Prevalence of clinically significant bradyarrhythmias in patients implanted with loop recorders for cryptogenic stroke: A manifestation of atrial cardiomyopathy?

Advances in Neurocardiology: Focus on Atrial Fibrillation.

Atrial fibrillation (AF), commonly encountered in patients with ischemic stroke and transient ischemic attack (TIA), confers a 5-fold increased risk of ischemic stroke.1,2 AF-related strokes are associated with an ≈50% increased risk of disability and 60% increased risk of death at 3 months compared with strokes of other etiologies.3 Paroxysmal AF (PAF), a self-terminating recurrent form of cardiac arrhythmia that comprises between 25% and 62% of AF cases, may present as a brief single episode of arrhythmia or as clusters of abnormal rhythm of variable duration, sometimes evolving into a more persistent or permanent form.4 The self-terminating nature of PAF may lead to its underdiagnosis and consequent use of less effective treatment strategies (aspirin instead of oral anticoagulation) in poststroke patients. To address the underdiagnosis of PAF in patients with ischemic stroke and TIAs, several treatment guidelines have singled out the identification of PAF as an important goal after a stroke/TIA.5–8 The diagnosis of PAF, however, poses a challenge. Several features of AF (such as its brief duration, episodic frequency, and asymptomatic presentations) make its detection difficult and elusive to bedside screening measures, such as pulse monitoring and routine ECGs. To date, several studies have explored the use of prolonged noninvasive and invasive cardiac monitoring devices to identify AF but with variable success. After detection of AF, a cardioembolic mechanism is often inferred and anticoagulation occasionally prescribed for secondary stroke prevention. The routine use of cardiac monitoring to identify patients with PAF who will benefit from anticoagulation has been reported to be cost-effective.9 In this review, we provide an overview of the different methods of cardiac monitoring, summarize studies that investigated the incidence of PAF after stroke, and highlight gaps in our understanding of the pathogenic and prognostic significance of AF …

Introduction: This interim analysis evaluates the risk profile and incidence of atrial fibrillation (AF) in patients who underwent continuous monitoring with an implantable loop recorder (ILR) for cryptogenic (unexplained) stroke or transient ischemic attack (TIA). Methods: The observational INSIGHT XT study prospectively enrolled patients who received an ILR with dedicated diagnostics for atrial fibrillation, irrespective of the clinical indication. Of 1002 patients enrolled in the study between Aug 2008 and Jan 2012, 121 received the ILR to evaluate cryptogenic stroke or TIA. The definition of cryptogenic stroke/TIA was at the investigators' appraisal and no unified approach to patient work-up was required. This analysis includes 74 patients with cryptogenic stroke or TIA for whom at least one follow-up visit was available at the time of interim analysis. Results: The mean age was 63±12 (50% female). Stroke was the index event in 46 of 74 (62%) of patients. 61% had hypertension, 14% diabetes, and none had heart failure. The mean CHADS2 score was 3.0±0.8 and the mean CHA2DS2VASc score 4.0±1.2. Most patients (72%) had no prior symptoms or cardiac rhythm disturbances, whereas 18% had a history of prior palpitations. Sixty-seven patients were taking antiplatelet medication and four were on oral anticoagulation (OAC) at enrollment. During a median follow up of 12 months (IQR 7 to 18) AF was reported in 17 patients (23%) and two patients were started on OAC and 10 patients were converted from antiplatelets to OAC. Five patients experienced a stroke or TIA (median time to event 1.2 months), of which one patient died. Three of the patients with stroke or TIA had AF detected prior to the recurrent event. Conclusion: Continuous monitoring with an ILR in patients with cryptogenic stroke of TIA detects a high proportion of AF; this can be attributed to longer continuous monitoring in this study. These patients have high CHADS2/CHA2DS2VASc scores; documenting AF in these cases may therefore be clinically relevant in order to decide appropriate treatment.

