Paroxysmal atrial fibrillation detection in patients with acute ischemic stroke through prolonged Holter: prospective study

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.

Role of the score for the targeting of atrial fibrillation (STAF) combined with D-dimer in screening ischemic stroke patients with atrial fibrillation

Background

We aim to explore the effect of the score for the targeting of atrial fibrillation (STAF) combined with the serum D-dimer (DD) level in screening acute ischemic stroke patients with atrial fibrillation (AF).

Methods

This study is a retrospective case observation study. This study consecutively selected patients with acute ischemic stroke who were hospitalized in the Department of Neurology at Zhuhai Hospital Affiliated with Jinan University from February 2019 to February 2021. Venous blood was drawn from all patients within 24 hours of hospitalization for DD detection. In accordance with the medical records, the patients were classified into an AF group and a non-AF group and were scored according to the STAF standard. A combined test method was used to estimate the diagnostic screening value of the STAF combined with the DD value for acute ischemic stroke patients with AF.

The efficacy of detecting arrhythmia is higher with 7-day continuous electrocardiographic patch monitoring than with 24-h Holter monitoring

Background

Detecting high-risk arrhythmia is important in diagnosing patients with palpitations. We compared the diagnostic accuracies of 7-day patch-type electrocardiographic (ECG) monitoring and 24-h Holter monitoring for detecting significant arrhythmias in patients with palpitations.

Methods

This was a single-center prospective trial with 58 participants who presented with palpitations, chest pain or syncope. Outcomes were defined as the detection of any one of six arrhythmias, including supraventricular tachycardia (SVT), atrial fibrillation or atrial flutter lasting more than 30 s, pauses of more than 3 s, high-degree atrioventricular block, ventricular tachycardia (VT) >3 beats, or polymorphic VT/ventricular fibrillation. The McNemar test for paired proportions was used to compare arrhythmia detection rates.

Results

The overall arrhythmia detection rate was higher with 7-day ECG patch monitoring than with 24-h Holter monitoring (34.5% vs. 19.0%, p = .008). Compared with the use of 24-h Holter monitors, the use of 7-day ECG patch monitors was associated with higher detection of SVT (29.3% vs. 13.8%, p = .042). No serious adverse skin reactions were reported among the ECG patch-monitored participants.

Conclusions

The results suggest that a 7-day patch-type continuous ECG monitor is more effective for the detection of supraventricular tachycardia than is a 24-h Holter monitor. However, the clinical significance of device detected arrhythmia should be consolidated.

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.

Seeking predictors for paroxysmal atrial fibrillation in stroke with an online clinical database

OBJECTIVE:

A considerable fraction of ischemic stroke cases remain cryptogenic and there is increasing data suggesting the role of missed paroxysmal atrial fibrillations (pAF) in at least a number of these cases. Since electrophysiological identification of pAFs can be challenging, there has been an accumulation of proposed predictors and biomarkers for pAFs. The predictive values of these is varying and sometimes conflicting among studies. Therefore, we aimed to verify a fraction of previously reported parameters for pAF detection by investigating an independent clinical sample.

METHODS:

Using a publicly available data downloaded from the MIMIC-3 intensive care unit database, we tested the predictive role of particular risk factors and biomarkers for pAF detection after ischemic stroke in 124 patients with ischemic stroke admitted within 24 hours of stroke onset.

RESULTS:

Our evaluation revealed a strong association of older age in women, as well as admission National Institutes of Health Stroke Scale (NIHSS) and discharge modified Rankin Scores (mRS) in both sexes for pAFs, in patients that were in sinus rhythm on admission. We also detected a trend for lower gender-adjusted hemoglobin in patients with pAF, although the difference was insignificant. On the other hand, we did not find any significant association of pAF detection with some other previously reported biomarkers: serum magnesium level, leukocyte count, neutrophil/lymphocyte ratio or left atrial dilatation.

CONCLUSION:

Even though our analysis did not reveal a strong and specific biomarker to predict pAFs after stroke, it identified key risk factors. It may be necessary to consider the possibility of pAFs and perform rigorous evaluation to prevent further events of embolic stroke in female patients older than 75 years, with more severe neurological deficits on admission, higher disability on discharge and also with relatively lower hemoglobin level. This first study from Turkey using clinical data from the MIMIC-3 database also demonstrates the value of publicized clinical data for confirmatory studies on various medical fields across the World.