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Lai Z, Peng M, He H, Li Y, Bai X, Cai J. Percutaneous transluminal angioplasty and stenting vs aggressive medical management on stroke or intracranial atherosclerotic stenosis: a systematic review and meta-analysis. Sci Rep 2023; 13:7567. [PMID: 37161029 PMCID: PMC10169842 DOI: 10.1038/s41598-023-34663-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 05/05/2023] [Indexed: 05/11/2023] Open
Abstract
There are currently two main treatment strategies mainly for high-risk patients: percutaneous transluminal angioplasty and stenting (PTAS) and aggressive medical management (AMM). However, the choice between PTAS or AMM remains controversial for patients with stroke or intracranial atherosclerotic stenosis (ICAS). The investigators searched the PubMed, Web of Science, Embase, Scopus, and Cochrane library databases. Randomized controlled trial (RCT) comparing PTAS and AMM for patients with stroke or ICAS were selected. RevMan 5.3 was used to analyze the results and assess risk of bias. The primary endpoints are stroke and death within 30 days after enrollment, or ischemic stroke in the territory of the qualifying artery beyond 30 days, and entire follow-up endpoints. The secondary outcomes were the disabling or fatal stroke, and incidence of death within 3 years. Four studies, 989 patients were included in this article. The AMM group was superior in the entire follow-up endpoint (OR 0.56; 95% CI 0.40, 0.79). The AMM also better in primary endpoint within 30 days (OR 0.32; 95% CI 0.17, 0.61). There was no significant difference beyond 30 days (OR 1.08; 95% CI 0.63, 1.86). The remaining outcomes, such as stroke and death, were not significantly different (P > 0.05). This meta-analysis shows AMM is significantly more effective than PTAS in subjects with ICAS due to the high rate of periprocedural stroke (OR 0.32; 95% CI 0.17, 0.61) and stroke during the entire follow-up (OR 0.56; 95% CI 0.40, 0.79) associated with PTAS. Furthermore, PTAS offers no additional benefits over AMM beyond 30 days (OR 1.08; 95% CI 0.63, 1.86).
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Affiliation(s)
- Zhiyu Lai
- Diagnosis and Treatment Center of Encephalopathy, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
- Department of Cerebrovascular Surgery, Hospital of Guangzhou University Mega Center, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510006, China
- The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Mingqiang Peng
- Diagnosis and Treatment Center of Encephalopathy, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
- Department of Cerebrovascular Surgery, Hospital of Guangzhou University Mega Center, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510006, China
- The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Haoming He
- Diagnosis and Treatment Center of Encephalopathy, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
- Department of Cerebrovascular Surgery, Hospital of Guangzhou University Mega Center, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510006, China
- The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Yingbin Li
- Diagnosis and Treatment Center of Encephalopathy, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
- Department of Cerebrovascular Surgery, Hospital of Guangzhou University Mega Center, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510006, China
- The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Xiaoxin Bai
- Diagnosis and Treatment Center of Encephalopathy, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
- Department of Cerebrovascular Surgery, Hospital of Guangzhou University Mega Center, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510006, China
- The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Jun Cai
- Diagnosis and Treatment Center of Encephalopathy, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China.
- Department of Cerebrovascular Surgery, Hospital of Guangzhou University Mega Center, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510006, China.
- The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China.
- Department of Neurosurgery, Hospital of Guangzhou Higher Education Mega Center, Guangdong Provincial Hospital of Chinese Medicine, No. 55 Neihuan Xi Road, Guangzhou, 510006, Guangdong, China.