Recently, the CRYSTAL AF trial detected paroxysmal atrial fibrillation (AF) in 12.4% of patients after cryptogenic ischaemic stroke (IS) or cryptogenic transient ischaemic attack (TIA) by an insertable cardiac monitor (ICM) within 1 year of monitoring. Our aim was (i) to assess if an AF risk factor based pre-selection of ICM candidates would enhance the rate of AF detection and (ii) to determine AF risk factors with significant predictive value for AF detection. Seventy-five patients with cryptogenic IS/TIA were consecutively enrolled if at least one of the following AF risk factors was present: a CHA2DS2-VASc score ≥4, atrial runs, left atrium (LA) size >45 mm, left atrial appendage (LAA) flow ≤0.2 m/s, or spontaneous echo contrast in the LAA. The electrocardiographic and echocardiographic criteria were chosen as they have been repeatedly reported to predict AF; the same applies for four of the six items of the CHA2DS2-VASc score. The study end-point was the detection of one or more episodes of AF (≥2 min). Seventy-four patients underwent implantation of an ICM; one patient had AF at the date of implantation. After 6 months, AF was detected in 21/75 patients (28%), after 12 months in 25/75 patients (33.3%). 92% of AF episodes were asymptomatic. LA size >45 mm and the presence of atrial runs were independently associated with AF detection [hazard ratio 3.6 (95% confidence interval 1.6-8.4), P = 0.002, and 2.7 (1.2-6.7), P = 0.023, respectively]. The detection rate of AF is one-third after 1 year if candidates for an ICM after cryptogenic IS/TIA are selected by AF risk factors. LA dilation and atrial runs independently predict AF.

Introduction: Atrial Fibrillation (AF) is detected in nearly 30% of patients undergoing cardiac monitoring after ischemic stroke. Studies investigating predictors of AF showed mixed results. In this study, we aim to identify predictors of AF on insertable cardiac monitors (ICMs) and compare rates between cryptogenic stroke patients and controls. Methods: The ANT icoagulation A nd St R oke Re C urrence in A T rial F I brillation Dete C ted A fter Stroke (ANTARCTICA) study is an individual patient data meta-analysis of prospective observational studies of cryptogenic ischemic stroke and control patients (non-cryptogenic ischemic stroke and non-ischemic stroke) who underwent an ICM implantation. The search included prospective observational studies and randomized controlled trials of patients with non-cardioembolic ischemic stroke or transient ischemic attack or non-ischemic stroke controls who underwent prolonged cardiac monitoring with an ICM after the index event. We performed multiple imputations to derive missing covariates such as left atrial volume index. We used multivariable multi-level logistic regression models to identify clinical, imaging, and echocardiographic factors associated with AF detection. We compared AF rates and charecterisctis between cryptogenic stroke and controls. Results: We identified 14 studies (2 RCTs and 12 observational) that included 2036 patients (1562 cryptogenic stroke and 474 non-cryptogenic stroke and non stroke controls); AF was detected in 30.7% of cryptogenic stroke patients and 29.1% of non-cryptogenic stroke patients. In multivariable logistic regression analyses, factors associated with AF were age (OR per year increase 1.05 95% CI 1.04-1.06), left atrial volume index (OR per unit increase 1.03 95% CI 1.02-1.05), and cryptogenic stroke (adjusted OR 1.89, 95% CI 1.20-2.98, p = 0.006). When compared to controls, the time to AF detection was significantly shorter in cryptogenic stroke (median 65 days vs. 169 days, p < 0.001) and AF duration was non-significantly longer (median 90 minutes vs. 120 minutes, p = 0.144). Results remained unchanged when the control group was limited to patients with non-cryptogenic ischemic stroke. Conclusions: In this large, individual patient data meta-analysis of patients undergoing ICM, there is increased detection and burden of AF after cryptogenic stroke compared to controls, suggesting a likely pathogenicity of device-detected AF in cryptogenic stroke.

