scholarly journals Predictors of Stroke Risk in Native Chinese with Nonrheumatic Atrial Fibrillation: Retrospective Investigation of Hospitalized Patients

2009 ◽  
Vol 32 (2) ◽  
pp. 76-81 ◽  
Author(s):  
Yihong Sun ◽  
Dayi Hu ◽  
Kuibao Li ◽  
Ziqiang Zhou
Keyword(s):  
Atrial Fibrillation ◽  
Stroke Risk ◽  
Hospitalized Patients ◽  
Retrospective Investigation

scholarly journals Trends in all-cause mortality of atrial fibrillation in hospitalized patients in Sweden between 1995–2008

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
A Sztaniszlav ◽  
A Magnuson ◽  
I L Bryngelsson ◽  
N Edvardsson ◽  
K Sztaniszlav ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Mortality Risk ◽  
Stroke Risk ◽  
Education Level ◽  
Hospitalized Patients ◽  
Control Population ◽  
High Morbidity ◽  
Significant Difference ◽  
All Cause Mortality ◽  
Over Time

Abstract Introduction Atrial fibrillation (AF) is the most common arrythmia. Both its incidence and prevalence increased significantly during the last decades. AF is associated with high morbidity and mortality. Purpose The aim of this study was to describe and evaluate the trends of all-cause mortality in patients first-ever hospitalized for AF, and the effect of age, sex, stroke risk, and education level on mortality over time. Methods In this observational retrospective cohort study, we enrolled the patients who were hospitalized primarily and for the first time because of AF between 1st January 1995 and 31st December 2004. In regard to the date of the index admission patients were divided into four cohorts and they were followed up to five years. Patients were compared with an age and sex matched control population. All data were collected from Swedish national registries. Kaplan-Meier plots and Cox regression with trend analysis were used for statistical evaluation. Results In total 64 489 AF patients (mean age 72±10.1 year) were included in this study. The control group comprised 116 893 individuals. 81.9% of the women and 58.5% of the men were older than 65 years of age. 65.5% of women and 58.5% of the men had a stroke risk of CHADS2-VA2Sc ≥2. We found a significantly decreasing trend of the relative risk for all-cause mortality in AF patients over time: trend HR: 0.94 (95% CI: 0.92–0.96, p<0.001) in women and trend HR: 0.91 (95% CI: 0.89–0.93 p<0.001) in men. The mortality trends between AF patients and their controls did not show significant difference: trend HR: 0.99 (95% CI: 0.96–1.02, p=0.59) in women and trend HR: 1.00 (95% CI: 0.97–1.03, p=0.98) in men. The subpopulation analysis showed that the mortality risk remained unchanged over the time in women aged 18–69 years (trend HR: 0.91 – 95% CI: 0.82–1.02, p=0.099), in patients with low stroke risk (trend HR: 1.08 – 95% CI: 0.92–1.26, p=0.36 in women and trend HR: 0.95 – 95% CI: 0.87–1.05, p=0.30 in men) and in patients with post-secondary level of education (trend HR: 0.93 – 95% CI 0.83–1.04, p=0.23 in women and trend HR: 1.04 – 95% CI: 0.96–1.12, p=0.32 in men). Conclusion The all-cause mortality risk of the AF hospitalized patients was higher compared to control population and had a decreasing tendency during the time of the study. However, this trend is not significantly different from the control population. We found unchanged mortality trend in younger patients, in those with lower stroke risk, and in patients with higher education level. FUNDunding Acknowledgement Type of funding sources: None.

Recurrent Stroke Risk in Pilots with Atrial Fibrillation

2020 ◽  
Vol 91 (4) ◽  
pp. 352-357
Author(s):  
Jessica Tedford ◽  
Valerie Skaggs ◽  
Ann Norris ◽  
Farhad Sahiar ◽  
Charles Mathers
Keyword(s):  
Atrial Fibrillation ◽  
General Population ◽  
Recurrent Events ◽  
Stroke Risk ◽  
Event Rate ◽  
Recurrent Stroke ◽  
Previous History ◽  
Recurrent Event ◽  
Recurrence Rates ◽  
Medical Certification