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Sun S, Liu D, Zhou Y, Yang G, Cui LB, Xu X, Guo Y, Sun T, Jiang J, Li N, Wang Y, Li S, Wang X, Fan L, Cao F. Longitudinal real world correlation study of blood pressure and novel features of cerebral magnetic resonance angiography by artificial intelligence analysis on elderly cognitive impairment. Front Aging Neurosci 2023; 15:1121152. [PMID: 36819723 PMCID: PMC9935573 DOI: 10.3389/fnagi.2023.1121152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 01/16/2023] [Indexed: 02/05/2023] Open
Abstract
Objective This study aims to investigate novel clinical risk factors for cognitive impairment (CI) in elderly. Methods A total of 3221 patients (259 patients with CI and 2,962 subjects without CI) were recruited into this nested case-control study who underwent cerebral magnetic resonance angiography (MRA) from 2007 to 2021. All of the clinical data with MRA imaging were recorded followed by standardization processing blindly. The maximum stenosis score of the posterior circulatory artery, including the basilar artery, and bilateral posterior cerebral artery (PCA), was calculated by the cerebral MRA automatic quantitative analysis method. Logistic regression (LR) analysis was used to evaluate the relationship between risk factors and CI. Four machine learning approaches, including LR, decision tree (DT), random forest (RF), and support vector machine (SVM), employing 5-fold cross-validation were used to establish CI predictive models. Results After matching with age and gender, 208 CI patients and 208 control subjects were finalized the follow-up (3.46 ± 3.19 years) with mean age at 84.47 ± 6.50 years old. Pulse pressure (PP) in first tertile (<58 mmHg) (OR 0.588, 95% confidence interval (CI): 0.362-0.955) was associated with a decreased risk for CI, and ≥50% stenosis of the left PCA (OR 2.854, 95% CI: 1.387-5.872) was associated with an increased risk for CI after adjusting for body mass index, myocardial infarction, and stroke history. Based on the means of various blood pressure (BP) parameters, the performance of the LR, DT, RF and SVM models accurately predicted CI (AUC 0.740, 0.786, 0.762, and 0.753, respectively) after adding the stenosis score of posterior circulatory artery. Conclusion Elderly with low pulse differential pressure may have lower risk for cognitive impairment. The hybrid model combined with the stenosis score of posterior circulatory artery, clinical indicators, and the means of various BP parameters can effectively predict the risk of CI in elderly individuals.
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Affiliation(s)
- Shasha Sun
- Department of Cardiology, Chinese PLA Medical School, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Dongyue Liu
- Department of Cardiology, Chinese PLA Medical School, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Yanfeng Zhou
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China,Laboratory of Computational Biology and Machine Intelligence, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Ge Yang
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China,Laboratory of Computational Biology and Machine Intelligence, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Long-Biao Cui
- Department of Cardiology, Chinese PLA Medical School, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Xian Xu
- Department of Radiology, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Yuanhao Guo
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China,Laboratory of Computational Biology and Machine Intelligence, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Ting Sun
- Department of Cardiology, Chinese PLA Medical School, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Jiacheng Jiang
- Department of Radiology, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Na Li
- Nankai University School of Medicine, Nankai University, Tianjin, China
| | - Yabin Wang
- Department of Cardiology, Chinese PLA Medical School, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Sulei Li
- Department of Cardiology, Chinese PLA Medical School, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Xinjiang Wang
- Department of Radiology, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Li Fan
- Department of Cardiology, Chinese PLA Medical School, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China,Li Fan,
| | - Feng Cao
- Department of Cardiology, Chinese PLA Medical School, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China,*Correspondence: Feng Cao,
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Dose-response relationship between blood pressure and intracranial atherosclerotic stenosis. Atherosclerosis 2020; 317:36-40. [PMID: 33333347 DOI: 10.1016/j.atherosclerosis.2020.12.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 11/10/2020] [Accepted: 12/02/2020] [Indexed: 01/17/2023]
Abstract
BACKGROUND AND AIMS We aimed to explore the association between blood pressure, intracranial atherosclerotic stenosis (ICAS) risks and ICAS burden in the Chinese population. METHODS A retrospective hospital-based multi-center case-control study with large sample size was conducted. 1055 ICAS patients and 1296 non-ICAS subjects with complete clinical information and intracranial artery evaluation were identified between 2014 and 2019. Cerebral arteries were evaluated by magnetic resonance angiography, and/or computed tomography, and/or digital subtraction angiography. Two or more neurologists were involved in reading and assessment of images. The association between ICAS and burden of ICAS with blood pressure was evaluated with univariate logistic models and multivariate logistic models. RESULTS With every increase of 10 mmHg in systolic blood pressure, diastolic blood pressure and pulse pressure, the odds of ICAS increased by 32%, 28% and 35% in multivariate analysis, respectively (odds ratio = 1.32, 1.28, and 1.35 respectively, all p < 0.001). Similarly, every increment of 10 mmHg in systolic blood pressure and pulse pressure was associated with an increased risk of ICAS burden (each odds ratio = 1.08, p < 0.05). CONCLUSIONS Systolic blood pressure, diastolic blood pressure, and pulse pressure were associated with the risk of ICAS in a dose-response manner. Moreover, higher systolic blood pressure and pulse pressure could lead to higher ICAS burdens.
