Score for atrial fibrillation detection in acute stroke and transient ischemic attack patients in a Brazilian population: the acute stroke atrial fibrillation scoring system

Probability of Cardioembolic vs. Atherothrombotic Pathogenesis of Cryptogenic Strokes in Older Patients

Some clinical, laboratory, ECG, and echocardiographic parameters could provide useful indications to assess the probability of cardioembolism or atherothrombosis in cryptogenic strokes. We retrospectively examined 290 patients with ischemic stroke aged ≥60 years, divided into 3 groups: strokes originating from large artery atherothrombosis (n = 92), cardioembolic strokes caused by paroxysmal atrial fibrillation (n = 88) and cryptogenic strokes (n = 110). In addition to echocardiographic and routine clinical-laboratory variables, neutrophil:lymphocyte ratio, red blood cell distribution width, mean platelet volume, P wave and PR interval duration and biphasic inferior P waves, both on admission and after 7 to 10 days, were also considered. By multiple logistic regression, cardioembolic strokes were compared with large artery atherothrombosis strokes, and beta coefficients were rounded to produce a scoring system. Late PR interval ≥188 ms, left atrium ≥4 cm, left ventricular end-diastolic volume <65 ml, and posterior circulation syndrome were associated with paroxysmal atrial fibrillation (positive scores). In contrast, male gender, hypercholesterolemia, and initial platelet count ≥290 × 10⁹/L were associated with atherothrombosis of large arteries (negative scores). The algebraic sum of these scores produced values indicative of cardioembolism if >0 (positive predictive value 89.1%), or of atherothrombosis, if ≤0 (positive predictive value 72.5%). The area under the receiver operating characteristic curve was 0.85. Among cryptogenic strokes, 41.5% had a score >0 (probable atrial fibrillation) and 58.5% had a score ≤0 (possible atherothrombosis). In conclusion, a scoring system based on electrocardiogram, laboratory, clinical and echocardiographic parameters can provide useful guidance for further investigations and secondary prevention in older patients with cryptogenic stroke.

A Simplified Risk Score to Predict In-Hospital Newly-Diagnosed Atrial Fibrillation in Acute Ischemic Stroke Patients

Purpose

Atrial fibrillation (AF) is a significant cause of stroke, and newly diagnosed AF (NDAF) is typically detected in the early period of stroke onset. We aimed to identify the factors associated with in-hospital NDAF in acute ischemic stroke patients and developed a simplified clinical prediction model.

Methods

Patients with cryptogenic stroke aged 18 years or older who were admitted between January 2017 and December 2021 were recruited. NDAF was determined by inpatient cardiac telemetry. Univariable and multivariable regression analyses were used to evaluate the factors associated with in-hospital NDAF. The predictive model was developed using regression coefficients.

Results

The study enrolled 244 eligible participants, of which 52 NDAFs were documented (21.31%), and the median time to detection was two days (1-3.5). After multivariable regression analysis, parameters significantly associated with in-hospital NDAF were elderly (>75 years) (adjusted Odds ratio, 2.99; 95% confident interval, 1.51-5.91; P = 0.002), female sex (2.08; 1.04-4.14; P = 0.04), higher admission national institute of health stroke scale (1.04; 1.00-1.09; P = 0.05), and presence of hyperdense middle cerebral artery sign (2.33; 1.13-4.79; P = 0.02). The area under the receiver operating characteristic curve resulted in 0.74 (95% CI 0.65-0.80), and the cut-point of 2 showed 87% sensitivity and 42% specificity.

Conclusion

The validated and simplified risk scores for predicting in-hospital NDAF primarily rely on simplified parameters and high sensitivity. It might be used as a screening tool for in-hospital NDAF in stroke patients who initially presumed cryptogenic stroke.

A nomogram for predicting atrial fibrillation detected after acute ischemic stroke

Background

Atrial fibrillation detected after stroke (AFDAS) is associated with an increased risk of ischemic stroke (IS) recurrence and death. Early diagnosis can help identify strategies for secondary prevention and improve prognosis. However, there are no validated predictive tools to assess the population at risk for AFDAS. Therefore, this study aimed to develop and validate a predictive model for assessing the incidence of AFDAS after acute ischemic stroke (AIS).

