Fitzmaurice, David

Objectives This study evaluated the comparative effectiveness of vitamin K antagonists (VKAs), direct thrombin inhibitors (DTIs) and factor Xa inhibitors (FXaI) in patients with atrial fibrillation (AF) at risk of stroke in everyday practice. Methods Data from patients with AF and Congestive heart failure, Hypertension, Age 75 years, Diabetes mellitus, prior Stroke, TIA, or thromboembolism, Vascular disease, Age 65-74 years, Sex category (CHA2DS2-VASc) score ≥2 (excluding gender) in the Global Anticoagulant Registry in the FIELD–Atrial Fibrillation registry were analysed using an improved method of propensity weighting, overlap weights and Cox proportional hazards models. Results All-cause mortality, non-haemorrhagic stroke/systemic embolism (SE) and major bleeding over 2 years were compared in 25 551 patients, 7162 (28.0%) not treated with oral anticoagulant (OAC) and 18 389 (72.0%) treated with OAC (FXaI (41.8%), DTI (11.4%) and VKA (46.8%)). OAC treatment compared with no OAC treatment was associated with decreased risk of all-cause mortality (HR 0.82 (95% CI 0.74 to 0.91)) and non-haemorrhagic stroke/SE (HR 0.71 (95% CI 0.57 to 0.88)) but increased risk of major bleeding (HR 1.46 (95% CI 1.15 to 1.86)). Non-vitamin K antagonist oral anticoagulant (NOAC) use compared with no OAC treatment was associated with lower risks of all-cause mortality and non-haemorrhagic stroke/SE (HR 0.67 (95% CI 0.59 to 0.77)) and 0.65 (95% CI 0.50 to 0.86)) respectively, with no increase in major bleeding (HR 1.10 (95% CI 0.82 to 1.47)). NOAC use compared with VKA use was associated with lower risk of all-cause mortality and major bleeding (rates/100 patient-years 3.6 (95% CI 3.3 to 3.9) vs 4.8 (95% CI 4.5 to 5.2) and 1.0 (95% CI 0.9 to 1.1) vs 1.4 (95% CI 1.2 to 1.6); HR 0.79 (95% CI 0.70 to 0.89) and 0.77 (95% CI 0.61 to 0.98) respectively), with similar risk of non-haemorrhagic stroke/SE (rates/100 patient-years 0.8 (95% CI 0.7 to 0.9) versus 1.0 (95% CI 0.8 to 1.1); HR 0.96 (95% CI 0.73 to 1.25). Conclusion Important benefits in terms of mortality and major bleeding were observed with NOAC versus VKA with no difference among NOAC subtypes. Trial registration number NCT01090362.

Abstract Aims Most clinical risk stratification models are based on measurement at a single time-point rather than serial measurements. Artificial intelligence (AI) is able to predict one-dimensional outcomes from multi-dimensional datasets. Using data from Global Anticoagulant Registry in the Field (GARFIELD)-AF registry, a new AI model was developed for predicting clinical outcomes in atrial fibrillation (AF) patients up to 1 year based on sequential measures of prothrombin time international normalized ratio (PT-INR) within 30 days of enrolment. Methods and results Patients with newly diagnosed AF who were treated with vitamin K antagonists (VKAs) and had at least three measurements of PT-INR taken over the first 30 days after prescription were analysed. The AI model was constructed with multilayer neural network including long short-term memory and one-dimensional convolution layers. The neural network was trained using PT-INR measurements within days 0–30 after starting treatment and clinical outcomes over days 31–365 in a derivation cohort (cohorts 1–3; n = 3185). Accuracy of the AI model at predicting major bleed, stroke/systemic embolism (SE), and death was assessed in a validation cohort (cohorts 4–5; n = 1523). The model’s c-statistic for predicting major bleed, stroke/SE, and all-cause death was 0.75, 0.70, and 0.61, respectively. Conclusions Using serial PT-INR values collected within 1 month after starting VKA, the new AI model performed better than time in therapeutic range at predicting clinical outcomes occurring up to 12 months thereafter. Serial PT-INR values contain important information that can be analysed by computer to help predict adverse clinical outcomes.