Role of Early Prothrombotic Evaluation in Device-Related Thrombus Risk Stratification After Left Atrial Appendage Closure
Bibliographic record
Abstract
Background: Left atrial appendage closure (LAAC) is increasingly used for stroke prevention in patients with non-valvular atrial fibrillation and contraindications to oral anticoagulation. The potential role of early prothrombotic status assessment in evaluating device-related thrombus (DRT) risk following LAAC remains unclear. Methods: The study included 147 patients undergoing LAAC with oral anticoagulation contraindication. Coagulation activation markers-prothrombin fragment 1 + 2 and thrombin antithrombin III-were measured at baseline and 7 days postprocedure. Based on the 50th percentile of delta (%) changes, patients were classified into low or high prothrombotic status. Specific delta % thresholds were assessed, which could serve as noninvasive cutoffs to rule out DRT. Results: = 0.015). Proposed thresholds for prothrombin fragment 1 + 2 (74.11%) and thrombin antithrombin III (120.74%) demonstrated negative predictive values of 98.9%. Using these thresholds, 75.5% of patients were classified as low risk for DRT. No clinical differences were observed at follow-up between the low- and high-risk DRT groups. Conclusions: Early evaluation of coagulation markers provides valuable insight into DRT risk after LAAC. The proposed thresholds demonstrate a high negative predictive value, effectively identifying patients at low risk for DRT and supporting their use as noninvasive tools to safely rule out DRT. These markers could enable early antithrombotic de-escalation and reduce the need for repeat imaging. Further studies are warranted.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".