Predictors of new onset atrial fibrillation during 10-year follow-up after first-ever ischemic stroke

ECG predictors of AF: A systematic review (predicting AF in ischaemic stroke-PrAFIS)

In 25% of patients presenting with embolic stroke, a cause is not determined. Atrial fibrillation (AF) is a commonly identified mechanism of stroke in this population, particularly in older patients. Conventional investigations are used to detect AF, but can we predict AF in this population and generally? We performed a systematic review to identify potential predictors of AF on 12-lead electrocardiogram (ECG).

METHOD

We conducted a search of EMBASE and Medline databases for prospective and retrospective cohorts, meta-analyses or case-control studies of ECG abnormalities in sinus rhythm predicting subsequent atrial fibrillation. We assessed quality of studies based on the Newcastle-Ottawa scale and data were extracted according to PRISMA guidelines.

RESULTS

We identified 44 studies based on our criteria. ECG patterns that predicted the risk of developing AF included interatrial block, P-wave terminal force lead V1, P-wave dispersion, abnormal P-wave-axis, abnormal P-wave amplitude, prolonged PR interval, left ventricular hypertrophy, QT prolongation, ST-T segment abnormalities and atrial premature beats. Furthermore, we identified that factors such as increased age, high CHADS-VASC, chronic renal disease further increase the positive-predictive value of some of these parameters. Several of these have been successfully incorporated into clinical scoring systems to predict AF.

CONCLUSION

There are several ECG abnormalities that can predict AF both independently, and with improved predictive value when combined with clinical risk factors, and if incorporated into clinical risk scores. Improved and validated predictive models could streamline selection of patients for cardiac monitoring and initiation of oral anticoagulants.

Atrial fibrillation in embolic stroke of undetermined source: role of advanced imaging of left atrial function

AIMS

Atrial fibrillation (AF) is detected in over 30% of patients following an embolic stroke of undetermined source (ESUS) when monitored with an implantable loop recorder (ILR). Identifying AF in ESUS survivors has significant therapeutic implications, and AF risk is essential to guide screening with long-term monitoring. The present study aimed to establish the role of left atrial (LA) function in subsequent AF identification and develop a risk model for AF in ESUS.

METHODS AND RESULTS

We conducted a single-centre retrospective case-control study including all patients with ESUS referred to our institution for ILR implantation from December 2009 to September 2019. We recorded clinical variables at baseline and analysed transthoracic echocardiograms in sinus rhythm. Univariate and multivariable analyses were performed to inform variables associated with AF. Lasso regression analysis was used to develop a risk prediction model for AF. The risk model was internally validated using bootstrapping. Three hundred and twenty-three patients with ESUS underwent ILR implantation. In the ESUS population, 293 had a stroke, whereas 30 had suffered a transient ischaemic attack as adjudicated by a senior stroke physician. Atrial fibrillation of any duration was detected in 47.1%. The mean follow-up was 710 days. Following lasso regression with backwards elimination, we combined increasing lateral PA (the time interval from the beginning of the P wave on the surface electrocardiogram to the beginning of the A' wave on pulsed wave tissue Doppler of the lateral mitral annulus) [odds ratio (OR) 1.011], increasing Age (OR 1.035), higher Diastolic blood pressure (OR 1.027), and abnormal LA reservoir Strain (OR 0.973) into a new PADS score. The probability of identifying AF can be estimated using the formula. Model discrimination was good [area under the curve (AUC) 0.72]. The PADS score was internally validated using bootstrapping with 1000 samples of 150 patients showing consistent results with an AUC of 0.73.

CONCLUSION

The novel PADS score can identify the risk of AF on prolonged monitoring with ILR following ESUS and should be considered a dedicated risk stratification tool for decision-making regarding the screening strategy for AF in stroke.

