The value of STAF (Score for the Targeting of Atrial Fibrillation) in Patients with Cryptogenic Embolic Stroke

Risk scores for prediction of paroxysmal atrial fibrillation after acute ischemic stroke or transient ischemic attack: A systematic review and meta-analysis

Introduction

Detection of paroxysmal atrial fibrillation (PAF) is crucial for secondary prevention in patients with recent strokes of unknown etiology. This systematic review and meta-analysis assess the predictive power of available risk scores for detecting new PAF after acute ischemic stroke (AIS).

Methods

PubMed, Embase, Scopus, and Web of Science databases were searched until September 2023 to identify relevant studies. A bivariate random effects meta-analysis model pooled data on sensitivity, specificity, and area under the curve (AUC) for each score. The QUADAS-2 tool was used for the quality assessment.

Results

Eventually, 21 studies with 18 original risk scores were identified. Age, left atrial enlargement, and NIHSS score were the most common predictive factors, respectively. Seven risk scores were meta-analyzed, with iPAB showing the highest pooled sensitivity and AUC (sensitivity: 89.4%, specificity: 74.2%, AUC: 0.83), and HAVOC having the highest pooled specificity (sensitivity: 46.3%, specificity: 82.0%, AUC: 0.82). Altogether, seven risk scores displayed good discriminatory power (AUC ≥0.80) with four of them (HAVOC, iPAB, Fujii, and MVP scores) being externally validated.

Conclusion

Available risk scores demonstrate moderate to good predictive accuracy and can help identify patients who would benefit from extended cardiac monitoring after AIS. External validation is essential before widespread clinical adoption.

External Validation of SAFE Score to Predict Atrial Fibrillation Diagnosis after Ischemic Stroke: A Retrospective Multicenter Study

Introduction

The screening for atrial fibrillation (AF) scale (SAFE score) was recently developed to provide a prediction of the diagnosis of AF after an ischemic stroke. It includes 7 items: age ≥ 65 years, bronchopathy, thyroid disease, cortical location of stroke, intracranial large vessel occlusion, NT-ProBNP ≥250 pg/mL, and left atrial enlargement. In the internal validation, a good performance was obtained, with an AUC = 0.88 (95% CI 0.84-0.91) and sensitivity and specificity of 83% and 80%, respectively, for scores ≥ 5. The aim of this study is the external validation of the SAFE score in a multicenter cohort.

Methods

A retrospective multicenter study, including consecutive patients with ischemic stroke or transient ischemic attack between 2020 and 2022 with at least 24 hours of cardiac monitoring. Patients with previous AF or AF diagnosed on admission ECG were excluded.

Results

Overall, 395 patients were recruited for analysis. The SAFE score obtained an AUC = 0.822 (95% CI 0.778-0.866) with a sensitivity of 87.2%, a specificity of 65.4%, a positive predictive value of 44.1%, and a negative predictive value of 94.3% for a SAFE score ≥ 5, with no significant gender differences. Calibration analysis in the external cohort showed an absence of significant differences between the observed values and those predicted by the model (Hosmer-Lemeshow's test 0.089).

Conclusions

The SAFE score showed adequate discriminative ability and calibration, so its external validation is justified. Further validations in other external cohorts or specific subpopulations of stroke patients might be required.

Risk Stratification Tools to Guide a Personalized Approach for Cardiac Monitoring in Embolic Stroke of Undetermined Source

Current recommendations support a personalized sequential approach for cardiac rhythm monitoring to detect atrial fibrillation after embolic stroke of undetermined source. Several risk stratification scores have been proposed to predict the likelihood of atrial fibrillation after embolic stroke of undetermined source. This systematic review aimed to provide a comprehensive overview of the field by identifying risk scores proposed for this purpose, assessing their characteristics and the cohorts in which they were developed and validated, and scrutinizing their predictive performance. We identified 11 risk scores, of which 4 were externally validated. The most frequent variables included were echocardiographic markers and demographics. The areas under the curve ranged between 0.70 and 0.94. The 3 scores with the highest area under the curve were the Decryptoring (0.94 [95% CI, 0.88-1.00]), newly diagnosed atrial fibrillation (0.87 [95% CI, 0.79-0.94]), and AF-ESUS (Atrial Fibrillation in Embolic Stroke of Undetermined Source) (0.85 [95% CI, 0.80-0.87]), of which only the latter was externally validated. Risk stratification scores can guide a personalized approach for cardiac rhythm monitoring after embolic stroke of undetermined source.

Long-Term Cardiac Monitoring After Embolic Stroke of Undetermined Source: Search Longer, Look Harder

Embolic stroke of undetermined source (ESUS) represents a heterogeneous subgroup of patients with cryptogenic stroke, in which despite an extensive diagnostic workup the cause of stroke remains uncertain. Identifying covert atrial fibrillation among patients with ESUS remains challenging. The increasing use of cardiac implanted electronic devices (CIED), such as pacemakers, implantable defibrillators, and implantable loop recorders (ILR), has provided important information on the burden of subclinical atrial fibrillation. Accumulating evidence indicate that long-term continuous monitoring, especially in selected patients with ESUS, significantly increases the possibility of atrial fibrillation detection, suggesting it may be a cost-effective tool in secondary stroke prevention. This review summarizes available evidence related to the use of long-term cardiac monitoring and the use of implantable cardiac monitoring devices in patients with ESUS.