Impact of atrial fibrillation/flutter on the in-hospital mortality of ischemic stroke patients

Outcome of Pulmonary Embolism with and without Ischemic Stroke

Background: Ischemic stroke is the second, and pulmonary embolism (PE) is the third most common cardiovascular cause of death after myocardial infarction. Data regarding risk factors for ischemic stroke in patients with acute PE are limited. Methods: Patients were selected by screening the German nationwide in-patient sample for PE (ICD-code I26) and were stratified by ischemic stroke (ICD code I63) and compared. Results: The nationwide in-patient sample comprised 346,586 hospitalized PE patients (53.3% females) in Germany from 2011 to 2014; among these, 6704 (1.9%) patients had additionally an ischemic stroke. PE patients with ischemic stroke had a higher in-hospital mortality rate than those without (28.9% vs. 14.5%, p < 0.001). Ischemic stroke was independently associated with in-hospital death (OR 2.424, 95%CI 2.278-2.579, p < 0.001). Deep venous thrombosis and/or thrombophlebitis (DVT) combined with heart septal defect (OR 24.714 [95%CI 20.693-29.517], p < 0.001) as well as atrial fibrillation/flutter (OR 2.060 [95%CI 1.943-2.183], p < 0.001) were independent risk factors for stroke in PE patients. Systemic thrombolysis was associated with a better survival in PE patients with ischemic thrombolysis who underwent cardio-pulmonary resuscitation (CPR, OR 0.55 [95%CI 0.36-0.84], p = 0.006). Conclusions: Ischemic stroke did negatively affect the survival of PE. Combination of DVT and heart septal defect and atrial fibrillation/flutter were strong and independent risk factors for ischemic stroke in PE patients. In PE patients with ischemic stroke, who had to underwent CPR, systemic thrombolysis was associated with improved survival.

Ischemic stroke subtypes: risk factors, treatments, and 1-month prognosis - The Lille, France Stroke Registry

OBJECTIVES

First, this registry-based study aimed to comprehensively analyze patients' medical histories and treatments based on ischemic strokes' etiology. We focused on the management of atrial fibrillation among patients diagnosed with cardioembolic stroke. Then, our objective was to identify prognostic factors associated with 28-day mortality.

MATERIALS AND METHODS

All ischemic strokes occurring in adults between 2014 and 2021 in Lille, France, were categorized using the TOAST classification. Comparative analyses of patients' medical characteristics were conducted across subtypes. Survival rates within 28 days post-stroke were assessed, and factors influencing mortality were identified using a multivariate Cox model.

RESULTS

1912 ischemic strokes were recorded, due to cardioembolism (36%), large-artery atherosclerosis (9%), small-artery occlusion (9%), other determined causes (6%), or undetermined causes (39%). The median NIHSS score after cardioembolic stroke (6, IQR: 3-13) was twice that after small-artery occlusion (3, IQR: 2-5). Among patients with cardioembolic stroke, 26% were diagnosed post-admission with atrial fibrillation. For the 42% diagnosed pre-admission, only 54% had prior prescriptions for oral anticoagulants. Reperfusion therapies were administered in 21% of cases, with significant variations across subtypes. Mortality rates were higher after cardioembolic strokes (17%) than after small-artery occlusions (3%). Prognostic factors included etiology, high NIHSS score, atrial fibrillation, and previous heparin prescription.

CONCLUSIONS

While atrial fibrillation was underdiagnosed and undertreated, patients with cardioembolic stroke exhibited high severity and elevated mortality rates. Etiology emerged as an independent predictor of early mortality, regardless of NIHSS score upon admission. These findings underscore the importance of targeted prevention to improve patient outcomes after ischemic stroke.

Atrial fibrillation and mortality after ischemic stroke: An observational study using an insurance claim database

OBJECTIVES

In this study, we aimed to examine the association between atrial fibrillation and mortality after ischemic stroke and evaluate the use of anticoagulation therapy for atrial fibrillation before stroke onset in patients who experienced stroke.

METHODS

In this retrospective observational study, we used a combined database of medical and long-term care insurance claims data from one prefecture in Japan. The data of 25,352 patients aged ≥ 65 years who were hospitalized in acute care hospitals with a diagnosis of ischemic stroke between April 2012 and March 2015 were extracted. Cox proportional hazard modeling, with adjustment for age, sex, comorbidities, and long-term care dependency level (based on the activities of daily living), was performed to evaluate the relationship between mortality and atrial fibrillation.

