Refinement of detecting atrial fibrillation in stroke patients: results from the TRACK-AF Study

Rate of atrial fibrillation by Holter-Stroke Risk Analysis in undetermined TIA/rapidly improving stroke symptoms patients

Introduction

Holter-SRA (Stroke Risk Analysis) is an automated analysis of ECG monitoring for Atrial Fibrillation (AF) detection. The aim of this study was to evaluate the rate of AF in undetermined TIA/Rapidly improving stroke symptoms (RISS) patients.

Methods

Prospective study of undetermined TIA/RISS patients who presented to the emergency department. Early vascular studies (angio CT, transthoracic echocardiography and ECG) were performed in emergency department. The Holter-SRA device was placed for 2 h and the patients were classified into: confirmed AF, high risk of AF or low risk of AF. Prolonged ambulatory monitoring (7 days) was carried out every month for patients with a high-risk pattern. The results were evaluated until definitive detection of AF or low-risk pattern. The endpoints were rate of AF and vascular recurrence at 90 days.

Results

Over a period of 24 months, 83 undetermined TIA/RISS patients were enrolled. The mean age was 70 ± 10 years and 61% were men. The median ABCD2 score was 4 points (1-7). After 2 h of monitoring in the emergency department, AF was detected in one patient (1.2%), 51 patients with a low-risk pattern and 31 patients (37.3%) showed a high-risk pattern of AF. During the ambulatory monitoring, of the 31 patients high risk pattern patients, AF was diagnosed to 17 cases and of the 51 patients with a low-risk pattern, one case experienced a recurrent vascular due to undetected AF (1.9% false negative). Three patients (3.6%) suffered a vascular recurrence within the first 90 days, before AF diagnosis.

Conclusions

In our study, AF was detected in 22.9% of the 83 patients with indeterminate TIA/RISS. Holter-SRA has allowed us to increase the detection of AF, especially those patients with a high-risk pattern in the first 3 months.

Many Models, Little Adoption-What Accounts for Low Uptake of Machine Learning Models for Atrial Fibrillation Prediction and Detection?

(1) Background: Atrial fibrillation (AF) is a major risk factor for stroke and is often underdiagnosed, despite being present in 13-26% of ischemic stroke patients. Recently, a significant number of machine learning (ML)-based models have been proposed for AF prediction and detection for primary and secondary stroke prevention. However, clinical translation of these technological innovations to close the AF care gap has been scant. Herein, we sought to systematically examine studies, employing ML models to predict incident AF in a population without prior AF or to detect paroxysmal AF in stroke cohorts to identify key reasons for the lack of translation into the clinical workflow. We conclude with a set of recommendations to improve the clinical translatability of ML-based models for AF. (2) Methods: MEDLINE, Embase, Web of Science, Clinicaltrials.gov, and ICTRP databases were searched for relevant articles from the inception of the databases up to September 2022 to identify peer-reviewed articles in English that used ML methods to predict incident AF or detect AF after stroke and reported adequate performance metrics. The search yielded 2815 articles, of which 16 studies using ML models to predict incident AF and three studies focusing on ML models to detect AF post-stroke were included. (3) Conclusions: This study highlights that (1) many models utilized only a limited subset of variables available from patients' health records; (2) only 37% of models were externally validated, and stratified analysis was often lacking; (3) 0% of models and 53% of datasets were explicitly made available, limiting reproducibility and transparency; and (4) data pre-processing did not include bias mitigation and sufficient details, leading to potential selection bias. Low generalizability, high false alarm rate, and lack of interpretability were identified as additional factors to be addressed before ML models can be widely deployed in the clinical care setting. Given these limitations, our recommendations to improve the uptake of ML models for better AF outcomes include improving generalizability, reducing potential systemic biases, and investing in external validation studies whilst developing a transparent modeling pipeline to ensure reproducibility.