Methods

This study was a multicenter retrospective study. We collected clinical data from 5332 patients with AIS at two hospitals between 2014.01 and 2021.12 and divided the development and validation of clinical prediction models into a training cohort (n = 3173) and a validation cohort (n = 2159). Characteristic variables were selected from the training cohort using the least absolute shrinkage and selection operator (LASSO) algorithm and multivariable logistic regression analysis. A nomogram model was developed, and its performance was evaluated regarding calibration, discrimination, and clinical utility.

Results

We found the best subset of risk factors based on clinical characteristics and laboratory variables, including age, congestive heart failure (CHF), previous AIS/transient ischemia attack (TIA), national institutes of health stroke scale (NIHSS) score, C-reactive protein (CRP), and B-type natriuretic peptide (BNP). A predictive model was developed. The model showed good calibration and discrimination, with calibration values of Hosmer-Lemeshow χ² = 4.813, P = 0.732 and Hosmer-Lemeshow χ² = 4.248, P = 0.834 in the training and validation cohorts, respectively. The area under the ROC curve (AUC) was 0.815, 95% CI (0.777–0.853) and 0.808, 95% CI (0.770–0.847). The inclusion of neuroimaging variables significantly improved the performance of the integrated model in both the training cohort (AUC. 0.846 (0.811–0.882) vs. 0.815 (0.777–0.853), P = 0.001) and the validation cohort (AUC: 0.841 (0.804–0.877) vs. 0.808 (0.770–0.847), P = 0.001). The decision curves showed that the integrated model added more net benefit in predicting the incidence of AFDAS.

Conclusion

Predictive models based on clinical characteristics, laboratory variables, and neuroimaging variables showed good calibration and high net clinical benefit, informing clinical decision-making in diagnosing and treating patients with AFDAS.

Development of a Score to Predict the Paroxysmal Atrial Fibrillation in Stroke Patients: The Screening for Atrial Fibrillation Scale

Background and Purpose

An individual selection of ischemic stroke patients at higher risk of atrial fibrillation (AF) might increase the diagnostic yield of prolonged cardiac monitoring and render it cost-effective.

Methods

The clinical, laboratory, and brain/cardiac imaging characteristics of consecutive ischemic stroke patients without documented AF were recorded. All patients underwent at least 72 h of cardiac monitoring unless AF was diagnosed before, transthoracic echocardiogram, blood biomarkers, and intracranial vessels imaging. A predictive grading was developed by logistic regression analysis, the screening for atrial fibrillation scale (SAFE).

Results

A total of 460 stroke patients were analyzed to develop the SAFE scale, a 7-items score (possible total score 0–10): age ≥ 65 years (2 points); history of chronic obstructive pulmonary disease or obstructive sleep apnea (1 point); thyroid disease (1 point); NT-proBNP ≥ 250 pg/ml (2 points); left atrial enlargement (2 points); cortical topography of stroke, including hemispheric or cerebellar cortex (1 point); and intracranial large vessel occlusion (1 point). A score = 5 identified patients with paroxysmal AF with a sensitivity of 83% and a specificity of 80%.

Conclusion

Screening for atrial fibrillation scale (SAFE) is a novel and simple strategy for selecting ischemic stroke patients at higher risk of having AF who can benefit from a more thorough etiological evaluation. External validation of SAFE in a multicenter study, with a larger number of patients, is warranted.

Development and Validation of a Novel Score for Predicting Paroxysmal Atrial Fibrillation in Acute Ischemic Stroke

