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Prediction of Residual Stroke Risk in Anticoagulated Patients with Atrial Fibrillation: mCARS.

ABSTRACT: Our ability to evaluate residual stroke risk despite anticoagulation in atrial fibrillation (AF) is currently lacking. The Calculator of Absolute Stroke Risk (CARS) has been proposed to predict 1-year absolute stroke risk in non-anticoagulated patients. We aimed to determine whether a modified CARS (mCARS) may be used to assess the residual stroke risk in anticoagulated AF patients from 'real-world' and 'clinical trial' cohorts. We studied patient-level data of anticoagulated AF patients from the real-world Murcia AF Project and AMADEUS clinical trial. Individual mCARS were estimated for each patient. None of the patients were treated with non-vitamin K antagonist oral anticoagulants. The predicted residual stroke risk was compared to actual stroke risk. 3503 patients were included (2205 [62.9%] clinical trial and 1298 [37.1%] real-world). There was wide variation of CARS for each category of CHA₂DS₂-VASc score in both cohorts. Average predicted residual stroke risk by mCARS (1.8 ± 1.8%) was identical to actual stroke risk (1.8% [95% CI, 1.3-2.4]) in the clinical trial, and broadly similar in the real-world (2.1 ± 1.9% vs. 2.4% [95% CI, 1.6-3.4]). AUCs of mCARS for prediction of stroke events in the clinical trial and real-world were 0.678 (95% CI, 0.598-0.758) and 0.712 [95% CI, 0.618-0.805], respectively. mCARS was able to refine stroke risk estimation for each point of the CHA₂DS₂-VASc score in both cohorts. Personalised residual 1-year absolute stroke risk in anticoagulated AF patients may be estimated using mCARS, thereby allowing an assessment of the absolute risk reduction of treatment and facilitating a patient-centred approach in the management of AF. Such identification of patients with high residual stroke risk could help target more aggressive interventions and follow-up.

SUBMITTER: Ding WY

PROVIDER: S-EPMC8348193 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThere is currently no validated risk prediction model for recurrent events among patients with acute ischemic stroke (AIS) and atrial fibrillation (AF). Considering that the application of conventional risk scores has contextual limitations, new strategies are needed to develop such a model. Here, we set out to develop and validate a comprehensive risk prediction model for stroke recurrence in AIS patients with AF.MethodsAIS patients with AF were collected from multicenter registries in South Korea and Japan. A developmental dataset was constructed with 5648 registered cases from both countries for the period 2011‒2014. An external validation dataset was also created, consisting of Korean AIS subjects with AF registered between 2015 and 2018. Event outcomes were collected during 1 year after the index stroke. A multivariable prediction model was developed using the Fine-Gray subdistribution hazard model with non-stroke mortality as a competing risk. The model incorporated 21 clinical variables and was further validated, calibrated, and revised using the external validation dataset.ResultsThe developmental dataset consisted of 4483 Korean and 1165 Japanese patients (mean age, 74.3 ± 10.2 years; male 53%); 338 patients (6%) had recurrent stroke and 903 (16%) died. The clinical profiles of the external validation set (n = 3668) were comparable to those of the developmental dataset. The c-statistics of the final model was 0.68 (95% confidence interval, 0.66 ‒0.71). The developed prediction model did not show better discriminative ability for predicting stroke recurrence than the conventional risk prediction tools (CHADS2, CHA2DS2-VASc, and ATRIA).ConclusionsNeither conventional risk stratification tools nor our newly developed comprehensive prediction model using available clinical factors seemed to be suitable for identifying patients at high risk of recurrent ischemic stroke among AIS patients with AF in this modern direct oral anticoagulant era. Detailed individual information, including imaging, may be warranted to build a more robust and precise risk prediction model for stroke survivors with AF.

Project description:Atrial fibrillation (AF) is associated with increased mortality, predictors of which are poorly characterized. We investigated the predictive power of the commonly used CHA2DS2-VASc score (congestive heart failure, hypertension, age ≥ 75 years [doubled], diabetes, stroke/transient ischemic attack/thromboembolism [doubled], vascular disease [prior myocardial infarction, peripheral artery disease, or aortic plaque], age 65-75 years, sex category [female]), the HAS-BLED score (hypertension, abnormal renal/liver function, stroke, bleeding history or predisposition, labile international normalized ratio [INR], elderly [age ≥ 65 years], drugs/alcohol concomitantly), and their combination for mortality in AF patients. The PREvention oF thromboembolic events-European Registry in Atrial Fibrillation (PREFER in AF) was a prospective registry including AF patients across seven European countries. We used logistic regression to analyze the relationship between the CHA2DS2-VASc and HAS-BLED scores and outcomes, including mortality, at one year. We evaluated the performance of logistic regression models by discrimination measures (C-index and DeLong test) and calibration measures (Hosmer and Lemeshow goodness-of-fit and integrated discrimination improvement (IDI), with bootstrap techniques for internal validation. In 5209 AF patients with complete information on both scores, average one-year mortality was 3.1%. We found strong gradients between stroke/systemic embolic events (SSE), major bleeding and-specifically-mortality for both CHA2DS2-VASc and HAS-BLED scores, with a similar C-statistic for event prediction. The predictive power of the models with both scores combined, removing overlapping components, was significantly enhanced (p < 0.01) compared to models including either CHA2DS2-VASc or HAS-BLED alone: for mortality, C-statistic: 0.740, compared to 0.707 for CHA2DS2-VASc or 0.646 for HAS-BLED alone. IDI analyses supported the significant improvement for the combined score model compared to separate score models for all outcomes. Both the CHA2DS2-VASc and the HAS-BLED scores predict mortality similarly in patients with AF, and a combination of their components increases prediction significantly. Such combination may be useful for investigational and-possibly-also clinical purposes.

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Prediction of Residual Stroke Risk in Anticoagulated Patients with Atrial Fibrillation: mCARS.

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