RESULTS

The prevalence of atrial fibrillation was 21.8% in the study population. A significant association was noted between mortality and atrial fibrillation (adjusted hazard ratio: 1.28, 95% confidence interval: 1.16-1.41, p < 0.001). Anticoagulant drugs were used in 32.2% of the patients with atrial fibrillation.

CONCLUSIONS

These results indicate that atrial fibrillation is associated with mortality after stroke; however, the use of anticoagulation therapy for atrial fibrillation is unsatisfactory. Efforts to improve the use of atrial fibrillation therapy are required in Japan.

Ischemic Stroke and Systemic Embolism Among One-and-Done Direct Oral Anticoagulant Users with Non-valvular Atrial Fibrillation

INTRODUCTION

Direct oral anticoagulants (DOACs) are essential in ischemic stroke/systemic embolism (SE) prevention among patients with nonvalvular atrial fibrillation (NVAF). This study compared the risk of ischemic stroke/SE among patients with NVAF who discontinued DOACs following the first fill ("one-and-done") relative to patients who continued DOACs beyond the first fill ("continuers").

METHODS

De-identified data from Symphony Health, an ICON plc Company, PatientSource®, April 1, 2017 to October 31, 2020, were used to identify adults with NVAF initiated on DOACs (index date). Patients with only one DOAC claim during the 90-day landmark period starting on the index date were classified as one-and-done and the remaining as continuers. Inverse probability of treatment weighting was used to balance baseline characteristics in the cohorts. Time from the landmark period end to the first ischemic stroke/SE event or, among those without the event, to clinical activity or data end was compared between balanced cohorts using survival analysis.

RESULTS

Of patients initiating DOACs, 23.6% were classified as one-and-done users. After weighting was performed, 241,159 and 238,889 patients comprised the one-and-done and continuer cohorts, respectively. At 12 months of follow-up, the probability of ischemic stroke/SE was 1.44% in the one-and-done cohort and 1.00% in the continuer cohort [hazard ratio (95% confidence interval) 1.44 (1.34-1.54); p < 0.0001]. Results at earlier and later time points and in a sensitivity analysis with a 75-day landmark period were similar.

CONCLUSION

A substantial proportion of patients were one-and-done DOAC users, which was associated with significantly higher risk of ischemic stroke/SE events. There is an unmet need to improve access and encourage continuous use of DOACs among patients with NVAF so that severe and fatal complications may be mitigated.

Air pollution impacts on in-hospital case-fatality rate of ischemic stroke patients

BACKGROUND

A growing body of evidence suggests that air pollution exposure is associated with an increased risk for cardiovascular diseases. Data regarding the impact of long-term air pollution exposure on ischemic stroke mortality are sparse.

METHODS

The German nationwide inpatient sample was used to analyse all cases of hospitalized patients with ischemic stroke in Germany 2015-2019, which were stratified according to their residency. Data of the German Federal Environmental Agency regarding average values of air pollutants were assessed from 2015 to 2019 at district-level. Data were combined and the impact of different air pollution parameters on in-hospital case-fatality was analyzed.

RESULTS

Overall, 1,505,496 hospitalizations of patients with ischemic stroke (47.7% females; 67.4 % ≥70 years old) were counted in Germany 2015-2019, of whom 8.2 % died during hospitalization. When comparing patients with residency in federal districts with high vs. low long-term air pollution, enhanced levels of benzene (OR 1.082 [95%CI 1.034-1.132],P = 0.001), ozone (O_3, OR 1.123 [95%CI 1.070-1.178],P < 0.001), nitric oxide (NO, OR 1.076 [95%CI 1.027-1.127],P = 0.002) and PM_2.5 fine particulate matter concentrations (OR 1.126 [95%CI 1.074-1.180],P < 0.001) were significantly associated with increased case-fatality independent from age, sex, cardiovascular risk-factors, comorbidities, and revascularization treatments. Conversely, enhanced carbon monoxide, nitrogen dioxide, PM_10, and sulphur dioxide (SO₂) concentrations were not significantly associated with stroke mortality. However, SO_2-concentrations were significantly associated with stroke-case-fatality rate of >8 % independent of residence area-type and area use (OR 1.518 [95%CI 1.012-2.278],P = 0.044).

CONCLUSION

Elevated long-term air pollution levels in residential areas in Germany, notably of benzene, O₃, NO, SO_2, and PM_2.5, were associated with increased stroke mortality of patients.

