GARFIELD-AF risk score for mortality, stroke, and bleeding within 2 years in patients with atrial fibrillation
Bibliographic record
Abstract
AIMS: To determine whether the Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) integrated risk tool predicts mortality, non-haemorrhagic stroke/systemic embolism, and major bleeding for up to 2 years after new-onset AF and to assess how this risk tool performs compared with CHA2DS2-VASc and HAS-BLED. METHODS AND RESULTS: Potential predictors of events included demographic and clinical characteristics, choice of treatment, and lifestyle factors. A Cox proportional hazards model was identified for each outcome by least absolute shrinkage and selection operator methods. Indices were evaluated in comparison with CHA2DS2-VASc and HAS-BLED risk predictors. Models were validated internally and externally in ORBIT-AF and Danish nationwide registries. Among the 52 080 patients enrolled in GARFIELD-AF, 52 032 had follow-up data. The GARFIELD-AF risk tool outperformed CHA2DS2-VASc for all-cause mortality in all cohorts. The GARFIELD-AF risk score was superior to CHA2DS2-VASc for non-haemorrhagic stroke, and it outperformed HAS-BLED for major bleeding in internal validation and in the Danish AF cohort. In very low- to low-risk patients [CHA2DS2-VASc 0 or 1 (men) and 1 or 2 (women)], the GARFIELD-AF risk score offered strong discriminatory value for all the endpoints when compared to CHA2DS2-VASc and HAS-BLED. The GARFIELD-AF tool also included the effect of oral anticoagulation (OAC) therapy, thus allowing clinicians to compare the expected outcome of different anticoagulant treatment decisions [i.e. no OAC, non-vitamin K antagonist (VKA) oral anticoagulants, or VKAs]. CONCLUSIONS: The GARFIELD-AF risk tool outperformed CHA2DS2-VASc at predicting death and non-haemorrhagic stroke, and it outperformed HAS-BLED for major bleeding in overall as well as in very low- to low-risk group patients with AF. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier for GARFIELD-AF: NCT01090362, ORBIT-AF I: NCT01165710; ORBIT-AF II: NCT01701817.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".