Potential missed opportunities to prevent ischaemic stroke: prospective multicentre cohort study of atrial fibrillation-associated ischaemic stroke and TIA

Ischemic stroke in oral anticoagulated patients with atrial fibrillation

BACKGROUND

Ischemic strokes in orally anticoagulated patients pose challenges for acute management and secondary prevention but the characteristics of these strokes are poorly understood. We examined the clinical and imaging features, the presumed underlying etiology and the subsequent antithrombotic management.

METHODS

We analyzed a consecutive series of patients enrolled into the EIDASAF study, a single center, observational study of ischemic stroke patients with a diagnosis atrial fibrillation (AF) prior to the index event who had been admitted to the Hyperacute Stroke Unit of Imperial College London between 2010 and 2017. We compared patients with oral anticoagulation therapy prior admission (OAC_prior ) with those without anticoagulation (OAC_naive ). Brain imaging was analyzed centrally.

RESULTS

763 patients were included in the analysis. 481 (63%) were OAC_naive while 282 (37%) were OAC_prior . Patients with OAC_prior were younger, more often had a previous history of stroke or transient ischemic attack (TIA), and more often suffered from hypertension and diabetes. In OAC_naive, patients, large and deep middle cerebral artery infarcts occurred more often than in OAC_prior patients. The groups differed significantly in the distribution of competing etiologies underlying their stroke. At discharge, OAC_prior more frequently were (re)-anticoagulated compared to OAC_naive patients. Within the OAC_prior group, patients with recurrent strokes did not differ from those with a first stroke regarding clinical characteristics and pattern of cerebral infarction but they were less frequently anticoagulated.

CONCLUSIONS

Ischemic strokes on OAC represent a significant proportion of AF-related strokes. There is an unmet need to better understand the causes underlying these strokes and to optimize the medical management.

Utility of risk prediction models to detect atrial fibrillation in screened participants

AIMS

Atrial fibrillation (AF) is associated with higher risk of stroke. While the prevalence of AF is low in the general population, risk prediction models might identify individuals for selective screening of AF. We aimed to systematically identify and compare the utility of established models to predict prevalent AF.

METHODS AND RESULTS

Systematic search of PubMed and EMBASE for risk prediction models for AF. We adapted established risk prediction models and assessed their predictive performance using data from 2.5M individuals who attended vascular screening clinics in the USA and the UK and in the subset of 1.2M individuals with CHA2DS2-VASc ≥2. We assessed discrimination using area under the receiver operating characteristic (AUROC) curves and agreement between observed and predicted cases using calibration plots. After screening 6959 studies, 14 risk prediction models were identified. In our cohort, 10 464 (0.41%) participants had AF. For discrimination, six prediction model had AUROC curves of 0.70 or above in all individuals and those with CHA2DS2-VASc ≥2. In these models, calibration plots showed very good concordance between predicted and observed risks of AF. The two models with the highest observed prevalence in the highest decile of predicted risk, CHARGE-AF and MHS, showed an observed prevalence of AF of 1.6% with a number needed to screen of 63. Selective screening of the 10% highest risk identified 39% of cases with AF.

CONCLUSION

Prediction models can reliably identify individuals at high risk of AF. The best performing models showed an almost fourfold higher prevalence of AF by selective screening of individuals in the highest decile of risk compared with systematic screening of all cases.

REGISTRATION

This systematic review was registered (PROSPERO CRD42019123847).