Kidney function estimators for drug dose adjustment of direct oral anticoagulants in older adults with atrial fibrillation
Bibliographic record
Abstract
ABSTRACT Background The Cockcroft–Gault equation (CrClC-G) is recommended for dose adjustment of direct oral anticoagulant drugs (DOACs) to kidney function. We aimed to assess whether defining DOAC dose appropriateness according to various kidney function estimators changed the associations between dose appropriateness and adverse events in older adults with atrial fibrillation (AF). Methods Participants of the Berlin Initiative Study with AF and treated with DOACs were included. We investigated CrClC-G and estimated glomerular filtration rate (eGFR) using the Chronic Kidney Disease Epidemiology Collaboration and European Kidney Function Consortium equations based on creatinine and/or cystatin C. Marginal structural Cox models yielded confounder-adjusted hazard ratios for the risk of mortality, thromboembolism and bleeding associated with dose status. Results A total of 224 patients were included in the analysis (median age 87 years). Using CrClC-G, 154 (69%) had an appropriate dose of DOACs, 52 (23%) were underdosed and 18 (8%) were overdosed. During a 39-month median follow-up period, 109 (14.9/100 person-years) participants died, 25 (3.6/100 person-years) experienced thromboembolism and 60 (9.8/100 person-years) experienced bleeding. Dose status was not associated with mortality and thromboembolism, independent of the equation. Underdose status was associated with a lower risk of bleeding with all the equations compared with the appropriate dose group. In participants with discrepancies in dose status using CrClC-G and eGFR equations, the occurrence of endpoints did not differ between participants having an appropriate dose using CrClC-G or eGFR. Conclusion In older adults with AF, the association of DOAC dose status with adverse events did not differ when using CrClC-G or eGFR. Our results suggest that eGFR equations are not inferior to CrClC-G within this context.
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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 | 0.012 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".