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Effects of the information–knowledge–attitude–practice nursing model combined with predictability intervention on patients with cerebrovascular disease

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World Journal of Clinical Cases 2022年第20期10卷 6803-6810页

作者： Hong-Liang Huo Yuan-Yuan Gui Chun-Miao Xu Yan Zhang Qiang Li Department of Nursing The Fourth Affiliated Hospital of Qiqihar Medical UniversityQiqihar 161000Heilongjiang ProvinceChina Nursing School Qiqihar Medical UniversityQiqihar 161006Heilongjiang ProvinceChina

BACKGROUND cerebrovascular disease(CVD)poses a serious threat to human health and safety.Thus,developing a reasonable exercise program plays an important role in the long-term recovery and prognosis for patients with CVD.Studies have shown that predictive nursing can improve the quality of care and that the information–knowledge–attitude–practice(IKAP)nursing model has a positive impact on patients who suffered a stroke.Few studies have combined these two nursing models to treat CVD.AIM To explore the effect of the IKAP nursing model combined with predictive nursing on the Fugl–Meyer motor function(FMA)score,Barthel index score,and disease knowledge mastery rate in patients with CVD.METHODS A total of 140 patients with CVD treated at our hospital between December 2019 and September 2021 were randomly divided into two groups,with 70 patients in each.The control group received routine nursing,while the observation group received the IKAP nursing model combined with predictive nursing.Both groups were observed for self-care ability,motor function,and disease knowledge mastery rate after one month of nursing.RESULTS There was no clear difference between the Barthel index and FMA scores of the two groups before nursing(P>0.05);however,their scores increased after nursing.This increase was more apparent in the observation group,and the difference was statistically significant(Pdisease knowledge mastery,timely medication,appropriate exercise,and reasonable diet were significantly higher in the observation group than in the control group(P<0.05).The satisfaction rate in the observation group(97.14%)was significantly higher than that in the control group(81.43%;P<0.05).CONCLUSION The IKAP nursing model,combined with predictive nursing,is more effective than routine nursing in the care of patients with CVD,and it can significantly improve the Barthel index and FMA scores with better knowledge acquisition,as well as produce high satisfaction in patients.Moreover,they can be widely used in the clinical se

关键词： Information–knowledge–attitude–practice nursing model Predictive nursing cerebrovascular disease Barthel index Fugl–Meyer motor function score disease knowledge mastery rate

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Assessment of cheese sign and its association with vascular risk factors: Data from PUMCH dementia cohort

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中华医学杂志(英文版) 2024年第7期137卷 830-836页

作者： Huang Xinying Hou Bo Wang Jie Li Jie Shang Li Mao Chenhui Dong Liling Liu Caiyan Feng Feng Gao Jing Peng Bin Department of Neurology State Key Laboratory of Complex Severe and Rare disease Peking Union Medical College Hospital Chinese Academy of Medical Science and Peking Union Medical College Beijing 100730 China Department of Radiology Chinese Academy of Medical Sciences and Peking Union Medical College

Background: In the clinic, practitioners encounter many patients with an abnormal pattern of dense punctate magnetic resonance imaging (MRI) signal in the basal ganglia, a phenomenon known as "cheese sign". This sign is reported as common in cerebrovascular diseases, dementia, and old age. Recently, cheese sign has been speculated to consist of dense perivascular space (PVS). This study aimed to assess the lesion types of cheese sign and analyze the correlation between this sign and vascular disease risk factors.Methods: A total of 812 patients from Peking Union Medical College Hospital (PUMCH) dementia cohort were enrolled. We analyzed the relationship between cheese sign and vascular risk. For assessing cheese sign and defining its degree, the abnormal punctate signals were classified into basal ganglia hyperintensity (BGH), PVS, lacunae/infarctions and microbleeds, and counted separately. Each type of lesion was rated on a four-level scale, and then the sum was calculated; this total was defined as the cheese sign score. Fazekas and Age-Related White Matter Changes (ARWMC) scores were used to evaluate the paraventricular, deep, and subcortical gray/white matter hyperintensities.Results: A total of 118 patients (14.5%) in this dementia cohort were found to have cheese sign. Age (odds ratio [OR]: 1.090, 95% confidence interval [CI]: 1.064-1.120,P <0.001), hypertension (OR: 1.828, 95% CI: 1.123-2.983,P = 0.014), and stroke (OR: 1.901, 95% CI: 1.092-3.259,P = 0.025) were risk factors for cheese sign. There was no significant relationship between diabetes, hyperlipidemia, and cheese sign. The main components of cheese sign were BGH, PVS, and lacunae/infarction. The proportion of PVS increased with cheese sign severity.Conclusions: The risk factors for cheese sign were hypertension, age, and stroke. Cheese sign consists of BGH, PVS, and lacunae/infarction.

