Stroke Severity and Outcomes in Patients With Newly Diagnosed Atrial Fibrillation

Brain lesion and echocardiogenic predictors of newly detected atrial fibrillation in acute ischemic stroke

OBJECTIVES

Atrial fibrillation (AF) is one of the notorious risk factors in acute ischemic stroke (AIS), and the use of anticoagulants has been shown to be effective in preventing ischemic stroke in AF patients. Therefore, identifying AF in AIS patients has become increasingly important. However, the impact of brain imaging and cardiac indices on the development of new AF after stroke remains unclear.

METHODS

A consecutive series of AIS patients who were admitted to the Ulsan University Hospital between January 2013 and December 2019 were identified. Patients with relevant ischemic brain lesions on MRI were included, and those without echocardiography data were excluded. We included and classified the AF patients who had the disease prior to or during hospitalization or met the criteria for cryptogenic stroke (CS). Differences in baseline characteristics, stroke risk factors, stroke severity, insular lesion, and echocardiographic data were investigated among each group.

RESULTS

A total of 850 patients were enrolled in the study, comprising 231 patients with AF detected after stroke (AFDAS), 287 patients with known AF (KAF), and 350 patients with CS. Compared with KAF, patients with AFDAS had a lower prevalence of underlying coronary heart disease and stroke history. They had greater right insular cortex lesions and lesser left atrial enlargement in unadjusted analysis. Following adjusted analysis, the involvement of the right insular cortex was found to be associated with the AFDAS patient group (odds ratio, 1.57). When compared to the CS group, AFDAS patients were older, experienced more severe initial strokes, and had similar rates of pre-stroke anticoagulation prescription. Additionally, they demonstrated a higher prevalence of both insular lesions, increased left atrium volume index, reduced ejection fraction, and elevated e/e' ratio. After adjustment, age, initial stroke severity, insular involvement, left atrium volume index, ejection fraction, and e/e' ratio were found to be significant.

CONCLUSIONS

These results suggest that the right insular cortex lesion on acute stroke may be a cause of AFDAS.

Characteristics and outcomes of atrial fibrillation detected before and after acute ischemic stroke

BACKGROUND

Atrial fibrillation (AF) can be known before the stroke (KAF) or be newly detected after stroke (AFDAS). It is unknown whether the outcome of stroke differs between KAF and AFDAS. We performed a propensity-matched analysis to investigate the outcome of patients with AFDAS and their counterparts with KAF.

METHODS

We analysed a consecutive series of patients enrolled into the EIDASAF study, a single centre, retrospective study of ischemic stroke patients with a diagnosis of AF before or after the event who had been admitted to the Hyperacute Stroke Unit of Imperial College Healthcare NHS Trust between 2010 and 2017.

RESULTS

Overall, our cohort included 959 patients with AF and acute ischemic stroke. After propensity score matching, 547 patients were matched (404 KAF group and 143 AFDAS group). The rates of in hospital death and of haemorrhagic transformation were significantly higher in KAF patients compared to AFDAS patients. Logistic regression analysis did not reveal a statistically significant influence of AF subtypes on the outcome of death. However, in logistic regression analysis KAF was associated with increased probability of haemorrhagic transformation (OR 9.64; CI 1.29-71.68, p = 0.022) after the index event.

CONCLUSION

KAF is associated with an increased risk of haemorrhagic transformation but not of death when compared to AFDAS.

Prevalence, risk factors and prognostic value of atrial fibrillation detected after stroke after haemorrhagic versus ischaemic stroke

BACKGROUND AND OBJECTIVES

Prior evidence suggests that atrial fibrillation detected after stroke (AFDAS) is distinct from known atrial fibrillation (KAF), with particular clinical characteristics and impacts on outcomes in ischaemic stroke. However, the results remained inconsistent in ischaemic stroke, and the role of AFDAS in haemorrhagic stroke remains unclear. Therefore, we aimed to estimate the prevalence, risk factors and prognostic value of AFDAS in haemorrhagic stroke in comparison with ischaemic stroke.

METHODS

This was a multicentre cohort study. Patients who had an ischaemic and haemorrhagic stroke hospitalised in the Chinese Stroke Center Alliance hospitals were enrolled and classified as AFDAS, KAF or sinus rhythm (SR) based on heart rhythm. Univariate and multivariate logistic regression analyses were used to assess the prevalence, characteristics, risk factors and outcomes of AFDAS, KAF and SR in different stroke subtypes.

