Predictors of Atrial Fibrillation in Patients With Stroke Attributed to Large- or Small-Vessel Disease: A Prespecified Secondary Analysis of the STROKE AF Randomized Clinical Trial

Importance

The Stroke of Known Cause and Underlying Atrial Fibrillation (STROKE AF) trial found that approximately 1 in 8 patients with recent ischemic stroke attributed to large- or small-vessel disease had poststroke atrial fibrillation (AF) detected by an insertable cardiac monitor (ICM) at 12 months. Identifying predictors of AF could be useful when considering an ICM in routine poststroke clinical care.

Objective

To determine the association between commonly assessed risk factors and poststroke detection of new AF in the STROKE AF cohort monitored by ICM.

Design, Setting, and Participants

This was a prespecified analysis of a randomized (1:1) clinical trial that enrolled patients between April 1, 2016, and July 12, 2019, with primary follow-up through 2020 and mean (SD) duration of 11.0 (3.0) months. Eligible patients were selected from 33 clinical research sites in the US. Patients had an index stroke attributed to large- or small-vessel disease and were 60 years or older or aged 50 to 59 years with at least 1 additional stroke risk factor. A total of 496 patients were enrolled, and 492 were randomly assigned to study groups (3 did not meet inclusion criteria, and 1 withdrew consent). Patients in the ICM group had the index stroke within 10 days before insertion. Data were analyzed from October 8, 2021, to January 28, 2022.

Interventions

ICM monitoring vs site-specific usual care (short-duration external cardiac monitoring).

Main Outcomes and Measures

The ICM device automatically detects AF episodes 2 or more minutes in length; episodes were adjudicated by an expert committee. Cox regression multivariable modeling included all parameters identified in the univariate analysis having P values <.10. AF detection rates were calculated using Kaplan-Meier survival estimates.

Results

The analysis included the 242 participants randomly assigned to the ICM group in the STROKE AF study. Among 242 patients monitored with ICM, 27 developed AF (mean [SD] age, 66.6 [9.3] years; 144 men [60.0%]; 96 [40.0%] women). Two patients had missing baseline data and exited the study early. Univariate predictors of AF detection included age (per 1-year increments: hazard ratio [HR], 1.05; 95% CI, 1.01-1.09; P = .02), CHA2DS2-VASc score (per point: HR, 1.54; 95% CI, 1.15-2.06; P = .004), chronic obstructive pulmonary disease (HR, 2.49; 95% CI, 0.86-7.20; P = .09), congestive heart failure (CHF; with preserved or reduced ejection fraction: HR, 6.64; 95% CI, 2.29-19.24; P < .001), left atrial enlargement (LAE; HR, 3.63; 95% CI, 1.55-8.47; P = .003), QRS duration (HR, 1.02; 95% CI, 1.00-1.04; P = .04), and kidney dysfunction (HR, 3.58; 95% CI, 1.35-9.46; P = .01). In multivariable modeling (n = 197), only CHF (HR, 5.06; 95% CI, 1.45-17.64; P = .05) and LAE (HR, 3.32; 1.34-8.19; P = .009) remained significant predictors of AF. At 12 months, patients with CHF and/or LAE (40 of 142 patients) had an AF detection rate of 23.4% vs 5.0% for patients with neither (HR, 5.1; 95% CI, 2.0-12.8; P < .001).

Conclusions and Relevance

Among patients with ischemic stroke attributed to large- or small-vessel disease, CHF and LAE were associated with a significantly increased risk of poststroke AF detection. These patients may benefit most from the use of ICMs as part of a secondary stroke prevention strategy. However, the study was not powered for clinical predictors of AF, and therefore, other clinical characteristics may not have reached statistical significance.

Trial Registration

ClinicalTrials.gov Identifier: NCT02700945.

Abstract P844: The Use of Innovative Technology to Reduce Time of Notification Activation to Confirmation Response of Endovascular Team

Background: It is well recognized that time to treatment inversely affects good outcome in acute stroke patients. The sooner patients are evaluated by a trained stroke physician, the more likely they will receive approved acute stroke treatments and interventions. At our Comprehensive Stroke Center, the code stroke team is made up of individuals and providers from multiple disciplines and in the activation of a code stroke, timing is the key element and we sought to improve this notification process through the use of a unifying single, alert system.

Purpose: The goal of this project was to reduce our team activation time. We introduced an application called PerfectServe which allows for the entire stroke team to be alerted and the immediate notification of the neuro-interventional radiology team, when a suitable candidate is identified, without having to rely on a multistep process.

Methods: Implementation of interventional radiology stroke intervention team using PerfectServe application notifications alongside our neurology and neuro-interventional radiology providers and enabling them to see real time updates of stroke patients and communicate plans of care. Retrospective analysis using a T-test analysis technique analyzed the data related to a one step process (PerfectServe application) and a previously utilized multiple step process (Everbridge application) times in minutes.

Results: The one-step PerfectServe application significantly decreased the team notification alert to response confirmation by 10 minutes ( p =0.05).

Conclusions: The one-step PerfectServe application activation process provided more effective communication, team activation times, and better door to treatment times.