关键词： Dementia cerebrovascular disease Cheese sign Dense punctate lesions Basal ganglia Risk factor White matter

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Machine learning applications in stroke medicine:advancements,challenges,and future prospectives

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Neural Regeneration Research 2024年第4期19卷 769-773页

作者： Mario Daidone Sergio Ferrantelli Antonino Tuttolomondo Internal Medicine and Stroke Care Ward Department of Health PromotionMother and Child CareInternal Medicine and Medical SpecialtiesUniversity of Palermo Molecular and Clinical Medicine PhD Program University of Palermo

Stroke is a leading cause of disability and mortality worldwide,necessitating the development of advanced technologies to improve its diagnosis,treatment,and patient outcomes.In recent years,machine learning techniques have emerged as promising tools in stroke medicine,enabling efficient analysis of large-scale datasets and facilitating personalized and precision medicine approaches.This abstract provides a comprehensive overview of machine learning’s applications,challenges,and future directions in stroke medicine.Recently introduced machine learning algorithms have been extensively employed in all the fields of stroke medicine.Machine learning models have demonstrated remarkable accuracy in imaging analysis,diagnosing stroke subtypes,risk stratifications,guiding medical treatment,and predicting patient prognosis.Despite the tremendous potential of machine learning in stroke medicine,several challenges must be addressed.These include the need for standardized and interoperable data collection,robust model validation and generalization,and the ethical considerations surrounding privacy and bias.In addition,integrating machine learning models into clinical workflows and establishing regulatory frameworks are critical for ensuring their widespread adoption and impact in routine stroke care.Machine learning promises to revolutionize stroke medicine by enabling precise diagnosis,tailored treatment selection,and improved prognostication.Continued research and collaboration among clinicians,researchers,and technologists are essential for overcoming challenges and realizing the full potential of machine learning in stroke care,ultimately leading to enhanced patient outcomes and quality of life.This review aims to summarize all the current implications of machine learning in stroke diagnosis,treatment,and prognostic evaluation.At the same time,another purpose of this paper is to explore all the future perspectives these techniques can provide in combating this disabling disease.

关键词： cerebrovascular disease deep learning machine learning reinforcement learning stroke stroke therapy supervised learning unsupervised learning

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Impact of cerebrovascular disease Mortality on Life Expectancy in China

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Biomedical and Environmental Sciences 2014年第3期27卷 169-175页

作者： LI Guo Qi FAN Jie LIU Jing WANG Wei WANG Miao QI Yue XIE Wu Xiang LIU Jun ZHAO Fan LI Yan ZHAO Dong Department of Epidemiology Beijing An Zhen HospitalCapital Medical UniversityBeijing Institute of HeartLung and Blood Vessel Diseases

Objective To evaluate the impact of cerebrovascular disease mortality on life expectancy （LE） in China in 2010 compared with 2005, and to identify the high-risk population （age, sex, and region） where cerebrovascular disease mortality has had a major impact on LE. Methods LE and cause-eliminated LE were calculated by using standard life tables which used adjusted mortality data from the Death Surveillance Data Sets in 2005 and 2010 from the National disease Surveillance System. Decomposition was used to quantitate the impact of cerebrovascular disease in different age groups. Results LE in China was 73.24 years in 2010, which was higher in women and urban residents compared with men and rural residents. The loss of LE caused by cerebrovascular disease mortality was 2.26 years, which was higher in men and rural residents compared with women and urban residents. More than 30% of the loss of LE were attributed to premature death from cerebrovascular disease in people aged 〈65 years. Compared with 2005, LE in 2010 increased by 0.92 years. The reduction of cerebrovascular disease mortality in urban residents contributed 0.45 years to the increase of LE, but the increase of cerebrovascular disease mortality caused a 0.12-year loss of LE in rural residents. Conclusion cerebrovascular disease mortality had a major impact on LE in China, with a significant difference between urban and rural residents. LE is likely to be further increased by reducing cerebrovascular disease mortality, and special attention should be paid to reducing premature deaths in people aged 〈65 years.