Predictors of Atrial Fibrillation in Patients with Embolic Stroke of Unknown Etiology and Implantable Loop Recorders-Further Insights of the TRACK AF Study on the Role of ECG and Echocardiography

Aims-Electrocardiography (ECG) and echocardiographic left atrial (LA) parameters may be helpful to assess the risk of atrial fibrillation (AF) in embolic stroke of unknown etiology (ESUS) and could therefore guide intensity of ECG monitoring. Methods-1153 consecutive patients with ischemic stroke or transient ischemic attack (TIA) were analyzed. An internal loop recorder (ILR) was implanted in 104 consecutive patients with ESUS. Multiple morphologic P-wave parameters in baseline 12-channel ECG and echocardiographic LA parameters were measured and analyzed in patients with and without ILR-detected AF. Using logistic regression, we evaluated the predictive value of several ECG parameters and LA dimensions on the occurrence of AF. Results-In 20 of 104 (19%) patients, AF was diagnosed by ILR during a mean monitoring time of 575 (IQR 470-580) days. Patients with AF were significantly older (72 (67-75) vs. 60 (52-72) years; p = 0.001) and premature atrial contractions (PAC) were more frequently observed (40% vs. 2%; p < 0.001) during baseline ECG. All morphologic P-wave parameters did not show a significant difference between groups. There was a non-significant trend towards a larger LA volume index (31 (24-36) vs. 29 (25-37) mL/m2; p = 0.09) in AF patients. Conclusions-Age and PAC are independently associated with incident AF in ESUS and could be used as markers for selecting patients that may benefit from more extensive rhythm monitoring or ILR implantation. In our consecutive cohort of patients with ESUS, neither morphological P-wave parameters nor LA size were predictive of AF.

Detecting atrial fibrillation in the polysomnography-derived electrocardiogram: a software validation study

PURPOSE

The present study validated a software-based electrocardiogram (ECG) analysis tool for detection of atrial fibrillation (AF) and risk for AF using polysomnography (PSG)-derived ECG recordings.

METHODS

The Stroke Risk Analysis® (SRA®) software was applied to 3-channel ECG tracings from diagnostic PSG performed in enrolled subjects including a subgroup of subjects with previously documented AF. No subjects used positive airway pressure therapy. All ECG recordings were visually analyzed by a blinded cardiologist.

RESULTS

Of subjects enrolled in the study, 93 had previously documented AF and 178 of 186 had an ECG that could be analyzed by either method. In subjects with known history of AF, automated analysis using SRA® classified 47 out of 87 ECG as either manifest AF or showing increased risk for paroxysmal AF (PAF) by SRA® (sensitivity 0.54, specificity 0.86). On visual analysis, 36/87 ECG showed manifest AF and 51/87 showed sinus rhythm. Among the latter subgroup, an increased risk for PAF was ascribed by SRA® in 11 cases (sensitivity 0.22, specificity 0.78) and by expert visual analysis in 5 cases (sensitivity 0.1, specificity 0.90). Among 36/178 ECG with manifest AF on visual analysis, 33 were correctly identified by the SRA® software (sensitivity and specificity 0.92).

CONCLUSION

Sleep studies provide a valuable source of ECG recordings that can be easily subjected to software-based analysis in order to identify manifest AF and automatically assess the risk of PAF. For optimal evaluability of data, multiple channel ECG tracings are desirable. For assessment of PAF risk, the SRA® analysis probably excels visual analysis, but sensitivity of both methods is low, reflecting that repeated ECG recording remains essential.

Atrial fibrillation: focus on monitoring strategies after cryptogenic stroke

Atrial fibrillation (AF) is responsible for up to one-third of ischemic strokes, with stroke potentially being the first manifestation of a previously undetected AF. Given the efficacy of oral anticoagulants in preventing AF-related ischemic events, searching for unknown AF after stroke requires a comprehensive diagnostic workup. Prospective data have demonstrated the benefits of long-term cardiac monitoring to identify AF in association with cryptogenic stroke, as most strokes are presumed to result from AF. However, strategies of empirical anticoagulation using oral anticoagulants following cryptogenic stroke failed to improve outcomes. We herein summarize contemporary evidence and knowledge gaps on searching for AF after a stroke and the potential secondary prevention strategies to prevent further recurrences.