Atrial fibrillation (AF)—whether paroxysmal or sustained—increases the risk of stroke. We developed and validated a risk score for identifying patients at risk of paroxysmal atrial fibrillation (pAF) after acute ischemic stroke (AIS). A total of 6033 patients with AIS who received 24 h Holter monitoring were identified in the Chang Gung Research Database. Among the identified patients, 5290 with pAF and without AF were included in the multivariable logistic regression analysis to develop the pAF prediction model. The ABCD-SD score (Age, Systolic Blood pressure, Coronary artery disease, Dyslipidemia, and Standard Deviation of heart rate) comprises age (+2 points for every 10 years), systolic blood pressure (−1 point for every 20 mmHg), coronary artery disease (+2 points), dyslipidemia (−2 points), and standard deviation of heart rate (+2 points for every 3 beats per minute). Overall, 5.2% (274/5290) of patients had pAF. The pAF risk ranged from 0.8% (ABCD-SD score ≤ 7) to 18.3% (ABCD-SD score ≥ 15). The model achieved an area under the receiver operating characteristic curve (AUROCC) of 0.767 in the model development group. The ABCD-SD score could aid clinicians in identifying patients with AIS at risk of pAF for advanced cardiac monitoring.

Promising Biomarker Candidates for Cardioembolic Stroke Etiology. A Brief Narrative Review and Current Opinion

Determining the cause of stroke is considered one of the main objectives in evaluating a stroke patient in clinical practice. However, ischemic stroke is a heterogeneous disorder and numerous underlying disorders are implicated in its pathogenesis. Although progress has been made in identifying individual stroke etiology, in many cases underlying mechanisms still remain elusive. Since secondary prevention strategies are tailored toward individual stroke mechanisms, patients whose stroke etiology is unknown may not receive optimal preventive treatment. Cardioembolic stroke is commonly defined as cerebral vessel occlusion by distant embolization arising from thrombus formation in the heart. It accounts for the main proportion of ischemic strokes, and its share to stroke etiology is likely to rise even further in future decades. However, it can be challenging to distinguish cardioembolism from other possible etiologies. As personalized medicine advances, stroke researchers' focus is increasingly drawn to etiology-associated biomarkers. They can provide deeper insight regarding specific stroke mechanisms and can help to unravel previously undetected pathologies. Furthermore, etiology-associated biomarkers could play an important role in guiding future stroke prevention strategies. To achieve this, broad validation of promising candidate biomarkers as well as their implementation in well-designed randomized clinical trials is necessary. This review focuses on the most-promising candidates for diagnosis of cardioembolic stroke. It discusses existing evidence for possible clinical applications of these biomarkers, addresses current challenges, and outlines future perspectives.

A predictive analytics model for differentiating between transient ischemic attacks (TIA) and its mimics

Background

Transient ischemic attack (TIA) is a brief episode of neurological dysfunction resulting from cerebral ischemia not associated with permanent cerebral infarction. TIA is associated with high diagnostic errors because of the subjective nature of findings and the lack of clinical and imaging biomarkers. The goal of this study was to design and evaluate a novel multinomial classification model, based on a combination of feature selection mechanisms coupled with logistic regression, to predict the likelihood of TIA, TIA mimics, and minor stroke.

Methods

We conducted our modeling on consecutive patients who were evaluated in our health system with an initial diagnosis of TIA in a 9-month period. We established the final diagnoses after the clinical evaluation by independent verification from two stroke neurologists. We used Recursive Feature Elimination (RFE) and Least Absolute Shrinkage and Selection Operator (LASSO) for prediction modeling.

Results

The RFE-based classifier correctly predicts 78% of the overall observations. In particular, the classifier correctly identifies 68% of the cases labeled as “TIA mimic” and 83% of the “TIA” discharge diagnosis. The LASSO classifier had an overall accuracy of 74%. Both the RFE and LASSO-based classifiers tied or outperformed the ABCD2 score and the Diagnosis of TIA (DOT) score. With respect to predicting TIA, the RFE-based classifier has 61.1% accuracy, the LASSO-based classifier has 79.5% accuracy, whereas the DOT score applied to the dataset yields an accuracy of 63.1%.

Conclusion

The results of this pilot study indicate that a multinomial classification model, based on a combination of feature selection mechanisms coupled with logistic regression, can be used to effectively differentiate between TIA, TIA mimics, and minor stroke.

Identification of patients with embolic stroke of undetermined source and low risk of new incident atrial fibrillation: The AF-ESUS score

Background and aims

Only a minority of patients with Embolic Stroke of Undetermined Source (ESUS) receive prolonged cardiac monitoring despite current recommendations. The identification of ESUS patients who have low probability of new diagnosis of atrial fibrillation (AF) could potentially support a strategy of more individualized allocation of available resources and hence, increase their diagnostic yield. We aimed to develop a tool that can identify ESUS patients who have low probability of new incident AF.