ECG Smart Monitoring versus Implantable Loop Recorders for Atrial Fibrillation Detection after Cryptogenic Stroke-An Overview for Decision Making

Up to 20% of patients with ischemic stroke or transient ischemic attack have a prior history of known atrial fibrillation (AF). Additionally, unknown AF can be detected by different monitoring strategies in up to 23% of patients with cryptogenic or non-cardioembolic stroke. However, most studies had substantial gaps in monitoring time, especially early after the index event. Following this, AF rates would be higher if patients underwent continuous monitoring early after stroke, avoiding any gaps in monitoring. The few existing randomized studies focused on patients with cryptogenic stroke but did not focus otherwise specifically on prevention strategies in patients at high risk for AF (patients at higher age or with high CHA2DS2-VASC scores). Besides invasive implantable loop recorders (ILRs), external loop recorders (ELRs) and mobile cardiac outpatient telemetry (MCOT) are non-invasive tools that are commonly used for long-term ECG monitoring in cryptogenic-stroke patients in the ambulatory setting. The role of MCOT and hand-held devices within ECG smart monitoring in the detection of AF for the prevention of and after cryptogenic stroke is currently unclear. This intense review provides an overview of current evidence, techniques, and gaps in knowledge and aims to advise which patients benefit most from the current available devices.

Electrocardiographic Predictors of Atrial Fibrillation

BACKGROUND

Atrial fibrillation (AF) is the most common pathological arrhythmia, and its complications lead to significant morbidity and mortality. However, patients with AF can often go undetected, especially if they are asymptomatic or have a low burden of paroxysms. Identification of those at high risk of AF development may help refine screening and management strategies.

METHODS

PubMed and Embase databases were systematically searched for studies looking at electrocardiographic predictors of AF from inception to August 2021.

RESULTS

A total of 115 studies were reported which examined a combination of atrial and ventricular parameters that could be electrocardiographic predictors of AF. Atrial predictors include conduction parameters, such as the PR interval, p-wave index and dispersion, and partial interatrial or advanced interatrial block, or morphological parameters, such as p-wave axis, amplitude and terminal force. Ventricular predictors include abnormalities in QRS amplitude, morphology or duration, QT interval duration, r-wave progression and ST segment, i.e., t-wave abnormalities.

CONCLUSIONS

There has been significant interest in electrocardiographic prediction of AF, especially in populations at high risk of atrial AF, such as those with an embolic stroke of undetermined source. This review highlights the breadth of possible predictive parameters, and possible pathological bases for the predictive role of each parameter are proposed.

Inflammatory cytokines differ between patients with high versus low CHA2DS2-VASc scores in sinus rhythm-a possible mechanism for adverse cardiovascular events

Background

The CHA₂DS₂-VASc score was shown to predict systemic thromboembolism and mortality in certain groups of patients in sinus rhythm (SR). Previous data showed that patients in SR with high CHA₂DS₂-VASc score have higher plasma levels of inflammatory markers such as sP-selectin and C-reactive protein. We further investigated this group.

Methods

Blood samples were collected from consecutive patients in SR. Plasma was extracted and stored at -80 °C. Concentrations of a panel of soluble markers IL-1β, IL-6, IL-8, IL-10, TNF-α and VEGF were measured by Magnetic Luminex Performance Assay. The PLF4 cytokine blood level was measured by ELISA.

Results

66 patients were enrolled (age 53 ± 18 years, 60% women). Patients with high CHA₂DS₂-VASc scores (n = 23) had significantly higher median IQR concentrations of TNF-α [10.34 (8.55,14.92) vs. 7.69 (6.06, 9.85) pg/ml, p = 0.009] and a trend towards higher levels of IL-1β [0.59 (0.4,0.8) vs. 0.44 (0.31, 0.62) pg/ml, p = 0.07] and IL-8 [5.92 (4.5,9.4) vs. 5.04 (3.63, 6.04) pg/ml, p = 0.07], compared to the group with low scores (n = 43). Median IQR concentrations of VEGF, IL-6, IL-10 and PF4 did not significantly differ between the CHA₂DS₂-VASc score groups.

Conclusion

Patients in SR with high versus low CHA₂DS₂-VASc scores have high plasma concentrations of systemic inflammation cytokines. The already proven high levels of sP-selectin, that promotes release of inflammatory cytokines from leukocytes, is in line with these results. This pro-inflammatory state in patients with high CHA₂DS₂-VASc scores, may explain the higher rate of adverse cardiovascular events associated with elevated CHA₂DS₂-VASc score even without atrial fibrillation.

Validation of Risk Scores for Predicting Atrial Fibrillation Detected After Stroke Based on an Electronic Medical Record Algorithm: A Registry-Claims-Electronic Medical Record Linked Data Study

Background

Poststroke atrial fibrillation (AF) screening aids decisions regarding the optimal secondary prevention strategies in patients with acute ischemic stroke (AIS). We used an electronic medical record (EMR) algorithm to identify AF in a cohort of AIS patients, which were used to validate eight risk scores for predicting AF detected after stroke (AFDAS).