Embolic Stroke of Undetermined Source: Approaches in Risk Stratification for Cardioembolism

Ischemic stroke is a leading cause of morbidity and mortality worldwide. Embolic stroke of undetermined source has been recently proposed to categorize nonlacunar ischemic strokes without confirmed etiology after adequate investigation with a likely embolic stroke mechanism. A strategy of empirical anticoagulation for embolic stroke of undetermined source patients is attractive but may only be beneficial in a select subset of patients. Strategies which would help identify the subset of embolic stroke of undetermined source patients most likely to have cardioembolic origin of stroke, and hence benefit from anticoagulation, are needed. This article will review current evidence which may be useful in the development of a risk stratification approach based on arrhythmia monitoring, cardiac imaging, and clinical risk stratification. This approach may be beneficial in clinical practice in improving patient outcomes and reducing stroke recurrence in this population; however, further work is required with active trials underway.

Implantable cardiac monitors to detect atrial fibrillation after cryptogenic stroke: a systematic review and economic evaluation

BACKGROUND

Cryptogenic stroke is a stroke for which no cause is identified after standard diagnostic tests. Long-term implantable cardiac monitors may be better at diagnosing atrial fibrillation and provide an opportunity to reduce the risk of stroke recurrence with anticoagulants.

OBJECTIVES

The objectives were to assess the diagnostic test accuracy, clinical effectiveness and cost-effectiveness of three implantable monitors [BioMonitor 2-AF™ (Biotronik SE & Co. KG, Berlin, Germany), Confirm Rx™ (Abbott Laboratories, Lake Bluff, IL, USA) and Reveal LINQ™ (Medtronic plc, Minneapolis, MN, USA)] in patients who have had a cryptogenic stroke and for whom no atrial fibrillation is detected after 24 hours of external electrocardiographic monitoring.

DATA SOURCES

MEDLINE, EMBASE, The Cochrane Library, Database of Abstracts of Reviews of Effects and Health Technology Assessment databases were searched from inception until September 2018.

REVIEW METHODS

A systematic review was undertaken. Two reviewers agreed on studies for inclusion and performed quality assessment using the Cochrane Risk of Bias 2.0 tool. Results were discussed narratively because there were insufficient data for synthesis. A two-stage de novo economic model was developed: (1) a short-term patient flow model to identify cryptogenic stroke patients who have had atrial fibrillation detected and been prescribed anticoagulation treatment (rather than remaining on antiplatelet treatment) and (2) a long-term Markov model that captured the lifetime costs and benefits of patients on either anticoagulation or antiplatelet treatment.

RESULTS

One randomised controlled trial, Cryptogenic Stroke and underlying Atrial Fibrillation (CRYSTAL-AF) (Sanna T, Diener HC, Passman RS, Di Lazzaro V, Bernstein RA, Morillo CA, et al. Cryptogenic stroke and underlying atrial fibrillation. N Engl J Med 2014;370:2478-86), was identified, and no diagnostic test accuracy study was identified. The CRYSTAL-AF trial compared the Reveal™ XT (a Reveal LINQ predecessor) (Medtronic plc) monitor with standard of care monitoring. Twenty-six single-arm observational studies for the Reveal devices were also identified. The only data for BioMonitor 2-AF or Confirm Rx were from mixed population studies supplied by the companies. Atrial fibrillation detection in the CRYSTAL-AF trial was higher with the Reveal XT than with standard monitoring at all time points. By 36 months, atrial fibrillation was detected in 19% of patients with an implantable cardiac monitor and in 2.3% of patients receiving conventional follow-up. The 26 observational studies demonstrated that, even in a cryptogenic stroke population, atrial fibrillation detection rates are highly variable and most cases are asymptomatic; therefore, they probably would not have been picked up without an implantable cardiac monitor. Device-related adverse events, such as pain and infection, were low in all studies. The de novo economic model produced incremental cost effectiveness ratios comparing implantable cardiac monitors with standard of care monitoring to detect atrial fibrillation in cryptogenic stroke patients based on data for the Reveal XT device, which can be related to Reveal LINQ. The BioMonitor 2-AF and Confirm RX were included in the analysis by making a strong assumption of equivalence with Reveal LINQ. The results indicate that implantable cardiac monitors could be considered cost-effective at a £20,000-30,000 threshold. When each device is compared incrementally, BioMonitor 2-AF dominates Reveal LINQ and Confirm RX.

LIMITATIONS

The cost-effectiveness analysis for implantable cardiac monitors is based on a strong assumption of clinical equivalence and should be interpreted with caution.

