Validation of the DOAC Score among patients on vitamin K antagonists
Bibliographic record
Abstract
Abstract Background The DOAC Score stratifies bleeding risk in patients with atrial fibrillation (AF) taking direct oral anticoagulants (DOACs). The discriminative ability of the DOAC Score among patients with AF taking vitamin K antagonists (VKAs) is unknown. Purpose This study evaluates the discrimination of the DOAC Score among patients with AF taking VKAs. Methods Two data sources were used for validation: COMBINE-AF and GARFIELD-AF. COMBINE-AF included patients with AF randomized to warfarin in the clinical trials of RE-LY, ARISTOTLE, ROCKET-AF, and ENGAGE AF-TIMI 48. GARFIELD-AF is a real-world registry, and patients who were prescribed with VKAs at enrollment were included. The DOAC Score consists of a 0 to 10 scoring system, was externally validated among patients with AF taking DOACs, and includes commonly obtained clinical variables (age, weight, estimated glomerular filtration rate, antiplatelet or nonsteroidal anti-inflammatory use, hypertension, diabetes, history of bleeding, liver disease, or stroke/transient ischemic attack/embolism). Patients were stratified into five clinical risk categories by the DOAC Score (very low [score 0-3], low [score 4-5], moderate [score 6-7], high [score 8-9], very high [score 10]), with one-year major bleeding rates determined for each risk group. Discrimination of the DOAC Score was estimated using Harrell’s C-statistics and compared to the HAS-BLED score with DeLong’s test. Results A total of 28,818 patients and 20,183 patients from COMBINE-AF and GARFIELD-AF were included and treated with VKAs. Major bleeding by one-year occurred in 994 (3.4%) patients in COMBINE-AF and 313 patients (1.6%) in GARFIELD-AF. Higher rates of major bleeding occurred in higher risk categories for patients in COMBINE-AF: very low (1.8 events per 100 person-years [events/100 p-y]), low (3.0 events/100 p-y), moderate (4.5 events/100 p-y), high (5.4 events/100 p-y), and very high (7.5 events/100 p-y) (Figure). A similar pattern was observed among patients in GARFIELD-AF: very low (0.8 events per 100 person-years events/100 p-y), low (1.5 events/100 p-y), moderate (2.2 events/100 p-y), high (3.2 events/100 p-y), and very high (7.6 events/100 p-y). Discrimination of the DOAC Score was moderate and higher than the HAS-BLED score in both COMBINE-AF (C-statistic: 0.62 vs 0.59, P<0.001) and GARFIELD-AF (C-statistic: 0.65 vs 0.62, P<0.001) (Table). Conclusions Among patients with AF taking VKAs, the DOAC Score was able to risk stratify patients for major bleeding risk, demonstrated moderate discrimination, and had improved discrimination compared to HAS-BLED in a large clinical trial cohort and a real-world registry. The DOAC Score could be considered an alternative to HAS-BLED for bleeding risk stratification.
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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 | 0.011 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".