Comparison of intermittent and continuous extracorporeal treatments for the enhanced elimination of dabigatran
Bibliographic record
Abstract
CONTEXT: Severe bleeding associated with dabigatran frequently requires intensive care management. An antidote is currently unavailable and data reporting the effect of dialysis on elimination of dabigatran are encouraging, but limited. Objective. To report the effect of intermittent hemodialysis (IHD) and continuous renal replacement therapy (CRRT) at enhancing elimination of dabigatran. MATERIALS AND METHODS: Patients were identified by existing collaborative networks. Pre-filter dabigatran plasma concentrations were measured in all patients, and in dialysate of three patients. RESULTS: Seven patients received dialysis, five with active bleeding and two requiring emergent surgery. Five received IHD and two received CRRT. The plasma elimination half-life of dabigatran was 1.5-4.9 h during IHD, and 14.0-27.5 h during CRRT. Mean dabigatran plasma clearance during IHD was 85-169 mL/min in three patients. Time to obtain a subtherapeutic dabigatran concentration depended on the initial concentration, being 8-18 h for IHD in three patients while 4 h was insufficient in a supratherapeutic case. A 38% rebound in dabigatran levels occurred after one case during IHD, and thrombin time increased after IHD in another, but not after 144 h CRRT or 17 h IHD in two others; data were incomplete in three cases. The amount removed during IHD was proportional to the pre-IHD concentration and clearance, but was consistently low at 3.3-17.4 mg in three patients where this was determined. Moderate bleeding occurred while obtaining vascular access in one patient. Two patients died from intracerebral bleeding, and the influence of treatments could not be determined in these cases. DISCUSSION AND CONCLUSIONS: IHD enhanced elimination of dabigatran more efficiently than CRRT, but their net effect remains poorly defined. Dialysis decisions, including modality and duration, must be individualized based on a risk-benefit assessment.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".