieving adequate anticoagulation with target INR 1.5-2.0 may prevent TCC malfunction and improve catheter outcome.
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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 | 0.002 |
| 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) | 0.000 | 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".