Methods

We performed multivariate stepwise regression in a pooled dataset of consecutive ESUS patients from three prospective stroke registries to identify predictors of new incident AF. The coefficient of each independent covariate of the fitted multivariable model was used to generate an integer-based point scoring system.

Results

Among 839 patients (43.1% women, median age 67.0 years) followed-up for a median of 24.3 months (2999 patient-years), 125 (14.9%) had new incident AF. The proposed score assigns 3 points for age ≥ 60 years; 2 points for hypertension; −1 point for left ventricular hypertrophy reported at echocardiography; 2 points for left atrial diameter >40 mm; −3 points for left ventricular ejection fraction <35%; 1 point for the presence of any supraventricular extrasystole recorded during all available 12-lead standard electrocardiograms performed during hospitalization for the ESUS; −2 points for subcortical infarct; −3 points for the presence of non-stenotic carotid plaques. The rate of new incident AF during follow-up was 1.97% among the 42.3% of the cohort who had a score of ≤0, compared to 26.9% in patients with > 0 (relative risk: 13.7, 95%CI: 5.9--31.5). The area under the curve of the score was 84.8% (95%CI: 79.9--86.9%). The sensitivity and negative predictive value of a score of ≤0 for new incident AF during follow-up were 94.9% (95%CI: 89.3--98.1%) and 98.0% (95%CI: 95.8--99.3%), respectively.

Conclusions

The proposed AF-ESUS score has high sensitivity and high negative predictive value to identify ESUS patients who have low probability of new incident AF. Patients with a score of 1 or more may be better candidates for prolonged automated cardiac monitoring.

Clinical trial registration

URL: https://www.clinicaltrials.gov / Unique identifier: NCT02766205.

Usefulness of the ACTEL Score to Predict Atrial Fibrillation in Patients with Cryptogenic Stroke

INTRODUCTION

To assess the probability of undetected atrial fibrillation (AF) in patients with ischemic stroke, we previously compared patients who were first diagnosed with AF with patients with large or small artery disease and obtained the MrWALLETS 8-item scoring system. In the present study, we utilized cryptogenic strokes (CS) as the control group, as AF is normally sought among CS patients.

METHODS

We retrospectively examined 191 ischemic stroke patients (72.5 ± 12.6 years), 68 with first diagnosed AF and 123 with CS, who had undergone 2 brain CT scans, echocardiography, carotid/vertebral ultrasound, continuous electrocardiogram monitoring and anamnestic/laboratory search for cardiovascular risk factors.

RESULTS

In logistic regression, 5 variables were independently associated with AF, forming the "ACTEL" score: Age ≥75 years (OR 2.42, 95% CI 1.18-4.96, p = 0.02; +1 point); hyperCholesterolemia (OR 0.38, 95% CI 0.18-0.78, p = 0.009; -1 point); Tricuspid regurgitation ≥ mild-to-moderate (OR 4.99, 95% CI 1.63-15.27, p = 0.005; +1 point); left ventricular End-diastolic volume <65 mL (OR 7.43, 95% CI 2.44-22.6, p = 0.0004; +1 point); Left atrium ≥4 cm (OR 4.57, 95% CI 1.97-10.62, p = 0.0004; +1 point). The algebraic sum of these points may range from -1 to +4. For AF identification, the area under the receiver operating characteristic curve was 0.80 (95% CI 0.73-0.87). With a cutoff of ≥2, positive predictive value was 80.8%, specificity 92.7% and sensitivity 55.9%.

CONCLUSIONS

The ACTEL score, a simplified and improved version of the MrWALLETS score, allows the identification of patients with first diagnosed AF, in the context of CSs, with a high positive predictive value.

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.

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.