Methods

We used linked data between a hospital stroke registry and a deidentified database including EMRs and administrative claims data. EMR algorithms were constructed to identify AF using diagnostic and medication codes as well as free clinical text. Based on the optimal EMR algorithm, the incidence rate of AFDAS was estimated. The predictive performance of 8 risk scores including AS5F, C₂HEST, CHADS₂, CHA₂DS₂-VASc, CHASE-LESS, HATCH, HAVOC, and Re-CHARGE-AF scores, were compared using the C-index, net reclassification improvement, integrated discrimination improvement, calibration curve, and decision curve analysis.

Results

The algorithm that defines AF as any positive mention of AF-related keywords in electrocardiography or echocardiography reports, or presence of diagnostic codes of AF was used to identify AF. Among the 5,412 AIS patients without known AF at stroke admission, the incidence rate of AFDAS was 84.5 per 1,000 person-year. The CHASE-LESS and AS5F scores were well calibrated and showed comparable C-indices (0.741 versus 0.730, p = 0.223), which were significantly higher than the other risk scores.

Conclusion

The CHASE-LESS and AS5F scores demonstrated adequate discrimination and calibration for predicting AFDAS. Both simple risk scores may help select patients for intensive AF monitoring.

Mobile Single-Lead Electrocardiogram Technology for Atrial Fibrillation Detection in Acute Ischemic Stroke Patients

(1) Background: AliveCor KardiaMobile (KM) is a portable electrocardiography recorder for detection of atrial fibrillation (AF). The aim of the study was to define the group of acute ischemic stroke (AIS) patients who can use the KM device and assess the diagnostic test accuracy. (2) Methods: the AIS patients were recruited to the study. Thirty-second single-lead electrocardiogram (ECG) usages were recorded on demand for three days using KM portable device. Each KM ECG record was verified by a cardiologist. The feasibility was evaluated using operationalization criteria. (3) Results: the recruitment rate among AIS patients was 26.3%. The withdrawal rate before the start of the intervention was 26%. The withdrawal rate after the start of the intervention was 6%. KM device detected AF in 2.8% of AIS patients and in 2.2% of ECG records. Cardiologist confirmed the AF in 0.3% AIS patients. Sensitivity and specificity of KM for AF was 100% and 98.3%, respectively. (4) Conclusions: the results of this study suggest that it is feasible to use KM device to detect AF in the selected AIS patients (younger and in better neurological condition). KM detected AF in the selected AIS patients with high specificity and sensitivity.

The significance of the morphology-voltage-P-wave duration (MVP) ECG score for prediction of in-hospital and long-term atrial fibrillation in ischemic stroke

BACKGROUND

Atrial fibrillation (AF) is the most common preventable cause of stroke. Diagnosis of new AF is frequent after acute ischemic stroke (AIS). We aimed to evaluate the predictive value of the recently developed morphology-voltage-P-wave duration (MVP) ECG risk score for in-hospital and long-term AF diagnosis following AIS.

MATERIAL AND METHODS

In this observational investigation, we evaluated the ability of the MVP ECG risk score to predict AF in 266 consecutive patients with AIS. The study population was divided into three groups according to their calculated MVP ECG risk score on admission electrocardiography. The groups were compared in terms of their predictive value for in-hospital and long-term AF diagnosis.

RESULTS

After adjustment for confounding baseline variables, MVP ECG risk score 5-6 group had 13.2 times higher rates of in-hospital AF compared to MVP ECG risk score 0-2 group, which was used as the reference group. For long-term follow-up, MVP ECG risk score 5-6 group had 5.2 times higher rates of long-term AF compared to MVP ECG risk score 0-2 group. A ROC analysis showed that the optimal cut-off value of the MVP ECG risk score to predict in-hospital AF was 4 with 78% sensitivity and 76% specificity (AUC: 0.80; 95% CI: 0.64-0.96; p < 0.001), the optimal cut-off value of the MVP ECG risk score to predict long-term AF was 3 with 85% sensitivity and 59% specificity (AUC: 0.81; 95% CI: 0.76-0.86; p < 0.001).

CONCLUSION

The MVP ECG risk score, which can be easily calculated from a surface ECG, can be used to guide who needs stricter monitoring for the diagnosis of long-term AF in patients with AIS.