关键词： cerebrovascular disease Life expectancy Loss of Life

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Long-term exposure to air pollution and cerebrovascular disease:findings from Beijing Health Management Cohort study

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Frontiers of Environmental Science & Engineering 2023年第7期17卷 79-89页

作者： Yuhan Zhao Xiaoping Kang Xue Tian Lulu Liu Zemeng Zhao Lili Luo Lixin Tao Xiangtong Liu Xiaonan Wang Xiuhua Guo Juan Xia Yanxia Luo School of Public Health Capital Medical UniversityBeijing 100069China Beijing Municipal Key Laboratory of Clinical Epidemiology Capital Medical UniversityBeijing 100069China Beijing Xiaotangshan Hospital Beijing 102211China

The relationship between air pollution and cerebrovascular disease has become a popular topic,yet research findings are highly heterogeneous.This study aims to investigate this association based on detailed individual health data and a precise evaluation of their exposure levels.The integrated models of generalized additive model,land use regression model and back propagation neural network were used to evaluate the exposure concentrations.And doubly robust additive model was conducted to explore the association between cerebrovascular disease and air pollution after adjusted for demographic characteristics,physical examination,disease information,geographic and socioeconomic status.A total of 25097 subjects were included in the Beijing Health Management Cohort from 2013 to 2018.With a 1µg/m^(3)increase in the concentrations of PM_(2.5),SO_(2)and NO_(2),the incidence risk of cerebrovascular disease increased by 1.02(95%CI:1.008–1.034),1.06(95%CI:1.034–1.095)and 1.02(95%CI:1.010–1.029)respectively.Whereas CO exposure could decrease the risk,with an odds ratio of 0.38(95%CI:0.212–0.626).In the subgroup analysis,individuals under the age of 50 with normal BMI were at higher risk caused by PM2.5,and So2 was considered more hazardous to women.Meanwhile,the protective effect of CO on women and those with normal BMI was stronger.Successful reduction of long-term exposure to PM2.5,SO_(2)and NO_(2)would lead to substantial benefits for decrease the risk of cerebrovascular disease especially for the health of the susceptible individuals.

关键词： Air pollution cerebrovascular disease Incidence Long-term exposure Doubly robust additive model

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Network pharmacology-based prediction and verification of the molecular targets and pathways for schisandrin against cerebrovascular disease

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Chinese Journal of Natural Medicines 2014年第4期12卷 251-258页

作者： LV Yan-Ni LI Shao-Xia ZHAI Ke-Feng KOU Jun-Ping YU Bo-Yang State Key Laboratory of Natural Medicines China Pharmaceutical University Department of Complex Prescription of TCM China Pharmaceutical University

AIM: To illuminate the molecular targets for schisandrin against cerebrovascular disease based on the combined methods of network pharmacology prediction and experimental verification. METHOD: A protein database was established through constructing the drug-protein network from literature mining data. The protein-protein network was built through an in-depth exploration of the relationships between the proteins. The computational platform was implemented to predict and extract the sensitive sub-network with significant P-values from the protein-protein network. Then the key targets and pathways were identified from the sensitive sub-network. The most related targets and pathways were also confirmed in hydrogen peroxide(H2O2)-induced PC12 cells by Western blotting. RESULTS: Twelve differentially expressed proteins(gene names: NFKB1, RELA, TNFSF10, MAPK1, CHUK, CASP8, PIGS2, MAPK14, CREB1, IFNG, APP, and BCL2) were confirmed as the central nodes of the interaction network(45 nodes, 93 edges). The NF-κB signaling pathway was suggested as the most related pathway of schisandrin for cerebrovascular disease. Furthermore, schisandrin was found to suppress the expression and phosphorylation of IKKα, as well as p50 and p65 induced by H2O2 in PC12 cells by Western blotting. CONCLUSION: The computational platform that integrates literature mining data, protein-protein interactions, sensitive sub-network, and pathway results in identification of the NF-κB signaling pathway as the key targets and pathways for schisandrin.

