Optimising prediction of mortality, stroke, and major bleeding for patients with atrial fibrillation: validation of the GARFIELD-AF tool in UK primary care electronic records

优化房颤患者死亡率、卒中和重大出血的预测:在英国初级保健电子病历中验证 GARFIELD-AF 工具

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Abstract

BACKGROUND: The GARFIELD-AF tool is a novel risk tool that simultaneously assesses the risk of all-cause mortality, stroke or systemic embolism, and major bleeding in patients with atrial fibrillation (AF). AIM: To validate the GARFIELD-AF tool using UK primary care electronic records. DESIGN AND SETTING: A retrospective cohort study using the Clinical Practice Research Datalink (CPRD) linked with Hospital Episode Statistics data and Office for National Statistics mortality data. METHOD: Discrimination was evaluated using the area under the curve (AUC) and calibration was evaluated using calibration-in-the-large regression and calibration plots. RESULTS: A total of 486 818 patients aged ≥18 years with incident diagnosis of non-valvular AF between 2 January 1998 and 31 July 2020 were included; 50.6% (n = 246 425/486 818) received anticoagulation at diagnosis The GARFIELD- AF models outperformed the CHA(2)DS(2)VASc and HAS-BLED scores in discrimination ability of death, stroke, and major bleeding at all the time points. The AUC for events at 1 year for the 2017 models were: death 0.747 (95% confidence interval [CI] = 0.744 to 0.751) versus 0.635 (95% CI = 0.631 to 0.639) for CHA(2)DS(2)VASc; stroke 0.666 (95% CI = 0.663 to 0.669) versus 0.625 (95% CI = 0.622 to 0.628) for CHA(2)DS(2)VASc; and major bleeding 0.602 (95% CI = 0.598 to 0.606) versus 0.558 (95% CI = 0.554 to 0.562) for HAS- BLED. Calibration between predicted and Kaplan- Meier observed events was inadequate with the GARFIELD-AF models. CONCLUSION: The GARFIELD-AF models were superior to the CHA(2)DS(2)VASc score for discriminating stroke and death and superior to the HAS-BLED score for discriminating major bleeding. The models consistently underpredicted the level of risk, suggesting that a recalibration is needed to optimise its use in the UK population.

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