Introduction: Cardioembolic etiology is assumed to be the most frequent cause of cryptogenic strokes. The detection of subclinical paroxysmal atrial fibrillation (AF) is important in the correct choice of preventive treatment. The aim of this prospective study was to detect the incidence of AF in patients with a cryptogenic stroke or transient ischemic attack (TIA) and to evaluate the association between the presence of AF and selected single-nucleotide polymorphisms (SNP). Methods: Patients with a cryptogenic stroke/ TIA (n=100) and a control group (n=15) of volunteers without significant cardiovascular disease were included in the study during the period of 2014 to 2019. To detect AF they underwent 12 months of ECG monitoring using an implanted loop recorder (ILR). Genotyping for SNPs rs10033464, rs2200733, rs225132, and rs2106261 was performed by a high resolution melting analysis. Results: We found AF to be present in 24 (24%) patients with a cryptogenic stroke/TIA, versus no subjects in the control group. The SNPs rs2106261, rs2200733, rs225132, and rs10033464 were not found to be associated with AF in our study (p=0.240; 1.000; 0.887; 0.589). However, a weak trend for a higher frequency of rs2106261 risk allele A homozygotes was observed in the patients with AF compared to the patients without AF (0.416 vs. 0.263, p=0.073). Homozygotes for allele A of rs2106261 were also present in a significantly higher frequency in AF patients compared to the controls (0.416 vs. 0.133, p = 0.012). Conclusion: In our study paroxysmal AF was a probable etiological factor in 24% of patients with cryptogenic ischemic stroke / TIA during the 12 months of monitoring. The homozygous allele A of rs2106261 was identified to be the possible genetic risk factor of AF, but this should be verified in larger cohorts. The study has been registered at www.clinicaltrials.gov, identifier NCT02216370.

Meta-Analysis of Randomized Clinical Trials Comparing the Impact of Implantable Loop Recorder Versus Usual Care After Ischemic Stroke for Detection of Atrial Fibrillation and Stroke Risk

BackgroundParoxysmal atrial fibrillation (AF) is a probable cause of cryptogenic stroke (CS), and its detection and treatment are important for the secondary prevention of stroke. Insertable cardiac monitors (ICMs) are clinically effective in screening for AF and are superior to conventional short-term cardiac monitoring. Japanese guidelines for determining clinical indications for ICMs in CS are stricter than those in Western countries. Differences between Japanese and Western guidelines may impact the detection rate and prediction of AF via ICMs in patients with CS. Available data on Japanese patients are limited to small retrospective studies. Furthermore, additional information about AF detection, including the number of episodes, cumulative episode duration, anticoagulation initiation (type and dose of regimen and time of initiation), rate of catheter ablation, role of atrial cardiomyopathy, and stroke recurrence (time of recurrence and cause of the recurrent event), was not provided in the vast majority of previously published studies.ObjectiveIn this study, we aim to identify the proportion and timing of AF detection and risk stratification criteria in patients with CS in real-world settings in Japan.MethodsThis is a multicenter, prospective, observational study that aims to use ICMs to evaluate the proportion, timing, and characteristics of AF detection in patients diagnosed with CS. We will investigate the first detection of AF within the initial 6, 12, and 24 months of follow-up after ICM implantation. Patient characteristics, laboratory data, atrial cardiomyopathy markers, serial magnetic resonance imaging findings at baseline, 6, 12, and 24 months after ICM implantation, electrocardiogram readings, transesophageal echocardiography findings, cognitive status, stroke recurrence, and functional outcomes will be compared between patients with AF and patients without AF. Furthermore, we will obtain additional information regarding the number of AF episodes, duration of cumulative AF episodes, and time of anticoagulation initiation.ResultsStudy recruitment began in February 2020, and thus far, 213 patients have provided written informed consent and are currently in the follow-up phase. The last recruited participant (May 2021) will have completed the 24-month follow-up in May 2023. The main results are expected to be submitted for publication in 2023.ConclusionsThe findings of this study will help identify AF markers and generate a risk scoring system with a novel and superior screening algorithm for occult AF detection while identifying candidates for ICM implantation and aiding the development of diagnostic criteria for CS in Japan.Trial RegistrationUMIN Clinical Trial Registry UMIN000039809; https://tinyurl.com/3jaewe6aInternational Registered Report Identifier (IRRID)DERR1-10.2196/39307