Development and validation of a score to detect paroxysmal atrial fibrillation after stroke

OBJECTIVE

Prolonged monitoring times (72 hours) are recommended to detect paroxysmal atrial fibrillation (pAF) after ischemic stroke but this is not yet clinical practice; therefore, an individual patient selection for prolonged ECG monitoring might increase the diagnostic yield of pAF in a resource-saving manner.

METHODS

We used individual patient data from 3 prospective studies (n_total = 1,556) performing prolonged Holter-ECG monitoring (at least 72 hours) and centralized data evaluation after TIA or stroke in patients with sinus rhythm. Based on the TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) guideline, a clinical score was developed on one cohort, internally validated by bootstrapping, and externally validated on 2 other studies.

RESULTS

pAF was detected in 77 of 1,556 patients (4.9%) during 72 hours of Holter monitoring. After logistic regression analysis with variable selection, age and the qualifying stroke event (categorized as stroke severity with NIH Stroke Scale [NIHSS] score ≤5 [odds ratio 2.4 vs TIA; 95% confidence interval 0.8-6.9, p = 0.112] or stroke with NIHSS score >5 [odds ratio 7.2 vs TIA; 95% confidence interval 2.4-21.8, p < 0.001]) were found to be predictive for the detection of pAF within 72 hours of Holter monitoring and included in the final score (Age: 0.76 points/year, Stroke Severity NIHSS ≤5 = 9 points, NIHSS >5 = 21 points; to Find AF [AS5F]). The high-risk group defined by AS5F is characterized by a predicted risk between 5.2% and 40.8% for detection of pAF with a number needed to screen of 3 for the highest observed AS5F points within the study population. Regarding the low number of outcomes before generalization of AS5F, the results need replication.

CONCLUSION

The AS5F score can select patients for prolonged ECG monitoring after ischemic stroke to detect pAF.

CLASSIFICATION OF EVIDENCE

This study provides Class I evidence that the AS5F score accurately identifies patients with ischemic stroke at a higher risk of pAF.

Relationship between QRS duration and incident atrial fibrillation

BACKGROUND

QRS duration (QRSd), a measure of ventricular conduction, has been associated with adverse cardiovascular outcomes, but its relationship with incident atrial fibrillation (AF) is poorly understood.

METHODS AND RESULTS

This study included 15,314 participants from the Atherosclerosis Risk in Communities (ARIC) study who were free of AF at baseline. QRSd was automatically measured from resting 12-lead electrocardiograms (ECGs) at baseline. Incident AF cases were systematically ascertained using ECGs, hospital discharge diagnoses and death certificates. Multivariable adjusted Cox regression analyses were performed to investigate the relationship between QRSd and incident AF. Mean age of our population was 54 ± 6 years (55% females). During a median follow-up of 21.2 years, 2041 confirmed incident AF cases occurred. In multivariable adjusted Cox models, a 1-SD increase in QRSd was associated with a hazard ratio (HR) (95% CI) for AF of 1.05 (1.01; 1.10), p = 0.01. This relationship was significant among women (HR per 1-SD increase in QRSd (95% CI) 1.13 (1.06; 1.20), p < 0.001), but not among men (1.00 (0.95; 1.06), p = 0.97) (p for interaction 0.005). Compared to individuals with a QRSd <100 ms, the HRs for incident AF in individuals with a QRSd of 100-119 and ≥120 ms were 1.13 (1.02; 1.26) and 1.35 (1.08; 1.68), respectively (p for trend 0.002). Again, this relationship was significant among women (p for trend <0.001) but not among men (p for trend 0.23).

CONCLUSION

In this large population-based study, QRSd was an independent predictor of incident AF among women, but not in men. Further studies are needed to better understand the underlying mechanisms.

The complexity of atrial fibrillation newly diagnosed after ischemic stroke and transient ischemic attack: advances and uncertainties

Purpose of review

Atrial fibrillation is being increasingly diagnosed after ischemic stroke and transient ischemic attack (TIA). Patient characteristics, frequency and duration of paroxysms, and the risk of recurrent ischemic stroke associated with atrial fibrillation detected after stroke and TIA (AFDAS) may differ from atrial fibrillation already known before stroke occurrence. We aim to summarize major recent advances in the field, in the context of prior evidence, and to identify areas of uncertainty to be addressed in future research.