RESEARCH IN CONTEXT

Evidence before this study: Besides typical, established risk factors, increasing evidence suggests that air pollution is an important and growing risk factor for stroke events, estimated to be responsible for approximately 14 % of all stroke-associated deaths. However, real-world data regarding the impact of long-term exposure to air pollution on stroke mortality are sparse. Added value of this study: The present study demonstrates that the long-term exposure to the air pollutants benzene, O₃, NO, SO₂ and PM_2.5 are independently associated with increased case-fatality of hospitalized patients with ischemic stroke in Germany. Implications of all the available evidence: The results of our study support the urgent need to reduce the exposure to air pollution by tightening emission controls to reduce the stroke burden and stroke mortality.

Excessive Supraventricular Ectopic Activity and the Risk of Atrial Fibrillation and Stroke: A Systematic Review and Meta-Analysis

BACKGROUND

Excessive supraventricular ectopic activity (ESVEA) is correlated with the development of atrial fibrillation (AF) and is frequently observed in ischemic stroke patients. This meta-analysis aims to summarize the evidence on the association between ESVEA and the risk of AF and stroke.

METHODS

PubMed and Embase databases were systematically searched to identify all publications providing relevant data from inception to 23 August 2022. Hazard ratio (HR) and 95% confidence interval (CI) were pooled using fixed-effect or random-effect models.

RESULTS

We included 23,272 participants from 20 studies. Pooled results showed that ESVEA was associated with an increased risk of AF in the general population (HR: 2.57; 95% CI 2.16-3.05), increased risk of AF in ischemic stroke patients (HR: 2.91; 95% CI 1.80-4.69), new-onset ischemic stroke (HR: 1.91; 95% CI 1.30-2.79), and all-cause mortality (HR: 1.41; 95% CI 1.24-1.59). Pooled analysis indicated that ESVEA was not associated with recurrent ischemic stroke/transient ischemic attack (TIA) (HR: 1.24; 95% CI 0.91-1.67).

CONCLUSIONS

ESVEA is associated with AF, new-onset ischemic stroke, and all-cause mortality.

Clinical scoring model based on age, NIHSS, and stroke-history predicts outcome 3 months after acute ischemic stroke

Background

The clinical nomogram is a popular decision-making tool that can be used to predict patient outcomes, bringing benefits to clinicians and patients in clinical decision-making. This study established a simple and effective clinical prediction model to predict the 3-month prognosis of acute ischemic stroke (AIS), and based on the predicted results, improved clinical decision-making and improved patient outcomes.

Methods

From 18 December 2021 to 8 January 2022, a total of 146 hospitalized patients with AIS confirmed by brain MR were collected, of which 132 eligible participants constituted a prospective study cohort. The least absolute shrinkage and selection operator (LASSO) regression was applied to a nomogram model development dataset to select features associated with poor prognosis in AIS for inclusion in the logistic regression of our risk scoring system. On this basis, the nomogram was drawn, evaluated for discriminative power, calibration, and clinical benefit, and validated internally by bootstrap. Finally, the optimal cutoff point for each independent risk factor and nomogram was calculated using the Youden index.

Results

A total of 132 patients were included in this study, including 85 men and 47 women. Good outcome was found in 94 (71.212%) patients and bad outcome in 38 (28.788%) patients during the follow-up period. A total of eight (6.061%) deaths were reported over this period, of whom five (3.788%) died during hospitalization. Five factors affecting the 3-month prognosis of AIS were screened by LASSO regression, namely, age, hospital stay, previous stroke, atrial fibrillation, and NIHSS. Further multivariate logistic regression revealed three independent risk factors affecting patient outcomes, namely, age, previous stroke, and NIHSS. The area under the curve of the nomogram was 0.880, and the 95% confidence interval was 0.818–0.943, suggesting that the nomogram model has good discriminative power. The p-value for the calibration curve is 0.925, indicating that the nomogram model is well-calibrated. According to the decision curve analysis results, when the threshold probability is >0.01, the net benefit obtained by the nomogram is the largest. The concordance index for 1,000 bootstrapping calculations is 0.869. The age cutoff for predicting poor patient outcomes using the Youden index was 76.5 years (specificity 0.777 and sensitivity 0.684), the cutoff for the NIHSS was 7.5 (specificity 0.936, sensitivity 0.421), and the cutoff for total nomogram score was 68.8 (sensitivity 81.6% and specificity 79.8%).

Conclusion

The nomogram model established in this study had good discrimination, calibration, and clinical benefits. A nomogram composed of age, previous stroke, and NIHSS might predict the prognosis of stroke after AIS. It might intuitively and individually predict the risk of poor prognosis in 3 months of AIS and provide a reference basis for screening the treatment plan of patients.