CONCLUSIONS

All three implantable cardiac monitors could be considered cost-effective at a £20,000-30,000 threshold, compared with standard of care monitoring, for cryptogenic stroke patients with no atrial fibrillation detected after 24 hours of external electrocardiographic monitoring; however, further clinical studies are required to confirm their efficacy in cryptogenic stroke patients.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42018109216.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 5. See the NIHR Journals Library website for further project information.

Atrial high-rate episodes: prevalence, stroke risk, implications for management, and clinical gaps in evidence

Self-terminating atrial arrhythmias are commonly detected on continuous rhythm monitoring, e.g. by pacemakers or defibrillators. It is unclear whether the presence of these arrhythmias has therapeutic consequences. We sought to summarize evidence on the prevalence of atrial high-rate episodes (AHREs) and their impact on risk of stroke. We performed a comprehensive, tabulated review of published literature on the prevalence of AHRE. In patients with AHRE, but without atrial fibrillation (AF), we reviewed the stroke risk and the potential risk/benefit of oral anticoagulation. Atrial high-rate episodes are found in 10–30% of AF-free patients. Presence of AHRE slightly increases stroke risk (0.8% to 1%/year) compared with patients without AHRE. Atrial high-rate episode of longer duration (e.g. those >24 h) could be associated with a higher stroke risk. Oral anticoagulation has the potential to reduce stroke risk in patients with AHRE but is associated with a rate of major bleeding of 2%/year. Oral anticoagulation is not effective in patients with heart failure or survivors of a stroke without AF. It remains unclear whether anticoagulation is effective and safe in patients with AHRE. Atrial high-rate episodes are common and confer a slight increase in stroke risk. There is true equipoise on the best way to reduce stroke risk in patients with AHRE. Two ongoing trials (NOAH-AFNET 6 and ARTESiA) will provide much-needed information on the effectiveness and safety of oral anticoagulation using non-vitamin K antagonist oral anticoagulants in patients with AHRE.

Software-based analysis of 1-hour Holter ECG to select for prolonged ECG monitoring after stroke

Objective

Identification of ischemic stroke patients at high risk for paroxysmal atrial fibrillation (pAF) during 72 hours Holter ECG might be useful to individualize the allocation of prolonged ECG monitoring times, currently not routinely applied in clinical practice.

Methods

In a prospective multicenter study, the first analysable hour of raw ECG data from prolonged 72 hours Holter ECG monitoring in 1031 patients with acute ischemic stroke/TIA presenting in sinus rhythm was classified by an automated software (AA) into “no risk of AF” or “risk of AF” and compared to clinical variables to predict AF during 72 hours Holter‐ECG.

Results

pAF was diagnosed in 54 patients (5.2%; mean age: 78 years; female 56%) and was more frequently detected after 72 hours in patients classified by AA as “risk of AF” (n = 21, 17.8%) compared to “no risk of AF” (n = 33, 3.6%). AA‐based risk stratification as “risk of AF” remained in the prediction model for pAF detection during 72 hours Holter ECG (OR3.814, 95% CI 2.024‐7.816, P < 0.001), in addition to age (OR1.052, 95% CI 1.021‐1.084, P = 0.001), NIHSS (OR 1.087, 95% CI 1.023‐1.154, P = 0.007) and prior treatment with thrombolysis (OR2.639, 95% CI 1.313‐5.306, P = 0.006). Similarly, risk stratification by AA significantly increased the area under the receiver operating characteristic curve (AUC) for prediction of pAF detection compared to a purely clinical risk score (AS5F alone: AUC 0.751; 95% CI 0.724‐0.778; AUC for the combination: 0.789, 95% CI 0.763‐0.814; difference between the AUC P = 0.022).

Interpretation

Automated software‐based ECG risk stratification selects patients with high risk of AF during 72 hours Holter ECG and adds predictive value to common clinical risk factors for AF prediction.

