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1 INTRODUCTION Atrial fibrillation is a common arrhythmia of which prevalance increases with ages; at 1% in adults and up to 9% in patients over 80 years old The hardship of atrial fibrillation related diseases includes hospitalizations due to hemodynamic disorders, occlusions, heart failure, stroke and death These conditions usually occur when there are structural or electrophysiological abnormalities of the atria that cause abnormal impulses and/or conduction They are characterized by rapid and irregular depolarization of the atria, and together with the lack of P waves on the electrocardiogram, promote the formation of blood clots and consequently increase the risk of stroke Rates of stroke recorded in patients with atrial fibrillation are 7.04% in China; 4.9% in Taiwan, and 13.3/1,000 in Japan The risk of annual stroke in atrial fibrillation patients reported in community-based studies worldwide is 1.09% The Framingham study has showed a five-fold increase in the incidence of overall stroke in patients with atrial fibrillation In Vietnam, regardless of the lack of national and systematic statistics, from a number of studies, frequency of atrial fibrillation in celebral stroke patients is estimated from about 5%/year (Pham Quoc Khanh- 2010) up to 17.3% (Nguyen Duc Long2014) The urgency of the thesis Atrial fibrillation causes the formation of thrombosis in atrial chambers, usually originating from the left atrium, and therefore requires preventive treatment For valvular atrial fibrillation (artificial heart valve, valve repair surgery, moderate to severe mitral stenosis), antivitamin K with INR (International Normalized Ratio) are prescribed to reach a level of 2.0 to 3.0 For non-valvular atrial fibrillation, the thromboprophylaxis strategy is based on stroke risk stratification system using the Cha2DS2-VASc scale, and oral anticoagulants (NOACs-New oral anticoagulants) are additionalled prescribed While cerebral infarction from valvular atrial fibrillation has been well studied, there are still many questions about those from non-valvular atrial fibrillation In some prognosis stroke models, predicting factors often include atrial fibrillation as an important risk factor besides the NIHSS (National Institutes of Health Stroke Scale) Bayesian Model Averaging (BMA - Bayes inference model) is one of the most popular modelling methods currently utilized worldwide instead of the stepwise regression method The basis of this method is to choose the optimal model based on not only the interaction between important groups of variables but also actual clinical conditions, instead of just calculating one final model final Building regression models concurrently with the development of a nomogram to predict the mortality risk in patients with stroke with nonvalvular AF has attacted many interests because of its usability and flexibility Study’s Objectives: Describe the clinical and subclinical characteristics of acute cerebral infarction in patients with nonvalvular atrial fibrillation Identify risk factors for stroke in patients with acute cerebral infarction with nonvalvular atrial fibrillation Develop a prognostic model of 30-days mortality in patients with acute cerebral infarction with nonvalvular atrial fibrillation Thesis significance: Develop a prognostic model of 30-days mortality in patients with acute cerebral infarction with nonvalvular atrial fibrillation 2 Thesis content: This 99-pages thesis includes: Introduction (3 pages), Literature review (36 pages), Study method and population (12 pages), Results (23 pages), Discussion (21 pages), Conclusion (3 pages), and Recommendation (1 page) Chapter LITERATURE REVIEW 1.1 Overview of nonvalvlar atrial fibrillation 1.1.1 Definition of atrial fibrillation Atrial fibrillation is classified as a supraventricular arrhythmia characterized by an electrial asymmetry and atrial muscle contraction with following ECG features: varying R-R intervals (while with good atrioventricular conduction), no signs of P waves, irregularities of atrial waves Atrial fibrillation causes hemodynamic consequences associated with abnormal ventricular responses (too fast or too slow) and ataxia between atrial and ventricular Atrial fibrillation’s symptoms are varried: from asymptomatic to fatigue, nervousness, shortness of breath, or severe symptoms such as hypotension, fainting, or heart failure Atrial fibrillation increases the risk of stroke and/or peripheral embolism due to the formation of thrombus in atrial chambers Onset is usually in the left atrium 1.1.2 Classification of atrial fibrillation In 2016, the Vietnamese Cardiologists Association classified AF based on the time course: - Paroxysmal: ends spontanously, usually within days of onset The attacks may reappear with varying frequencies - Persistent: continuous appearance lasting over days - Permanent: appears continuously for more than 12 months - Chronic: atrial fibrillation cannot restore and/or revert sinus rhythm - Nonvalvular AF: atrial fibrillation occurs when there is no mitral stenosis due to rheumatic heart, no mechanical or biological valve or repair mitral stenosis 1.2 