Predictors of in-hospital and 90-day post-discharge stroke mortality in Lusaka, Zambia

BACKGROUND

Factors associated with stroke mortality are understudied in sub-Saharan Africa but have implications for designing interventions that improve stroke outcomes. We investigated predictors of in-hospital and 90-day post-discharge stroke mortality in Lusaka, Zambia.

METHODS

Data from consecutive adults admitted with stroke at University Teaching Hospital in Lusaka, Zambia between October 2018 and March 2019 were retrospectively reviewed for clinical in-hospital outcomes. Vital status at 90-days post-discharge was determined through phone calls. Factors associated with stroke mortality were included in multivariable logistic regression models utilizing multiple imputation analysis to determine independent predictors of in-hospital and 90-days post-discharge mortality.

RESULTS

In-hospital mortality was 24%, and 90-day post-discharge mortality was 22% among those who survived hospitalization. Hemorrhagic and unknown strokes, ICU care, seizures, and aspiration pneumonia were significantly associated with in-hospital mortality. Among these, hemorrhagic stroke (OR 2.88, 95% CI 1.27-6.53, p = 0.01) and seizures (OR 29.5, 95% CI 2.14-406, p = 0.01) remained independent predictors of in-hospital mortality in multivariable analyses. Ninety-day post-discharge mortality was significantly associated with older age, previous stroke, atrial fibrillation, and aspiration pneumonia, but only older age (OR 1.04, 95% CI 1.01-1.06, p = 0.007) and aspiration pneumonia (OR 3.93, 95% CI 1.30-11.88, p = 0.02) remained independently associated with 90-day mortality in multivariable analyses.

CONCLUSION

This Zambian stroke cohort had high in-hospital and 90-day post-discharge mortality that were associated with several in-hospital complications. Our data indicate the need for improvement in both acute stroke care and post-stroke systems of care to improve stroke outcomes in Zambia.

Population scale latent space cohort matching for the improved use and exploration of observational trial data

A significant amount of clinical research is observational by nature and derived from medical records, clinical trials, and large-scale registries. While there is no substitute for randomized, controlled experimentation, such experiments or trials are often costly, time consuming, and even ethically or practically impossible to execute. Combining classical regression and structural equation modeling with matching techniques can leverage the value of observational data. Nevertheless, identifying variables of greatest interest in high-dimensional data is frequently challenging, even with application of classical dimensionality reduction and/or propensity scoring techniques. Here, we demonstrate that projecting high-dimensional medical data onto a lower-dimensional manifold using deep autoencoders and post-hoc generation of treatment/control cohorts based on proximity in the lower-dimensional space results in better matching of confounding variables compared to classical propensity score matching (PSM) in the original high-dimensional space (P<0.0001) and performs similarly to PSM models constructed by experts with prior knowledge of the underlying pathology when evaluated on predicting risk ratios from real-world clinical data. Thus, in cases when the underlying problem is poorly understood and the data is high-dimensional in nature, matching in the autoencoder latent space might be of particular benefit.

Atrial Fibrillation Is Not an Independent Determinant of Mortality Among Critically Ill Acute Ischemic Stroke Patients: A Propensity Score-Matched Analysis From the MIMIC-IV Database

Background/Objective

This study was conducted to investigate the clinical characteristics and outcomes of patients with acute ischemic stroke and atrial fibrillation (AF) in intensive care units (ICUs).

Methods

In the Medical Information Mart for Intensive Care IV database, 1,662 patients with acute ischemic stroke were identified from 2008 to 2019. Of the 1,662 patients, 653 had AF. The clinical characteristics and outcomes of patients with and without AF were compared using propensity score matching (PSM). Furthermore, univariate and multivariate Cox regression analyzes were performed.

Results

Of the 1,662 patients, 39.2% had AF. The prevalence of AF in these patients increased in a stepwise manner with advanced age. Patients with AF were older and had higher Charlson Comorbidity Index, CHA2DS2-VASc Score, HAS-BLED score, and Acute Physiology Score III than those without AF. After PSM, 1,152 patients remained, comprising 576 matched pairs in both groups. In multivariate analysis, AF was not associated with higher ICU mortality [hazard ratio (HR), 0.95; 95% confidence interval (CI), 0.64–1.42] or in-hospital mortality (HR, 1.08; 95% CI, 0.79–1.47). In Kaplan–Meier analysis, no difference in ICU or in-hospital mortality was observed between patients with and without AF.

Conclusions

AF could be associated with poor clinical characteristics and outcomes; however, it does not remain an independent short-term predictor of ICU and in-hospital mortality among patients with acute ischemic stroke after PSM with multivariate analysis.

