Efficacy and Safety Considerations With Dose-Reduced Direct Oral Anticoagulants
Bibliographic record
Abstract
Importance: Dose-reduced regimens of direct oral anticoagulants (DOACs) may be used for 2 main purposes: dose-adjusted treatment intended as full-intensity anticoagulation (eg, for stroke prevention in atrial fibrillation [AF] in patients requiring dose reduction) or low-intensity treatment (eg, extended-duration treatment of venous thromboembolism [VTE]). We reviewed randomized clinical trials (RCTs) to understand the scenarios in which dose-adjusted or low-intensity DOACs were tested and reviewed the labeled indications by regulatory authorities, using data from large registries to assess whether the use of dose-reduced DOACs in routine practice aligned with the findings of RCTs. Observations: Among 4191 screened publications, 35 RCTs that used dose-adjusted DOACs were identified for dabigatran, apixaban, rivaroxaban, and edoxaban. Of these 35 RCTs, 29 were related to stroke prevention in AF. Efficacy and safety results for dose-adjusted DOACs in large RCTs of AF were similar to those found for full-dose DOACs. To our knowledge, dabigatran, apixaban, and rivaroxaban have not been studied as dose-adjusted therapy for acute VTE treatment. Low-intensity DOACs were identified in 37 RCTs. Low-intensity DOACs may be used for extended-duration treatment of VTE (apixaban and rivaroxaban), primary prevention in orthopedic surgeries (dabigatran, apixaban, and rivaroxaban), primary prevention in ambulatory high-risk cancer patients (apixaban and rivaroxaban) or (postdischarge) high-risk medical patients (rivaroxaban), in stable atherosclerotic vascular disease, or after a recent revascularization for peripheral artery disease in conjunction with aspirin (rivaroxaban). Minor variations exist between regulatory authorities in different regions regarding criteria for dose adjustment of DOACs. Data from large registries indicated that dose-reduced DOACs were used occasionally with doses or for clinical scenarios different from those studied in RCTs or recommended by regulatory authorities. Conclusions and Relevance: Dose adjustment and low-intensity treatment are 2 different forms of dose-reduced DOACs. Dose adjustment is mostly relevant for AF and should be done based on the approved criteria. Dose adjustment of DOACs should not be used for acute VTE treatment in most cases. In contrast, low-intensity DOACs may be used for primary or secondary VTE prevention for studied and approved indications. Attention should be given to routine practice patterns to align the daily clinical practice with existing evidence of safety and efficacy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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 teacher head, 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".