Ischemic stroke in patients with Nonvalvula 1.2.1 Concept Stroke: loss of functions of localized nerves from any cause Commonly used interexchangeable with acute stroke due to insufficient blood flow Acute ischemic stroke: Acute focal neurological defects appear acutely due to insufficient blood flow Cerebral infarction: A region of tissues that dies as a result of anemia 1.2.2 Pathophysiology of cerebral infarction stroke Pathophysiologic mechanism At first, the inner layer of the atherosclerotic wall becomes rough, enabling platelets to attach Since thromboembolism is made of platelets, it is unstable and fragile, and may dissolve on its own Also, collateral circulation may be formed to promptly compensate for the anemic area, resulting in full clinically recovery within 24 hours In the later stage, atherosclerosis also contains red blood cells and attached blood fibers, causing blood clots more durable Thus, when it sloughs off to the brain, it clogs and causes ischemia Mechanism of recovery When a stroke occurs, on average every minute, millions of brain cells die in the damaged brain areas due to blocked arteries The most serious damage is the necrotic area because this is an non-recoverable area The cells surrounding the affected area in the stroke are called “light murals”/“Grey zones” (or “treatment areas”) - although not dead, they have reduced metabolism to a minimum and almost lost all functions The goal of treatment is to restore those areas and restore their activities 1.3 Prognostic models of risk factors of nonvalvular AF 1.3.1 Prognosis studies related to stroke with valvular and/or nonvalvular AF in several hospitals national wide In 2016, Dang Viet Duc et al conducted a study to investigate the relation and prediction coronary artery disease and Cha2DS2-VASc and Cha2DS2-VASc-HS scores on 94 patients with coronary artery lesions images, and found that Cha2DS2-VASc average score was 3.55 ± 1.29 and that of Cha2DS2-VASc-HS was 5.13 ± 1.46 On coronary angiography image results: average Gensini lesions score was 22.7 ± 20.5 73 patients (77.7%) showed a significant coronary artery stenosis (≥ 50% of vascular diameter) The area under the ROC evaluates prediction of coronary artery diseases of Cha2DS2-VASc and Cha2DS2-VASc-HS scores with areas under the curve (AUC) of 0.77 and 0.81 respectively; The corresponding cut-off points of the two scales are 3.5 and 4.5 with a sensitivity of 57.5% -72.6% and specificity 81% -71.4% The Cha2DS2-VASc and Cha2DS2-VASc-HS scales have a strong correlation with coronary artery damage on the Gensini scale with r = 0.64 and 0.69 with p hour 25 18,1 25 16,6 p=0,776 Results: Time to intervention has highest frequency in 3- 4.5h group (45,7% in Study group and 31,8% in Control group), and lowest frequency in 6h intervention group (16,6% in non-AF) The difference is statistically significant in less-than-4.5h group (p0,05) Duration of hospitalization Table 3.8 Number of hospitalization days (n=289) Mean number of days Study group (n=138) Control group (n=151) p (𝟀𝟐 ) hospitalized 27,11 ± 12,34 20,49 ± 9,87 p=0,025 𝑋̅ ± SD (date) Results: Mean number of days of hospitalization in Study group is statistically significantly higher than that in Control group 3.2.2 Clinical Characteristics CT-scanner Table 3.9 CT scan images (n=62) Study group Control group (n=138) (n=151) Hình ảnh học p (𝟀𝟐 ) n % n % Sulcal effacement 15 10,9 6,0 p=0,089 Subcortical hypodensity 5,1 4,0 p=0,078 Mass effect 0 6,6 Pots sign 5,8 10 6,6 p=0,108 Hyperdense artery sign 6,5 11 7,3 p=0,088 Results: There is no statistically significantly differences between case and control groups MRI images Table 3.10 MRI Images (n=228) Study group Control group (n=138) (n=151) Image p (𝟀𝟐 ) Middle cerebral artery occlusion at M1 Middle cerebral artery occlusion at M2 n % n % 46 32 41,4 28,8 38 24 32,5 20,5 p=0,021 p=0,045 12 Middle cerebral artery occlusion at M3 Brain carotid artery occlusion Anterior cerebral artery occlusion Posterior cerebral artery occlusion Basilar artery occlusion Vertebral artery occlusion Supratentonial infarcts Infratentionrial infarcts 34 11 16,2 30,6 6,3 4,5 16,2 8,1 9,9 18 20 26 15,4 17,1 3,4 2,6 6,0 2,6 22,2 p=0,086 p=0,045 p=0,077 p=0,085 p=0,065 p=0,078 p=0,013 6,3 7,7 p=0,098 Results: In both study group control group, highest rates are at middle cerebral artery occlusion at M1 group, and lowest at posterior cerebral artery occlusion group 3.3 Risk factors of cerebral infraction acute stroke in study subjects 3.3.1 Associated factors Place and time of onset Morring 66,7 Night 70,2 33,3 29,8 Study group Control group At home Office Other 22,5 14,5 22,8 13,2 63,0 62,9 Study group Control group Figure 3.1 Place and time of onset (n=289) Results: - Onset at night is fold higher than at day, in both groups (p>0,05) - Place of onset is similar in AF and non-AF groups with 63% at home, and smaller proportion occurs at work or at different places (p>0,05) Medical history Table 3.11 Association between comorbidities and stroke (n=289) Study group Control group Cormobidities OR (95%CI), p (n=138) (n=151) 2+ comorbodities 29 18 1,53 (0,781-0,987) p
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