RESULTS

A total of 913 163 patients, including 818 799 with ischaemic stroke, 83 450 with intracerebral haemorrhage (ICH) and 10 914 with subarachnoid haemorrhage (SAH), were enrolled. AFDAS was the most common in ischaemic stroke. There were differences in the risk factor profile between stroke subtypes; older age is a common independent risk factor shared by ischaemic stroke (OR 1.06, 95% CI 1.06 to 1.06), ICH (OR 1.08, 95% CI 1.07 to 1.09) and SAH (OR 1.07, 95% CI 1.05 to 1.10). Similar to KAF, AFDAS was associated with an increased risk of in-hospital mortality compared with SR in both ischaemic stroke (OR 2.23, 95% CI 1.94 to 2.56) and ICH (OR 2.84, 95% CI 1.84 to 4.38).

DISCUSSION

There are differences in the prevalence, characteristics and risk factors for AFDAS and KAF in different stroke subtypes. AFDAS was associated with an increased risk of mortality compared with SR in both ischaemic stroke and ICH. Rhythm monitoring and risk factor modification after both ischaemic and haemorrhagic stroke are essential in clinical practice. More emphasis and appropriate treatment should be given to AFDAS.

From Admission to Discharge: Predicting National Institutes of Health Stroke Scale Progression in Stroke Patients Using Biomarkers and Explainable Machine Learning

As a result of social progress and improved living conditions, which have contributed to a prolonged life expectancy, the prevalence of strokes has increased and has become a significant phenomenon. Despite the available stroke treatment options, patients frequently suffer from significant disability after a stroke. Initial stroke severity is a significant predictor of functional dependence and mortality following an acute stroke. The current study aims to collect and analyze data from the hyperacute and acute phases of stroke, as well as from the medical history of the patients, in order to develop an explainable machine learning model for predicting stroke-related neurological deficits at discharge, as measured by the National Institutes of Health Stroke Scale (NIHSS). More specifically, we approached the data as a binary task problem: improvement of NIHSS progression vs. worsening of NIHSS progression at discharge, using baseline data within the first 72 h. For feature selection, a genetic algorithm was applied. Using various classifiers, we found that the best scores were achieved from the Random Forest (RF) classifier at the 15 most informative biomarkers and parameters for the binary task of the prediction of NIHSS score progression. RF achieved 91.13% accuracy, 91.13% recall, 90.89% precision, 91.00% f1-score, 8.87% FNrate and 4.59% FPrate. Those biomarkers are: age, gender, NIHSS upon admission, intubation, history of hypertension and smoking, the initial diagnosis of hypertension, diabetes, dyslipidemia and atrial fibrillation, high-density lipoprotein (HDL) levels, stroke localization, systolic blood pressure levels, as well as erythrocyte sedimentation rate (ESR) levels upon admission and the onset of respiratory infection. The SHapley Additive exPlanations (SHAP) model interpreted the impact of the selected features on the model output. Our findings suggest that the aforementioned variables may play a significant role in determining stroke patients' NIHSS progression from the time of admission until their discharge.

Association between Rapid Ventricular Response and Stroke Outcomes in Atrial Fibrillation-Related Cardiac Embolic Stroke

INTRODUCTION

Patients with atrial fibrillation-related stroke (AF-stroke) are prone to developing rapid ventricular response (RVR). We investigated whether RVR is associated with initial stroke severity, early neurological deterioration (END) and poor outcome at 3 months.

METHODS

We reviewed patients who had AF-stroke between January 2017 and March 2022. RVR was defined as having heart rate >100 beats per minute on initial electrocardiogram. Neurological deficit was evaluated with National Institutes of Health Stroke Scale (NIHSS) score at admission. END was defined as increase of ≥2 in total NIHSS score or ≥1 in motor NIHSS score within first 72 h. Functional outcome was score on modified Rankin Scale at 3 months. Mediation analysis was performed to examine potential causal chain in which initial stroke severity may mediate relationship between RVR and functional outcome.

RESULTS

We studied 568 AF-stroke patients, among whom 86 (15.1%) had RVR. Patients with RVR had higher initial NIHSS score (p < 0.001) and poor outcome at 3 months (p = 0.004) than those without RVR. The presence of RVR [adjusted odds ratio (aOR) = 2.13; p = 0.013] was associated with initial stroke severity, but not with END and functional outcome. Otherwise, initial stroke severity [aOR = 1.27; p = <0.001] was significantly associated with functional outcome. Initial stroke severity as a mediator explained 58% of relationship between RVR and poor outcome at 3 months.