Introduction: In 20-30% cases, the cause of stroke remained unexplained which has led to coining of the term, Cryptogenic Stroke (CS). Similarly, about 48% cases of transient ischemic attacks (TIAs) had no identifiable cause after standard diagnostic workup. Undiagnosed Atrial Fibrillation (AF) is a prime suspect in CS but guidelines do not recommend initiation of anticoagulation unless AF has formally been detected. Methods: In a IRB approved retrospective study we included patients with at least one episode of ischemic stroke or TIA without identifiable cause and was monitored with either 48-hour Holter Monitor (HM), 30-day Event Monitor (EM) or Implantable loop recorder (ILR) to diagnose any undiscovered AF. All patients had at least 1 year, and up to 3 years, of follow-up after device placement. SAS Version 9.4 was used for statistical analyses. Results: Out of a total of 531 patients, 150 patients were monitored by ILR, 286 by EM and 95 by HM. Primary Outcome- detection of AF. The diagnosis of AF within 1 month of the stroke was 5.59% (16/286), 6.32% (6/95) and 9.33% (14/150) in the EM, HM and ILR cohorts, respectively (p=0.33). At 6, 12 and 24 months, ILRs detected AF in 15.33% (23/150), 16% (24/150) and 20% (30/150) of patients respectively (p=.0017, .0008 and .0001, respectively). Hence the Chi-Squared analysis showed no statistically significant difference among 3 devices for the detection of AF within 1 month of the index stroke but a significant difference in AF detection was observed at 6, 12 and 24 months. Similarly, the multivariable logistic regression model demonstrated no significant difference in capturing AF between HM, EM and ILR within 1 month (p=0.29) but showed a significant difference in AF detection when ILR was compared to HM and EM at 6,12 and 24 months (p=0.0027, 0.0012 and <0.0001 respectively). Secondary Outcome- Kaplan Meier estimator analysis and Cox proportional Hazard model showed device type had no significant impact on secondary outcomes of the study: 1) Subsequent ischemic stroke or TIA 2) Initiation of anticoagulation 3) Mortality 4) Incidence of major bleeding. Conclusion: In conclusion, despite the superiority of AF detection by ILR, it is not superior to HM or EM in lowering the risk of subsequent stroke or TIA, or in reducing mortality.

Paroxysmal atrial fibrillation is often suspected as a probable cause of cryptogenic stroke. Continuous long-term ECG monitoring using insertable cardiac monitors is a clinically effective technique to screen for atrial fibrillation and superior to conventional follow-up in cryptogenic stroke. However, more studies are needed to identify factors which can help selecting patients with the highest possibility of detecting atrial fibrillation with prolonged rhythm monitoring. The clinical relevance of short-term atrial fibrillation, the need for medical intervention and the evaluation as to whether intervention results in improved clinical outcomes should be assessed. The Nordic Atrial Fibrillation and Stroke Study is an international, multicentre, prospective, observational trial evaluating the occurrence of occult atrial fibrillation in cryptogenic stroke and transient ischaemic attack. Patients with cryptogenic stroke or transient ischaemic attack from the Nordic countries are included and will have the Reveal LINQ® Insertable cardiac monitor system implanted for 12 months for atrial fibrillation detection. Biomarkers which can be used as predictors for atrial fibrillation and may identify patients, who could derive the most clinical benefit from the detection of atrial fibrillation by prolonged monitoring, are being studied. The primary endpoint is atrial fibrillation burden within 12 months of continuous rhythm monitoring. Secondary endpoints are atrial fibrillation burden within six months, levels of biomarkers predicting atrial fibrillation, CHA2DS2-VASc score, incidence of recurrent stroke or transient ischaemic attack, use of anticoagulation and antiarrhythmic drugs, and quality of life measurements. The clinical follow-up period is 12 months. The study started in 2017 and the completion is expected at the end of 2020.

Background: The use of insertable cardiac monitors (ICM) has increased the rate of detection of atrial fibrillation (AF) among cryptogenic stroke (CS) patients. We describe a single-center experience for AF detection among CS patients receiving ICMs upon discharge after the index stroke event and attempt to identify predictors for early AF detection. Methods: From April 2014 to April 2016, patients receiving ICMs upon discharge for CS who underwent >90 days of monitoring were reviewed. Time from ICM placement to AF detection, chronic underlying medical illnesses, presence of left atrial dilatation (LAD) on echocardiography, and PR interval on admission EKG were assessed as predictors of early AF detection. Results: A total of 114 patients met inclusion criteria and were followed for a median of 415 [268, 557] days. Among these 32 patients (28.1%) were found to have AF at a median of 53 [5, 132] days from ICM placement. Patients with AF detected <30 days from ICM placement had lower rates of hyperlipidemia (35.7% vs 88.9%, p=0.003) and higher rates of hypertension (100% vs 66.7%, p=0.02), tobaccoism (85.7% vs 33.3%, p=0.005), LAD (64.3% vs 16.7%, p=0.01), and prolonged PR interval (195.3±43.2 ms vs 170.3±23.4 ms, p=0.04) compared to patients with AF detected >30 days from ICM placement. Conclusion: More than one-quarter of CS patients monitored for >90 days with an ICM were found to have previously undiagnosed AF. The majority of patients with AF detected were identified >30 days after their index CS event. Among patients in whom AF was ultimately detected by the ICM, AF may be identified earlier among patients with hypertension and tobaccoism in combination with LAD and prolonged PR interval. Prospective studies are needed to better identify predictors for early AF among the broader population of all CS patients.