关键词： Schisandrin Network pharmacology cerebrovascular disease Molecular target NF-κB signaling pathway

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Association of Fibrin Monomer Polymerization Function, cerebrovascular Risk Factors and Ischemic cerebrovascular disease in Old People

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Journal of Huazhong University of Science and Technology(Medical Sciences) 2003年第2期23卷 131-133页

作者：洪梅魏文宁李红戈杨锐杨焰 Insititute of Haematology Xiehe Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan 430022 Department of Neurology Xiehe Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan 430022

In order to investigate the association of fibrin monomer polymerization function (FMPF) with traditional cerebrovascular risk factors and ischemic cerebrovascular disease in old people. 1∶1 paired case-control comparative study was performed for FMPF and traditional cerebrovascular risk factors on 110 cases of old ischemic cerebrovascular disease and 110 controls matched on age, sex and living condition. The results showed that cerebrovascular risk factors were more prevalent in case group than in control group. In the case group, FMPF was significantly higher than in control group. There was a significant positive correlation between hypertension and fibrin monomer polymerization velocity (FMPV), hypertension and fibrinogen (Fbg), alcohol consumption and Fbg, but no significant correlation between diabetic mellitus, smoking and FMPF was found. Among the parameters of blood lipids, there were significant positive correlations between total cholesterol (TC) and parameters of FMPF to varying degrees, triglycerides (TG) and FMPV, TG and Fbg. Our results also showed there were significant linear trends between TC and FMPV (Pcerebrovascular risk factors. An elevated FMPF is associated with ischemic cerebrovascular disease and an independent risk factor of this disease. In old people, detection of FMPF might be a useful screening to identify individuals at increased cerebrothrombotic risk.

关键词： old people fibrin monomer polymerization function cerebrovascular disease risk factor

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Circulating Vitamin D and Risk of cerebrovascular disease:A Meta-analysis

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Journal of cerebrovascular disease 2023年第1期6卷 1-7页

作者： Wei Huang Meng-Xiao Feng Yuan-Qiang Lu Department of Emergency Medicine The First Affiliated HospitalZhejiang UniversitySchool of MedicineHangzhou 310003China Key Laboratory for Diagnosis and Treatment of Aging and Physic-chemical Injury diseases of Zhejiang Province Hangzhou 310003China

Objective:This scoping review aims to perform a meta-analysis to harmonize the existing results on circulating vitamin D and cerebrovascular disease.Methods:Three scientific databases,PubMed,the Cochrane Library and EMBASE,were systematically searched.The overall relative risk(RR)and the corresponding 95%confidence interval(CI)were calculated using a random-effects model,and sensitivity analysis and publication bias tests were performed.Results:Of the 4,138 articles retrieved,28 studies were included in our analysis,with a cumulative sample size of 284,840.Subsequent random-effects meta-analysis showed an association between low levels of vitamin D and cerebrovascular disease:RR=1.39,95%CI:1.26,1.53.In subgroup analyses,low levels of vitamin D were associated with both ischemic stroke(RR=1.35,95%CI:1.17,1.55)and hemorrhagic stroke(RR=1.70,95%CI:1.03,2.79).The funnel plot was asymmetric.Sensitivity analysis showed that one literature article had a significant impact on the results.There was a statistically significant correlation between low levels of vitamin D and cerebrovascular disease.Conclusion:Vitamin D levels are associated with both ischemic and hemorrhagic stroke.