CONCLUSION

In patients with AF-stroke, RVR was independently associated with initial stroke severity but not with END and functional outcome. Initial stroke severity mediated considerable proportion of association between RVR and functional outcome.

Sinus rhythm restoration and improved outcomes in patients with acute ischemic stroke and in-hospital paroxysmal atrial fibrillation

AIMS

It is unclear whether early cardiac rhythm control is beneficial in patients with acute ischemic stroke and paroxysmal atrial fibrillation (PAF). We sought to investigate whether PAF self-termination and in-hospital sinus rhythm (SR) restoration is associated with improved outcome in ischemic stroke patients with PAF, compared to those with sustained atrial fibrillation (AF).

METHODS

Consecutive patients with first-ever acute stroke and confirmed PAF during hospitalization were followed for up to 10 years after the index stroke or until death. We investigated the association of in-hospital self-terminated PAF and PAF conversion to SR compared to sustained AF with 10-year all-cause mortality, stroke recurrence, and major adverse cardiovascular events (MACE). Cox regression analysis was performed to identify independent predictors of each outcome.

RESULTS

Among 297 ischemic stroke patients with in-hospital PAF detection, PAF was self-terminated in 87 (29.3%) patients, while 143 (48.1%) patients received antiarrhythmic medication in order to achieve PAF conversion to SR. During a median (Interquartile range, IQR) period of 28 (4-68) months, among patients with self-terminated PAF there were 13.5 deaths, 3.6 stroke recurrences, and 5.3 MACE per 100 patient-year while in patients who underwent medical PAF conversion there were 11.7 deaths, 4.6 stroke recurrences, and 5.8 MACE per 100 patient-year. Patients with sustained AF experienced 23.8 deaths, 8.7 stroke recurrences, and 13.9 MACE per 100 patient-years. In multivariable analysis, compared to patients with sustained AF, PAF self-termination was associated with significantly lower 10 years-risk of death (adjusted hazards ratio (adjHR): HR: 0.63, 95% Confidence interval: 0.40-0.96), stroke recurrence (adjHR: HR: 0.41, 95% CI: 0.19-0.91), and MACE (adjHR: 0.43, 95% CI: 0.23-0.81), while PAF medical conversion to SR was associated with lower 10 years-risk of death (adjHR: 0.65, 95% CI: 0.44-0.97) and MACE (adjHR: 0.56, 95% CI: 0.33-0.95).

DISCUSSION

This study showed that in-hospital PAF self-termination was associated with lower risk of 10-year mortality, stroke recurrence, and MACE, potentially attributed to the lower burden of AF, whereas in-hospital PAF conversion to SR was associated with lower risk of 10-year mortality and MACE.

CONCLUSION

Early restoration of sinus rhythm is associated with improved survival and MACE in patients with acute ischemic stroke and PAF.

Differences between Atrial Fibrillation Detected before and after Stroke and TIA: A Systematic Review and Meta-Analysis

BACKGROUND

Preliminary evidence suggests that patients with atrial fibrillation (AF) detected after stroke (AFDAS) may have a lower prevalence of cardiovascular comorbidities and lower risk of stroke recurrence than AF known before stroke (KAF).

OBJECTIVE

We performed a systematic search and meta-analysis to compare the characteristics of AFDAS and KAF.

METHODS

We searched PubMed, Scopus, and EMBASE for articles reporting differences between AFDAS and KAF until June 30, 2021. We performed random- or fixed-effects meta-analyses to evaluate differences between AFDAS and KAF in demographic factors, vascular risk factors, prevalent vascular comorbidities, structural heart disease, stroke severity, insular cortex involvement, stroke recurrence, and death.

RESULTS

In 21 studies including 22,566 patients with ischemic stroke or transient ischemic attack, the prevalence of coronary artery disease, congestive heart failure, prior myocardial infarction, and a history of cerebrovascular events was significantly lower in AFDAS than KAF. Left atrial size was smaller, and left ventricular ejection fraction was higher in AFDAS than KAF. The risk of recurrent stroke was 26% lower in AFDAS than in KAF. There were no differences in age, sex, stroke severity, or death rates between AFDAS and KAF. There were not enough studies to report differences in insular cortex involvement between AF types.

CONCLUSIONS

We found significant differences in the prevalence of vascular comorbidities, structural heart disease, and stroke recurrence rates between AFDAS and KAF, suggesting that they constitute different clinical entities within the AF spectrum. PROSPERO registration number is CRD42020202622.