In patients with cryptogenic stroke (CS) or transient ischemic attack (TIA), prolonged cardiac monitoring is recommended to improve detection of atrial fibrillation (AF). Prediction scores have been proposed to identify patients with a high likelihood of post-stroke AF detection and some of them have been used to guide the selection of patients for implantable loop recorders (ILR), but few studies have externally assessed their performances. Aim of this prospective cohort study was to assess the performance of nine AF prediction scores in a cohort of CS and TIA monitored with ILR. Patients were included after a diagnosis of CS or TIA and ILR implantation between July 2018 and December 2023. Nine AF prediction scores were evaluated: STAF, LADS, HAVOC, Brown-ESUS AF, AS5 F, C2HEST, CHASE-LESS, AF-ESUS, and Empoli ESUS-AF. For each score we calculated sensitivity, specificity, negative (NPV) and positive predictive value (PPV), overall accuracy, and area under the receiver operating characteristic curve (AUROC). AUROCs were compared with DeLong's test. Of 1032 admitted patients, 270 (26.2%) were defined cryptogenic, 194 of whom (71.9%) received an ILR (43.3% women; median age 74.0 years [IQR 65.8-82.0]; median NIHSS score on admission 3.0 [1.0-6.0]; 182 (93.8%) ischemic stroke and 12 (6.2%) TIA). Median time from index event to ILR implant was 10 days (7-37). During long-term monitoring (median follow-up 23.0 months [12.0-37.3]), AF was detected in 62 patients (32%), with a median time from index stroke to AF diagnosis of 4.0 months (1.0-11.3). Sensitivity of the scores ranged between 12.9% and 95.2%, specificity 12.9-67.7%, PPV 37.3-48.1%, NPV 68.6-90.6%, and overall accuracy 45.4-66.3%. The Brown ESUS-AF score reached the highest AUROC (0.697 in the whole cohort, 0.707 in the ischemic stroke subgroup). In patients with ischemic stroke, AUROC was higher for Brown ESUS-AF compared to HAVOC (p = 0.014), CH2EST (p = 0.002), and Empoli ESUS-AF (p = 0.015) and for LADS (AUROC = 0.690) compared to CH2EST (p = 0.039) and Empoli ESUS-AF (p = 0.015). AF prediction scores based on clinical and cardiovascular imaging parameters do not predict AF detection with adequate accuracy in patients with CS or TIA and ILR. Brown ESUS-AF and LADS scores demonstrated a better performance compared to other prediction scores.

Introduction: Embolic strokes related to atrial fibrillation (AF) carry significant morbidity and mortality. Identifying patients with asymptomatic AF following stroke is difficult. A protocol for incorporation of implantable loop recorders (ILR) in stroke management has not been established. Methods: We developed a protocol for evaluation of patients with cryptogenic embolic stroke using ILR for detection of AF (figure 1). Patients implanted with ILR were enrolled in an AF clinic with structured remote follow-up. The primary end point was time to first detected AF. Secondary end point was time to initiation of anticoagulation following identification of AF. Results: 95 patients underwent ILR placement. Baseline characteristics are shown in table 1. The median time between stroke and ILR placement was 6 days with a range of 1 to 496 days. The mean follow-up time was 169.4 +/- 103.1days. 18 patients (18.9%) had AF detected during the study period (Figure 2). Mean time to detection of AF was 95.7 +/- 93.6 days. 94.4% were anticoagulated (52.9% Rivaroxaban, 41.2% Apixaban, 5.9% Warfarin). The median time from detection of AF to initiation of anticoagulation was 2 days with a range of 1 to 28 days. Conclusions: A protocol for incorporating ILR in evaluation of embolic cryptogenic stroke can improve AF detection and time to initiation of anticoagulation.

