Universal Clinician Device for improving risk prediction and management of patients with atrial fibrillation: an assumed benefit analysis

Aim Atrial fibrillation (AF) management guidelines advise using risk tools to optimize AF treatment. This study aims to develop a dynamic and clinically applicable digital device to assess stroke and bleeding risk, and to facilitate outcome improvements in AF patients. The device will provide tailored treatment recommendations according to easily attainable individual patient data. Methods and Results This Universal Clinician Device (UCD) was created using the GARFIELD-AF registry using a split sample approach. The GARFIELD-AF risk tool was adapted with two modifications. First, predictors with >= 1000 missing data points were separated, allowing expected risks estimation. Second, recommendations for modifiable risk factors and associated 2-year outcome estimates were incorporated. Outcomes of interest were all-cause mortality, non-haemorrhagic stroke/systemic embolism (SE), and major bleeding. All patients were randomized to a derivation (n=34853) and validation cohort (n=17165). In the derivation cohort, predictors were identified using least absolute shrinkage and selection operator regression. Cox models were fitted with the selected parameters. The UCD demonstrated superior predictive power compared with CHA(2)DS(2)VASc for all-cause mortality [0.75(0.75-0.76) vs. 0.71(0.70-0.72)] and non-haemorrhagic stroke/SE [0.68(0.66-0.70) vs. 0.65(0.63-0.67)], and with HAS-BLED for major bleeding [0.69(0.67-0.71) vs. 0.64(0.62-0.65)]. Universal Clinician Device recommendations reduced all-cause mortality (8.45-5.42%) and non-haemorrhagic stroke/SE (2.58-1.50%). Patients with concomitant diabetes and chronic kidney disease benefitted further, reducing mortality risk from 13.15% to 8.67%. One-third of patients with a CHA(2)DS(2)VASc score of >1 had the lowest risk of stroke. Conclusion The UCD simultaneously predicts mortality, stroke, and bleeding risk in patients using easily attainable individual clinical data and guideline-based optimized treatment plans. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier for GARFIELD-AF: NCT01090362