Incidence and Risk Assessment for Atrial Fibrillation at 5 Years: Hypertensive Diabetic Retrospective Cohort

(1) Background: The link between diabetes and hypertension is mutual and reciprocal, increasing the risks for the development of atrial fibrillation (AF). The main objective was to develop a prediction model for AF in a population with both diabetes and hypertension at five years of follow-up. (2) Methods: A multicenter and community-based cohort study was undertaken of 8237 hypertensive diabetic patients without AF between 1 January 2103 and 31 December 2017. Multivariate Cox proportional-hazards regression models were used to identify predictors AF and to stratify risk scores by quartiles. (3) Results: AF incidence was 10.5/1000 people/years (95% confidence interval (CI) 9.5-11.5), higher in men. The independent prognostic factors identified: age (hazard ratio (HR) 1.07 95% CI 1.05-1.09, p < 0.001), weight (HR 1.03 95% CI 1.02-1.04, p < 0.001), CHA₂DS₂VASc score (HR 1.57 95% CI 1.16-2.13, p = 0.003) and female gender (HR 0.55 95% CI 0.37-0.82, p = 0.004). Q4 (highest-risk group for AF) had the highest AF incidence, stroke and mortality, and the smallest number needed to screen to detect one case of AF. (4) Conclusions: Risk-based screening for AF should be used in high cardiovascular risk patients as the hypertensive diabetics, for treatment of modifiable cardiovascular risk, and monitoring AF detection.

Stroke Risk Analysis, a System With a High Detection Rate of Atrial Fibrillation in Stroke and Transient Ischemic Attack

Background and Purpose- Stroke Risk Analysis (SRA) comprises an algorithm for automated analysis of ECG monitoring, enabling the detection of paroxysmal atrial fibrillation (pxAF) and identifying patterns indicating a high risk of atrial fibrillation (R_AF). We compared Holter-enabled continuous ECG monitoring in combination with SRA (hSRA) with standard continuous ECG monitoring for pxAF detection in patients with acute ischemic stroke. Also, we sought to identify whether the detection of R_AF patterns during the first cycle (first 2 hours) of hSRA recording was associated with the detection of pxAF during the Stroke Unit stay. Methods- We enrolled 524 consecutive patients admitted in the Stroke Unit with acute ischemic stroke or transient ischemic attack with neither history of AF nor AF at admission into a prospective multicentric observational analytic clinical study with intrapatient comparison, who received both continuous ECG monitoring as well as hSRA up to 7 days. Investigators were blinded to hSRA results unless pxAF was detected on SRA. Results- Of the 524 consecutive acute stroke patients (median age, 70.0 years; 60% male; acute ischemic stroke 93%, transient ischemic attack 7%), 462 were eligible and included in the study. Among 462 patients with hSRA available for 66 hours, AF was documented by hSRA in 79 patients (17.1%). From this group, 45 AF cases (9.7%) were confirmed after review by an independent and blinded cardiologist. continuous ECG monitoring detected 21 AF cases (4.3%; P<0.0001). hSRA detected R_AF patterns in 92 patients. 35 out of the 92 R_AF patients showed an episode of AF during the Stroke Unit stay. Predictive values of R_AF patterns within the first cycle of hSRA were: sensitivity 71%, specificity 86%, positive predictive value 38%, and negative predictive value 96%. Conclusions- Automated analysis using SRA technology strongly improves pxAF detection in acute ischemic stroke patients compared with continuous ECG monitoring. The predictive value of a R_AF pattern, as detected by hSRA during the first few hours after admission, deserves further investigation.

Use of insertable cardiac monitors for the detection of atrial fibrillation in patients with cryptogenic stroke in the United States is cost-effective

Objectives: Atrial fibrillation (AF) is the most common arrhythmia and a major marker of ischemic stroke risk. Early detection is crucial and, once diagnosed, anticoagulation therapy can be initiated to reduce stroke risk. The aim of this study was to assess the cost-effectiveness of employing an insertable cardiac monitor (ICM), BIOMONITOR, for the detection of AF compared to standard of care (SoC) ECG and Holter monitoring in patients with cryptogenic stroke, that is, stroke of unknown origin and where paroxysmal, silent AF is suspected. Materials and methods: A Markov model was developed which consisted of five main health states reflecting the potential lifetime evolution of the AF disease: post cryptogenic stroke (index event), subsequent mild, moderate and severe stroke, and death. Sub-states were included to track a patient's AF diagnostic status and the use of antiplatelet or anticoagulant therapy. AF detection was assumed to result in a treatment switch from aspirin to anticoagulants, except among those with a history of major bleeding. Detection yield and accuracy, clinical actions and treatment effects were derived from the literature and validated by an expert clinician. All relevant costs from a US Medicare perspective were included. Results and conclusions: An ICM-based strategy was associated with a reduction of 37 secondary ischemic strokes per 1000 patients monitored compared with SoC. Total per-patient costs with an ICM were higher (US$90,052 vs. US$85,157) although stroke-related costs were reduced. The use of an ICM was associated with a base-case incremental cost-effectiveness ratio of US$18,487 per life year gained compared with SoC and US$25,098 per quality-adjusted life year gained, below established willingness-to-pay thresholds. The conclusions were found to be robust over a range of input values. From a US Medicare perspective the use of a BIOMONITOR ICM represents a cost-effective diagnostic strategy for patients with cryptogenic stroke and suspected AF.