Introduction: Patients who suffer from cryptogenic stroke (CS) are routinely screened for asymptomatic paroxysmal atrial fibrillation (AF) with implantable loop recorders (ILRs). The clinical risk factors associated with AF after CS are not fully defined, and it is a common perception that ILRs are not helpful in younger patients with CS. Research Questions/Objectives: To identify which clinical characteristics are associated with AF detection via ILR in patients who have suffered CS. To identify if there is an age cut-off, below which ILR implantation is likely to be futile in patients with CS. Methods: A retrospective cohort study was conducted on patients with CS who underwent ILR implantation at Thomas Jefferson University Hospital from 04/2019 to 04/2021. Patients were excluded from the analysis if there was <6 months of ILR follow-up, delayed ILR placement (>1 year after CS), or pre-existing (known) AF. Baseline demographics and clinical characteristics were collected (Table 1). Patients with and without AF detection within 1 year of CS were compared and multivariable logistic regression was applied to the univariate predictors that were significant (Table 2). Analyses were run in R Studio 4.4.2. Results: We identified a total of 282 patients with CS who received ILRs. Of these 282 patients, 218 formed the study group after applying exclusion criteria (age 63.45±10.58 years, 45% female). AF was detected within 1 year of CS in 47 patients (21.6%) with a mean time from CS to AF detection of 125.30± 94.64 days. In univariate analyses, AF was statistically significantly associated with older age, LAVI, CHA2DS2-VASc score, LVEF%, CKD stage, and presence of atrial runs (Table 1). After multivariable adjustment (Table 2), CKD stage 5 (OR 14.4, p=0.0168), atrial runs (OR 3.77, p=0.0079), and age (OR 1.11, p=0.0056) remained significantly associated with AF detection. However, there were 5 patients below the age of 60 who had AF detected. No significant differences were observed in sex, race, BMI, or other comorbidities. Conclusions: Stage 5 CKD, atrial runs, and age showed significant association with AF detection after cryptogenic stroke. Although age was statistically significant, the OR was low (1.11), and 5 patients below the age of 60 had AF detected. Renal failure and atrial runs were the strongest associates of AF detection after CS. We conclude that there should be no minimum age cut-off for ILR implantation in CS patients.

Introduction: Insertable cardiac monitors (ICMs) have been shown to be superior to standard monitoring for the detection of underlying atrial fibrillation (AF) in patients (pts) with cryptogenic stroke (CS). However, identifying a subset of CS pts who would benefit most from ICMs is desirable. We evaluated whether a recently developed risk score for the prediction of clinically-detected AF in CS pts (the HAVOC score) also predicted the presence of subclinical AF as detected by ICMs. Methods: Pts who received an ICM in the CRYSTAL AF study were included. HAVOC scores were retrospectively calculated by assigning points based on the presence of hypertension (2), age ≥75 (2), valvular disease (2), vascular disease (1), obesity (1), congestive heart failure (4), and coronary artery disease (2), resulting in scores from 0-14 with pts assigned to Group A (0-1), B (2-3), or C (≥4) based on their score. The ICM monitored cardiac rhythm continuously for up to 3 years to identify the presence of AF. AF detected by the ICM (≥2 minutes) was correlated with HAVOC score groupings via the chi-square test. Results: A total of 214 ICM pts (mean age 61±11 years, 66% male) were followed for 1.8±0.7 years. Mean and median HAVOC scores were 2.4±2.6 and 2 [1-3], respectively, with 89% having scores ≤4. The AF detection rate at 3 years was 27%. Mean HAVOC scores tended to be higher among pts with vs. without AF detected (2.9±1.8 vs. 2.3±2.1, p=0.07). The proportion of patients with AF increased significantly from 11% to 18% to 32% as HAVOC scores progressed from Groups A to B to C, respectively (p=0.02). Conclusions: In a cohort of CS pts with ICMs, the prevalence of AF increased significantly with increasing HAVOC score groups. This parameter should be considered when comparing AF detection rates between different studies, as the vast majority of CRYSTAL AF pts had very low HAVOC scores. Further validation of this risk score in CS pts with ICMs is warranted across a broader spectrum of risk measured by this novel score.