INTRODUCTION: Atrial fibrillation (AF) is one of the most common cardiac arrhythmias in the general population and is considered disqualifying aeromedically. This study is a unique examination of significant outcomes in aviators with previous history of both AF and stroke.METHODS: Pilots examined by the FAA between 2002 and 2012 who had had AF at some point during his or her medical history were reviewed, and those with an initial stroke or transient ischemic attack (TIA) during that time period were included in this study. All records were individually reviewed to determine stroke and AF history, medical certification history, and recurrent events. Variables collected included medical and behavior history, stroke type, gender, BMI, medication use, and any cardiovascular or neurological outcomes of interest. Major recurrent events included stroke, TIA, cerebrovascular accident, death, or other major events. These factors were used to calculate CHA2DS2-VASc scores.RESULTS: Of the 141 pilots selected for the study, 17.7% experienced a recurrent event. At 6 mo, the recurrent event rate was 5.0%; at 1 yr, 5.8%; at 3 yr 6.9%; and at 5 yr the recurrent event rate was 17.3%. No statistical difference between CHA2DS2-VASc scores was found as it pertained to number of recurrent events.DISCUSSION: We found no significant factors predicting risk of recurrent event and lower recurrence rates in pilots than the general population. This suggests CHA2DS2-VASc scores are not appropriate risk stratification tools in an aviation population and more research is necessary to determine risk of recurrent events in aviators with atrial fibrillation.Tedford J, Skaggs V, Norris A, Sahiar F, Mathers C. Recurrent stroke risk in pilots with atrial fibrillation. Aerosp Med Hum Perform. 2020; 91(4):352–357.

Optimizing Heart Rate and Controlling Symptoms in Atrial Fibrillation

2016 ◽  
Vol 10 (1) ◽  
pp. 26
Author(s):  
Pragnesh Parikh ◽  
◽  
KL Venkatachalam ◽  
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Rate Control ◽  
Stroke Risk ◽  
Symptom Control ◽  
Review Article ◽  
Rhythm Control ◽  
Ventricular Rate ◽  
Control Methods ◽  
Novel Approaches

Atrial fibrillation (AF) is the most common arrhythmia noted in clinical practice and its incidence and prevalence are on the rise. The single most important intervention is the evaluation and treatment of stroke risk. Once the risk for stroke has been minimized, controlling the ventricular rate and treating symptoms become relevant. In this review article, we emphasize the importance of confirming and treating the appropriate arrhythmia and correlating symptoms with rhythm changes. Furthermore, we evaluate some of the risk factors for AF that independently result in symptoms, underlining the need to treat these risk factors as part of symptom control. We then discuss existing and novel approaches to rate control in AF and briefly cover rhythm control methods.

Pre-Diabetes Increases Stroke Risk in Patients With Nonvalvular Atrial Fibrillation

2021 ◽  
Vol 77 (7) ◽  
pp. 875-884
Author(s):  
Louise Kezerle ◽  
Meytal Avgil Tsadok ◽  
Amichay Akriv ◽  
Adi Berliner Senderey ◽  
Asaf Bachrach ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Stroke Risk ◽  
Nonvalvular Atrial Fibrillation

scholarly journals Hybrid Decision Support to Monitor Atrial Fibrillation for Stroke Prevention

2021 ◽  
Vol 18 (2) ◽  
pp. 813
Author(s):  
Ningrong Lei ◽  
Murtadha Kareem ◽  
Seung Ki Moon ◽  
Edward J. Ciaccio ◽  
U Rajendra Acharya ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Heart Rate ◽  
Decision Support ◽  
Stroke Prevention ◽  
Stroke Risk ◽  
Universal Access ◽  
Healthcare Providers ◽  
High Quality ◽  
Physician Support ◽  
Monitoring Service

In this paper, we discuss hybrid decision support to monitor atrial fibrillation for stroke prevention. Hybrid decision support takes the form of human experts and machine algorithms working cooperatively on a diagnosis. The link to stroke prevention comes from the fact that patients with Atrial Fibrillation (AF) have a fivefold increased stroke risk. Early diagnosis, which leads to adequate AF treatment, can decrease the stroke risk by 66% and thereby prevent stroke. The monitoring service is based on Heart Rate (HR) measurements. The resulting signals are communicated and stored with Internet of Things (IoT) technology. A Deep Learning (DL) algorithm automatically estimates the AF probability. Based on this technology, we can offer four distinct services to healthcare providers: (1) universal access to patient data; (2) automated AF detection and alarm; (3) physician support; and (4) feedback channels. These four services create an environment where physicians can work symbiotically with machine algorithms to establish and communicate a high quality AF diagnosis.

Sign in / Sign up

Export Citation Format

Share Document