Use of Guidelines for Reducing Stroke Risk in Patients With Nonvalvular Atrial Fibrillation: A Review From a Latin American Perspective

Atrial fibrillation (AF) is a prominent risk factor for stroke and a leading cause of death and disability throughout Latin America. Contemporary evidence-based guidelines for the management of AF and stroke incorporate the use of practical and relatively simple scoring methods to estimate both stroke and bleeding risk, in order to assist in matching patients with appropriate interventions. This review examines consistencies and differences among guidelines for reducing stroke risk in patients with AF, assessing the role of user-friendly scoring methods to determine appropriate patients for anticoagulation and other treatment options. Current options include warfarin and direct oral anticoagulants such as dabigatran, rivaroxaban, apixaban, and edoxaban. These agents have been found to be superior or noninferior to standard vitamin K antagonist anticoagulation in large randomized trials. Potential benefits of these agents mainly include lower ischemic stroke rates, reduced intracranial bleeding, no need for regular monitoring, and fewer drug-drug and drug-food interactions. Expert opinions regarding clinical situations for which data are presently lacking, such as emergency bleeding and stroke in anticoagulated patients, are also provided. Enhanced attention and adherence to evidence-based guidelines are essential components for a strategy to reduce stroke morbidity and mortality across Latin America.

Stroke Prevention in Atrial Fibrillation: Focus on Latin America

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, with an estimated prevalence of 1-2% in North America and Europe. The increased prevalence of AF in Latin America is associated with an ageing general population, along with poor control of key risk factors, including hypertension. As a result, stroke prevalence and associated mortality have increased dramatically in the region. Therefore, the need for effective anticoagulation strategies in Latin America is clear. The aim of this review is to provide a contemporary overview of anticoagulants for stroke prevention. The use of vitamin K antagonists (VKAs, eg, warfarin) and aspirin in the prevention of stroke in patients with AF in Latin America remains common, although around one fifth of all AF patients receive no anticoagulation. Warfarin use is complicated by a lack of access to effective monitoring services coupled with an unpredictable pharmacokinetic profile. The overuse of aspirin is associated with significant bleeding risks and reduced efficacy for stroke prevention in this patient group. The non-VKA oral anticoagulants (NOACbs) represent a potential means of overcoming many limitations associated with VKA and aspirin use, including a reduction in the need for monitoring and a reduced risk of hemorrhagic events. The ultimate decision of which anticoagulant drug to utilize in AF patients depends on a multitude of factors. More research is needed to appreciate the impact of these factors in the Latin American population and thereby reduce the burden of AF-associated stroke in this region.

A functional single-nucleotide polymorphism in interleukin-6 promoter is associated with p wave dispersion in hypertensive subjects with atrial fibrillation

Inflammation has been shown to be implicated in the pathophysiology of atrial fibrillation (AF). Interleukin-6 (IL-6) is a pleiotropic cytokine, functions as a mediator of inflammatory response and has both pro-inflammatory and anti-inflammatory properties. Little is known about genetic factors of inflammation in the accompanying atrial electrical remodeling expressed by P wave dispersion (Pdisp). The aim of the present study is to evaluate the association of -634C/G polymorphism of IL-6 gene with Pdisp in Han Chinese hypertensive patients with AF. A total of 100 patients with essential hypertension (EH) were eligible for this study. Patients with paroxysmal AF (n=50) were allocated to the AF group, and 50 subjects without AF to the control group. The PCR-based restriction fragment length polymorphism (PCR-RFLP) technique was used to assess the genotypes frequencies. The distribution of the IL-6 -634C/G genotypes (CC, CG, and GG) was 68.00%, 28.00%, and 4.00% in the controls, and 44.00%, 40.00%, and 16.00% in AF subjects, respectively (P=0.0269). The frequency of the G allele in the AF group was significantly higher than that in the control group (36.00% vs 18.00%, P=0.0041). Compared to the wild type CC, the G allele carriers (CG + GG genotypes) had a 2.7045-fold increased risk of AF (odds ratio =2.7045, 95% confidence interval =1.1966-6.1126, P=0.0156). AF patients with the CG + GG genotype had longer Pdisp (P=0.0032) than did patients with the CC genotype. The longer Pdisp in the subjects with the CG + GG genotype was also found in the control group (P=0.0016). These findings support that IL-6 -634C/G polymorphism is associated with Pdisp and AF, suggesting an active implication of inflammation in the atrial electrophysiological remodeling predisposing to AF.