Duration of Implantable Cardiac Monitoring and Detection of Atrial Fibrillation in Ischemic Stroke Patients: A Systematic Review and Meta-Analysis

BACKGROUND AND PURPOSE

Current guidelines do not provide firm directions on atrial fibrillation (AF) screening after ischemic stroke (IS). We sought to investigate the association of implantable cardiac monitoring (ICM) duration with the yield of AF detection in IS patients.

METHODS

We included studies reporting AF detection rates by ICM in IS patients with negative initial AF screening. We excluded studies reporting prolonged cardiac monitoring with devices other than ICM, not providing AF detection rates or monitoring duration, and reporting overlapping data for the same population. The random-effects model was used for all pooled estimates and meta-regression analyses.

RESULTS

We included 28 studies (4,531 patients, mean age 65 years). In meta-regression analyses, the proportion of AF detection by ICM was independently associated with monitoring duration (coefficient=0.015; 95% confidence interval [CI], 0.005 to 0.024) and mean patient age (coefficient=0.009; 95% CI, 0.003 to 0.015). No associations were detected with other patient characteristics, including IS subtype (cryptogenic vs. embolic stroke of undetermined source) or time from IS onset to CM implantation. In subgroup analyses, significant differences (P<0.001) in the AF detection rates were found for ICM duration (<6 months: 5% [95% CI, 3% to 6%]; ≥6 and ≤12 months: 21% [95% CI, 16% to 25%]; >12 and ≤24 months: 26% [95% CI, 22% to 31%]; >24 months: 34% [95% CI, 29% to 39%]).

CONCLUSION

s Extended duration of ICM monitoring and increased patient age are factors that substantially increase AF detection in IS patients with initial negative AF screening.

Atrial fibrillation in cryptogenic stroke and transient ischaemic attack - The Nordic Atrial Fibrillation and Stroke (NOR-FIB) Study: Rationale and design

Purpose

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.

Method

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.

Conclusion

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.

Long-term monitoring to detect atrial fibrillation with the indwelling implantable cardiac monitors

An increasing number of detection tools are available and several detection strategies have been described to pursue the diagnosis of atrial fibrillation to prevent ischemic stroke. Monitoring tools include standard electrocardiography, snapshot single-lead recordings with professional or personal devices (e.g. smartphone-based), Holter monitor, external devices with long-term recording capabilities, and cardiac implantable electronic devices, including pacemakers, implantable cardioverter defibrillators and insertable cardiac monitors. Insertable cardiac monitors have shown high sensitivity and specificity for the detection of atrial fibrillation, allow up to three years of continuous monitoring, do not require cooperation of the patient, are well tolerated, have a short device-related time delay between detection of atrial fibrillation and notification to the physician, provide information on atrial fibrillation burden and are minimally invasive. On the other hand, insertable cardiac monitors require a considerable use of resources to process the recordings and have a significant initial cost. Studies conducted with insertable cardiac monitors on patients with prior stroke and on patients with risk factors for stroke but no prior cerebrovascular events or atrial fibrillation have consistently shown a measurable incidence of atrial fibrillation at follow-up. However, the effectiveness of oral anticoagulations in reducing the incidence of ischemic stroke in patients with atrial fibrillation lasting less than 24 h, though reasonable, is currently unproven. The future of atrial fibrillation detection tools and atrial fibrillation detection strategies will be influenced by ongoing studies exploring whether oral anticoagulations reduce the incidence of stroke in patients with atrial fibrillation burden lower than 24 h.