Recent findings

Half of all atrial fibrillations in ischemic stroke and TIA patients are AFDAS, and most of them are asymptomatic. Over 50% of AFDAS paroxysms last less than 30 s. The rapid initiation of cardiac monitoring and its duration are crucial for its timely and effective detection. AFDAS comprises a heterogeneous mix of atrial fibrillation, possibly including cardiogenic and neurogenic types, and a mix of both. Over 25 single markers and at least 10 scores have been proposed as predictors of AFDAS. However, there are considerable inconsistencies across studies. The role of AFDAS burden and its associated risk of stroke recurrence have not yet been investigated.

Summary

AFDAS may differ from atrial fibrillation known before stroke in several clinical dimensions, which are important for optimal patient care strategies. Many questions remain unanswered. Neurogenic and cardiogenic AFDAS need to be characterized, as it may be possible to avoid some neurogenic cases by initiating timely preventive treatments. AFDAS burden may differ in ischemic stroke and TIA patients, with distinctive diagnostic and treatment implications. The prognosis of AFDAS and its risk of recurrent stroke are still unknown; therefore, it is uncertain whether AFDAS patients should be treated with oral anticoagulants.

A score for paroxysmal atrial fibrillation in acute ischemic stroke

Aim Many patients with ischemic stroke have paroxysmal atrial fibrillation that may be difficult to detect. We sought to identify markers of paroxysmal atrial fibrillation and construct a score that may help the clinician to select patients for anticoagulation even if investigations do not disclose atrial fibrillation. Methods A group of patients with acute ischemic stroke and TIA and documented paroxysmal atrial fibrillation was compared to a group of patients with ischemic stroke and TIA and no known paroxysmal atrial fibrillation and sinus rhythm on Holter monitoring. Clinical features, blood tests, ECG, and MRI findings were compared. Sensitivity and specificity of significant markers for paroxysmal atrial fibrillation were calculated. A simple score based on independent markers for paroxysmal atrial fibrillation was constructed. Results Out of 3480 patients with TIA or ischemic stroke, 237 (19%) had paroxysmal atrial fibrillation and 1002 (81%) had sinus rhythm. On univariate analyses, significant markers for paroxysmal atrial fibrillation included increasing age, females, prior ischemic stroke, myocardial infarction, other heart diseases, pathologic troponin, embolic stroke and stroke in different arterial territories (all P < .01). A score including age dichotomized at 75 years, cardiac disease and troponin was constructed. Conclusion We identified many markers for paroxysmal atrial fibrillation and constructed a score that may help the clinician to select patients for anticoagulation even if investigations do not disclose paroxysmal atrial fibrillation.

Atrial time and voltage dispersion are both needed to predict new-onset atrial fibrillation in ischemic stroke patients

BACKGROUND

Atrial fibrillation (AF) is a known risk factor for ischemic stroke. Electrocardiographic predictors of AF in population studies such as the Framingham Heart Study, as well as in hypertensive patients have demonstrated a predictive value of the P-wave duration for development of AF. QRS vector magnitude has had a predictive value in ventricular arrhythmia development. We aimed to assess the value of the three-dimensional P-wave vector magnitude and its relationship to P-wave duration for prediction of new-onset AF after ischemic stroke.

METHODS

First-ever ischemic stroke patients without AF at inclusion in the Lund Stroke Register were included. Measurements of P wave duration (Pd), QRS duration, corrected QT interval, and PQ interval were performed automatically using the University of Glasgow 12-lead ECG analysis algorithm. The P-wave vector magnitude (Pvm) was calculated automatically as the square root of the sum of the squared P-wave magnitudes in leads V6, II and one half of the P-wave amplitude in V2 ([Formula: see text]), based on the P-wave magnitude (Pvm) as defined by the visually transformed Kors' Quasi-orthogonal method.

RESULTS

The median age was 73 (IQR 63-80) years at stroke onset (135 males, 92 females). Multivariate predictors of new-onset atrial fibrillation included age > 65 years, hypertension, and Pd/Pvm. A cut-off value of 870 ms/mV gave sensitivity, specificity, positive and negative predictive values of 51, 79, 30 and 87%, respectively. The Pd/Pvm was the only ECG predictor of AF with a significant multivariate hazard ratio of 2.02 (95% CI 1.18 to 3.46, p = 0.010).