KLF15 Loss-of-Function Mutation Underlying Atrial Fibrillation as well as Ventricular Arrhythmias and Cardiomyopathy

Atrial fibrillation (AF) represents the most common type of clinical cardiac arrhythmia and substantially increases the risks of cerebral stroke, heart failure and death. Accumulating evidence has convincingly demonstrated the strong genetic basis of AF, and an increasing number of pathogenic variations in over 50 genes have been causally linked to AF. Nevertheless, AF is of pronounced genetic heterogeneity, and the genetic determinants underpinning AF in most patients remain obscure. In the current investigation, a Chinese pedigree with AF as well as ventricular arrhythmias and hypertrophic cardiomyopathy was recruited. Whole exome sequencing and bioinformatic analysis of the available family members were conducted, and a novel heterozygous variation in the KLF15 gene (encoding Krüppel-like factor 15, a transcription factor critical for cardiac electrophysiology and structural remodeling), NM_014079.4: c.685A>T; p.(Lys229*), was identified. The variation was verified by Sanger sequencing and segregated with autosomal dominant AF in the family with complete penetrance. The variation was absent from 300 unrelated healthy subjects used as controls. In functional assays using a dual-luciferase assay system, mutant KLF15 showed neither transcriptional activation of the KChIP2 promoter nor transcriptional inhibition of the CTGF promoter, alone or in the presence of TGFB1, a key player in the pathogenesis of arrhythmias and cardiomyopathies. The findings indicate KLF15 as a new causative gene responsible for AF as well as ventricular arrhythmias and hypertrophic cardiomyopathy, and they provide novel insight into the molecular mechanisms underlying cardiac arrhythmias and hypertrophic cardiomyopathy.

Connexin45 (GJC1) loss-of-function mutation contributes to familial atrial fibrillation and conduction disease

BACKGROUND

Atrial fibrillation (AF) represents the most common clinical cardiac arrhythmia and substantially increases the risk of cerebral stroke, heart failure, and death. Although causative genes for AF have been identified, the genetic determinants for AF remain largely unclear.

OBJECTIVE

This study aimed to investigate the molecular basis of AF in a Chinese kindred.

METHODS

A 4-generation family with autosomal-dominant AF and other arrhythmias (atrioventricular block, sinus bradycardia, and premature ventricular contractions) was recruited. Genome-wide scan with microsatellite markers and linkage analysis as well as whole-exome sequencing analysis were performed. Electrophysiological characteristics and subcellular localization of the AF-linked mutant were analyzed using dual whole-cell patch clamps and confocal microscopy, respectively.

RESULTS

A novel genetic locus for AF was mapped to chromosome 17q21.3, a 3.23-cM interval between markers D17S951 and D17S931, with a maximum 2-point logarithm of odds score of 4.2144 at marker D17S1868. Sequencing analysis revealed a heterozygous mutation in the mapping region, NM_005497.4:c.703A>T;p.(M235L), in the GJC1 gene encoding connexin45 (Cx45). The mutation cosegregated with AF in the family and was absent in 632 control individuals. The mutation decreased the coupling conductance in cell pairs (M235L/M235L, M235L/Cx45, M235L/Cx43, and M235L/Cx40), likely because of impaired subcellular localization.

CONCLUSION

This study defines a novel genetic locus for AF on chromosome 17q21.3 and reveals a loss-of-function mutation in GJC1 (Cx45) contributing to AF and other cardiac arrhythmias.

A New Therapeutic Framework for Atrial Fibrillation Drug Development

Atrial fibrillation (AF) is a highly prevalent cardiac arrhythmia and cause of significant morbidity and mortality. Its increasing prevalence in aging societies constitutes a growing challenge to global healthcare systems. Despite substantial unmet needs in AF prevention and treatment, drug developments hitherto have been challenging, and the current pharmaceutical pipeline is nearly empty. In this review, we argue that current drugs for AF are inadequate because of an oversimplified system for patient classification and the development of drugs that do not interdict underlying disease mechanisms. We posit that an improved understanding of AF molecular pathophysiology related to the continuous identification of novel disease-modifying drug targets and an increased appreciation of patient heterogeneity provide a new framework to personalize AF drug development. Together with recent innovations in diagnostics, remote rhythm monitoring, and big data capabilities, we anticipate that adoption of a new framework for patient subsegmentation based on pathophysiological, genetic, and molecular subsets will improve success rates of clinical trials and advance drugs that reduce the individual patient and public health burden of AF.