Clinical and Imaging Characteristics of Cerebral Infarction in Patients with Nonvalvular Atrial Fibrillation Combined with Cerebral Artery Stenosis

Sun, Wei; Li, Guang-Sheng; Zeng, Xiangjun; Lai, Zhaohui; Wang, Mingqi; Ouyang, Yidan; Zeng, Guoyong; Peng, Jidong; Zhong, Junyuan; Xiao, Daoxiong; Huang, Zhiping; Xiao-fen, Guo

doi:10.5551/jat.43240

Cited by 30 publications

(25 citation statements)

References 26 publications

(30 reference statements)

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“…This further reduces cerebral blood flow, and causes the insufficiency of blood supply for brain tissues, aggravating the cerebral infarction. This conclusion is basically consistent with the results reported in literature (13)(14)(15)(16).…”

Section: Discussionsupporting

confidence: 94%

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Application of Concomitant Disease Scoring in Acute Cerebral Infarction

Zhao¹,

Li²,

Liu³

et al. 2020

Iran Red Crescent Med J

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Background: Acute cerebral infarction (ACI) is a common cerebrovascular disease that seriously endangers human health. It is very important to carry out disease assessments to rescue patients who may suffer from preventable death. Objectives: This study aimed to explore the predictive value of concomitant disease scoring for the prognosis of patients with ACI. Methods: This is a respective observational study. A total of 399 patients with ACI from the Affiliated Hospital of North China University of Science and Technology, who met the inclusion criteria, were enrolled in the present study. The concomitant disease score was assessed within 24 hours after admission, and the risk degree of death was analyzed. Then, the goodness of fit test and validity analysis were carried out, and the best survival/death cutoff value was determined. Results: The area under the receiver operating characteristic (ROC) curve for the concomitant disease score was 0.700, the distinctiveness was relatively good, and the prediction cutoff value was 10 points. Furthermore, the mortality rate of patients with a higher score was significantly higher compared to patients with a lower score. Conclusions: The concomitant disease score has good predictive value for the prognosis of ACI patients, and is an ideal system for evaluating the condition of cerebral infarction.

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Section: Discussionsupporting

confidence: 94%

“…Cerebral artery stenosis is another risk factor for progressive cerebral infarction (14). Zhiwu Wu et al (17) reported that the risk of severe cerebral infarction increased in patients with severe cerebral artery stenosis.…”

Section: Discussionmentioning

confidence: 99%

Application of Concomitant Disease Scoring in Acute Cerebral Infarction

Zhao¹,

Li²,

Liu³

et al. 2020

Iran Red Crescent Med J

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“…At present, imaging technology is mainly used to diagnose and treat patients with cerebral infarction. Compared with X-ray and computed tomography (CT) scanning technology, MRI has clearer scan images and relatively low ionizing radiation, so it is often used in the diagnosis and treatment of patients with cerebral infarction [ 2 ]. However, MRI technology still has some shortcomings.…”

Section: Introductionmentioning

confidence: 99%

Magnetic resonance imaging reconstruction algorithm under complex convolutional neural network in diagnosis and prognosis of cerebral infarction

et al. 2021

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This study was to explore the application value of magnetic resonance imaging (MRI) image reconstruction model based on complex convolutional neural network (CCNN) in the diagnosis and prognosis of cerebral infarction. Two image reconstruction methods, frequency domain reconstruction network (FDRN) and image domain reconstruction network (IDRN), were introduced based on the CCNN algorithm. In addition, they were integrated to form two new MRI image reconstruction models, namely D-FDRN and D-IDRN. The peak signal to noise ratio (PSNR) value and structural similarity index measure (SSIM) value of the image were compared and analyzed before and after the integration. The MRI images of patients with cerebral infarction in the dataset were undertaken as the data source, the average diffusion coefficient (DCavg) and apparent diffusion coefficient (ADC) values of different parts of the MRI image were measured, respectively. The correlation of the vein abnormality grading (VABG) to the infarct size and the degree of stenosis of the responsible vessel was analyzed in this study. The results showed that the PSNR and SSIM values of the MRI reconstructed image of the D-IDRN algorithm based on the CCNN algorithm in this study were higher than those of other algorithms. There was a positive correlation between the VABG and the infarct size (r = 0.48 and P = 0.002), and there was a positive correlation between the VABG the degree of stenosis of the responsible vessel (r = 0.58 and P < 0.0001). The ADC value of the central area of the infarct on the affected side was significantly greatly lower than that of the normal side (P < 0.01), and the DCavg value of the central area of the infarct was much lower in contrast to the normal side (P < 0.05). It indicated that an image reconstruction algorithm constructed in this study could improve the quality of MRI images. The ADC value and DCavg value changed in the infarct central area could be used as the basis for the diagnosis of cerebral infarction. If the vein was abnormal, the patient suffered from severe vascular stenosis, large infarction area, and poorer prognosis.

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“…as hypertension, AS, dyslipidaemia, obesity, diabetes mellitus, and smoking (6)(7)(8). Hypertension is an important traditional risk factor in the progression of cerebral infarction (9).…”

Section: The Development and Progression Of Cerebral Infarction Are Amentioning

confidence: 99%

Correlation between plasma levels of Lp-PLA2, Hcy, CRP, Lp(a), AT-III, and TEG parameters and carotid atherosclerosis in patients with combined hypertension and cerebral infarction

wang

Zhu

et al. 2019

Preprint

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Background: To observe the correlation between Lp-PLA2, Hcy, CRP, Lp(a), AT-III, and TEG parameters and carotid atherosclerosis with combined hypertension and cerebral infarction and evaluate their value in risk determination.Methods: Patients with primary hypertension were selected as subjects and divided into 2 groups based on cerebral infarction: simple hypertension group and hypertension combined with cerebral infarction group. The differences of Lp-PLA2, Hcy, CRP, Lp(a), AT-Ⅲ, and TEG were compared. Spearson correlation and multivariate logistic regression model were used to analyze the correlation. A ROC curve was used to analyse the value of a single item and their combination for the determination of carotid AS risk.Results: The levels of single item and CIMT in the hypertension combined with cerebral infarction group were higher, and the values of R, EPL, and LY30 were lower than corresponding indicators in the simple hypertension group. Furthermore, it was found that Lp-PLA2 and Hcy were risk factors. The AUC for Hcy and Lp-PLA2 for the determination the carotid AS risk were larger. Conclusions: The increase or decrease of Lp-PLA2, Hcy, and TEG were important factors influencing the development of carotid AS with combined hypertension and cerebral infarction. The levels of Lp-PLA2, Hcy, and TEG with combined hypertension and cerebral infarction were significantly different from those with simple hypertension and could be used as independent predictive factors for determining carotid AS risk.

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Clinical and Imaging Characteristics of Cerebral Infarction in Patients with Nonvalvular Atrial Fibrillation Combined with Cerebral Artery Stenosis

Cited by 30 publications

References 26 publications

Application of Concomitant Disease Scoring in Acute Cerebral Infarction

Application of Concomitant Disease Scoring in Acute Cerebral Infarction

Magnetic resonance imaging reconstruction algorithm under complex convolutional neural network in diagnosis and prognosis of cerebral infarction

Correlation between plasma levels of Lp-PLA2, Hcy, CRP, Lp(a), AT-III, and TEG parameters and carotid atherosclerosis in patients with combined hypertension and cerebral infarction

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