CONCLUSION

P-wave dispersion as measured by the Pd/Pvm was the only ECG parameter measured which independently predicted subsequent AF identification in a cohort of stroke patients. Further prospective studies in larger cohorts are needed to validate its clinical usefulness.

Overcoming global challenges in stroke prophylaxis in atrial fibrillation: The role of non-vitamin K antagonist oral anticoagulants

Atrial fibrillation is the world's most common sustained cardiac arrhythmia and is associated with a significantly increased risk of stroke. The global burden of atrial fibrillation is rising, commensurate with the ageing population. Well-controlled vitamin K antagonist-based anticoagulation has been shown to reduce the risk of stroke secondary to atrial fibrillation by two-thirds. However, patients with atrial fibrillation have frequently been denied anticoagulation because of a variety of perceived risks related to bleeding, falls, chronological age, and poor compliance. Even when vitamin K antagonists are used, maximum benefit and safety are only delivered when high quality control of therapy (TTR > 70%) is achieved, which has proven remarkably difficult in many health-care systems and amongst many patient groups. The non-vitamin K antagonist oral anticoagulants (NOACs) offer solutions to many of the challenges of achieving widespread, safe, and effective anticoagulation for stroke prophylaxis in atrial fibrillation, yet their uptake into routine clinical practice remains variable. The evidence supporting their more widespread use to overcome the challenges of stroke prophylaxis for atrial fibrillation is reviewed in this article.

Impact of atrial fibrillation on postoperative outcomes after total knee arthroplasty-A retrospective study

BACKGROUND

Total knee arthroplasty (TKA) is primarily preformed among the elderly population who is commonly affected by cardiovascular and cerebrovascular diseases. Atrial fibrillation (AF) is a very common heart disease and its prevalence increases significantly with age. Therefore, we decided to evaluate the outcomes of patients with AF following TKA and analyze the risk factors of AF patients who underwent postoperative complication.

METHODS

We designed a retrospective cohort study using data from three institutions in China. We evaluated a total of 453 AF patients who received primary TKA and 453 matched control patients. Comparisons of specific parameters between AF and non-AF cohorts were performed.

RESULTS

Our results demonstrated that AF patients had significantly higher odds of more intraoperative bleeding, periprosthetic joint infection (PJI), post-operative cerebral stroke (POCS), post-operative cardiovascular events (POCE) and worse SF-36 physical component score and mental score at mean 24-month after surgery, but had no increased incidence of post-operative gastrointestinal events, DVT and PE in comparison to patients without AF than those without AF disease. Additionally, multivariate logistic regression analysis was used to identify risk factors of patients who underwent severe complication. Smoking, diabetes mellitus and persistent AF were common risk factors of PJI, POCS, and POCE. Heart rate＞70/min and absence of Beta blocker use were common risk factors of POCS and POCE. Absence of LMWH bridging was risk factor of POCS. BMI >25 kg/m2 and hypertension were risk factors of POCE.

CONCLUSIONS

These findings should be taken into consideration when discussing the expected outcomes of AF patients after TKA. AF disease impaired SF-36 physical component score (PCS) and mental component score (MCS) of patient after TKA.

Optimal Duration of Monitoring for Atrial Fibrillation in Cryptogenic Stroke: A Nonsystematic Review

Atrial fibrillation (AF) is the most common form of cardiac arrhythmias and an independent risk factor for stroke. Despite major advances in monitoring strategies, clinicians tend to miss the diagnoses of AF and especially paroxysmal AF due mainly to its asymptomatic presentation and the rather limited duration dedicated for monitoring for AF after a stroke, which is 24 hours as per the current recommended guidelines. Hence, determining the optimal duration of monitoring for paroxysmal atrial fibrillation after acute ischemic stroke remains a matter of debate. Multiple trials were published in regard to this matter using both invasive and noninvasive monitoring strategies for different monitoring periods. The data provided by these trials showcase strong evidence suggesting a longer monitoring strategy beyond 24 hours is associated with higher detection rates of AF, with the higher percentage of patients detected consequently receiving proper secondary stroke prevention with anticoagulation and thus justifying the cost-effectiveness of such measures. Overall, we thus conclude that increasing the monitoring duration for AF after a cryptogenic stroke to at least 72 hours will indeed enhance the detection rates, but the cost-effectiveness of this monitoring strategy compared to longer monitoring durations is yet to be established.