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Zhang K, Lin Q, Zhang T, Guo D, Cao L. Contemporary Prevalence and risk factors of carotid artery stenosis in asymptomatic low-income Chinese individuals: a population-based study. Postgrad Med 2020; 132:650-656. [PMID: 32590917 DOI: 10.1080/00325481.2020.1788319] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
OBJECTIVES Carotid artery stenosis (CAS) is an established risk factor for cerebrovascular disease. However, the contemporary prevalence and risk factors of CAS in asymptomatic rural Chinese individuals, especially low-income populations, remains unclear. Therefore, we aimed to explore the present prevalence and risk factors of CAS in a low-income Chinese population. METHODS A total of 3126 people aged ≥ 45 years without history of stroke or cardiovascular disease were recruited for this study. B-mode ultrasonography was performed to evaluate the presence of CAS. We used multivariate analysis to determine potential risk factors for CAS. RESULTS The overall prevalence of CAS in this population was 6.7%, with a prevalence of 8.8% for men and 5.0% for women. The risk of CAS increased with older age and a higher level of low-density lipoprotein cholesterol (LDL-C), systolic blood pressure (SBP), and fasting blood glucose (FBG) (all P < 0.05). Each 1-mmHg increase in SBP increased the risk of CAS by 0.011 times, each 1-mmol/L increase in LDL-C increased the risk of CAS by 0.192 times, and each 1-mmol/L increase in FBG increased the risk of CAS by 0.067 times. In addition, the risk of CAS increased 52.9% in men compared to that in women, increased 100.2% in current drinkers compared to that in never drinkers, and increased 38.9% in patients with diabetes compared to those without diabetes (all P < 0.05). CONCLUSIONS These findings suggest that the prevalence of CAS remains high in low-income individuals. Male sex, older age, current drinking, diabetes, and high levels of LDL-C, SBP, and FBG increase the risk of CAS. Thus, to prevent cerebrovascular disease and reduce the severe disease-associated burden for low-income individuals, there is a definitive need to control the risk factors of CAS.
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Affiliation(s)
- Kai Zhang
- Department of Geriatrics, Tianjin Medical University General Hospital , Tianjin, China
| | - Qiuxing Lin
- Department of Neurology, Tianjin Medical University General Hospital , Tianjin, China.,Laboratory of Epidemiology, Tianjin Neurological Institute , Tianjin, China.,Tianjin Neurological Institute, Key Laboratory of Post-Neuroinjury Neuro-repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City , Tianjin, China
| | - Tianyu Zhang
- Department of Geriatrics, Tianjin Medical University General Hospital , Tianjin, China
| | - Dandan Guo
- Centre of Ultrasound, Tianjin Medical University General Hospital , Tianjin, China
| | - Li Cao
- Department of Geriatrics, Tianjin Medical University General Hospital , Tianjin, China
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