Variability in Nonvitamin K Oral Anticoagulant Dose Eligibility and Adjustment According to Renal Formulae and Clinical Outcomes in Patients With Atrial Fibrillation With and Without Chronic Kidney Disease: Insights From ORBIT‐AF II
Bibliographic record
Abstract
Background Nonvitamin K oral anticoagulants require dose adjustment based on kidney function.The most common estimate of kidney function employed in clinical practice is estimated glomerular filtration rate (eGFR); however, product monographs recommend the use of the Cockcroft‐Gault estimated creatinine clearance (eCrCl) for dose adjustment. Methods and Results The authors included patients enrolled in the ORBIT‐AF II (Outcomes Registry for Better Informed Treatment of Atrial Fibrillation AF II) trial. Dosing was considered inappropriate when use of eGFR resulted in a lower (undertreatment) or higher (overtreatment) dose than that recommended by the eCrCl. The primary outcome of major adverse cardiovascular and neurological events was a composite of cardiovascular death, stroke or systemic embolism, new‐onset heart failure, and myocardial infarction. Among 8727 in the overall cohort, agreement between eCrCl and eGFR was observed in 93.5% to 93.8% of patients. Among 2184 patients with chronic kidney disease (CKD), the agreement between eCrCl and eGFR was 79.9% to 80.7%. Dosing misclassification was more frequent in the CKD population (41.9% of rivaroxaban users, 5.7% of dabigatran users, and 4.6% apixaban users). At 1 year, undertreated patients in the CKD group had significantly greater major adverse cardiovascular and neurological events (adjusted hazard ratio, 2.93 [95% CI, 1.08–7.92]) compared with the group with appropriate nonvitamin K oral anticoagulants dosing ( P =0.03). Conclusions The prevalence of misclassification of nonvitamin K oral anticoagulants dosing was high when using eGFR, particularly among patients with CKD. Among patients with CKD, potential undertreatment due to inappropriate and off‐label renal formulae may result in worse clinical outcomes. These findings highlight the importance of using eCrCl, and not eGFR, for dose adjustment in all patients with AF receiving nonvitamin K oral anticoagulants.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".