关键词： Vitamin D cerebrovascular disease Meta-analysis,Ischemic stroke Hemorrhagic stroke

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An Analysis of Risk Factors Affecting cerebrovascular disease

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Health 2022年第8期14卷 866-882页

作者： Kazumitsu Nawata Hitotsubashi Institute for Advanced Study (HIAS) Hitotsubashi University Tokyo Japan

Background: cerebrovascular disease is a worldwide health problem. Stroke, a type of cerebrovascular disease, caused by sudden loss of blood flow to parts of the brain, is the world’s second-leading cause of death and third-leading cause of disability. It is critical to analyze risk factors to prevent cerebrovascular disease. Data and Methods: The risk factors for cerebrovascular disease were analyzed using data from 2,678,054 medical checkups obtained from the JMDC Claims Database. Logit models were used, and the odds ratio (OR) and confidence interval (CI) were calculated. The sample period was from January 2005 to September 2019. Results: Age and heart disease history were very important nonmodifiable factors. The OR comparing persons aged 70 to those aged 50 was 2.05 with a 95% CI of 1.92 - 2.05. A heart disease history was also an especially important factor (OR 2.29, 95% CI 2.18 - 2.41). Among the modifiable factors, triglyceride level and recent large weight change were very important factors, changing the risk of cerebrovascular disease by about 30%. Other significant modifiable factors were diastolic blood pressure, urine protein, having breakfast, walking ability and smoking;each of these changed the risk of cerebrovascular disease by about 10%. Taking medications to control hypertension, hyperglycemia and hypercholesterolemia respectively increased the risk of cerebrovascular disease. In particular, taking antihypertensive medications nearly doubled the risk (OR 1.93, 95% CI 1.86 - 2.00). Conclusion: It is very important for individuals with risk factors to improve their physical conditions to prevent cerebrovascular disease. Taking medications to control blood pressure, glucose level, and cholesterol might introduce risks for cerebrovascular disease. Since all medications have side effects, it is necessary to carefully manage the use of these medications to minimize the negative side effects. Limitations: The dataset was observatory. There were no experimental interventions. Further, the dataset conta

关键词： cerebrovascular disease Stroke Risk Factors Medication Side Effects

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The Mechanisms of Pei-yuan-Tong-nao Capsule as a Therapeutic Agent against cerebrovascular disease

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World Journal of Traditional Chinese Medicine 2020年第3期6卷 331-340页

作者： Yu Wei Xiao-Jing Fan Ming-Hui Zhang Mai-Qiu Wu Wei Li Ping Wang Wei Xiong Jian-Ping Lin State Key Laboratory of Medicinal Chemical Biology College of Pharmacy and Tianjin Key Laboratory of Molecular Drug ResearchNankai University Department of Cerebral Acupuncture The Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine Department of Neurology Dongzhimen HospitalBeijing University of Chinese MedicineBeijing Platform of Pharmaceutical Intelligence Tianjin International Joint Academy of Biomedicine The Henan Lingrui Pharmaceutical Co. Henan ProvinceChina Biodesign Center Tianjin Institute of Industrial BiotechnologyChinese Academy of SciencesTianjin

Objective:Pei-Yuan-Tong-Nao(PYTN)capsule has been widely used for the treatment of cerebrovascular disease(CVD),including cerebral ischemia.However,due to the complexity of traditional Chinese Medicine(TCM)and the lack of proper inspection methods,the pharmacological mechanisms of the actions of PYTN capsule on CVD remain ambiguous.In this investigation,a network pharmacology method was used to investigate the mechanism of action of PYTN capsule in the treatment of CVD.Methods:In this method,a chemical similarity ensemble approach was employed to predict putative targets for chemicals derived from PYTN capsule.Results:Thus,a total of 351 compounds and 650 proteins were identified as potential active ingredients and putative CVD-related targets.In addition,two interaction networks were constructed,including a network between putative targets of PYTN capsule and known CVD-related targets,and a network between candidate active compounds and putative CVD-related targets.Conclusion:The mechanism of PYTN capsule in the treatment of CVD was found to be based on three functional modules,namely,antioxidation,anti-inflammation,and antiapoptosis modules through multiple signaling pathways,such as PI3 K-Akt,mitogen-activated protein kinase,and TNF signaling pathways.We hope that this work can provide insight into the pharmacological mechanisms of TCMs in the treatment of CVD and provide a basis for further development and the discovery of more effective clinical strategies for the treatment of complicated diseases.

关键词： cerebrovascular disease mechanism network pharmacology Pei-Yuan-Tong-Nao traditional Chinese medicine

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