Cognition and influencing factors of secondary prevention in patients with stroke 1 year after discharge in southwest of China: A cross-sectional survey

Cognition and influencing factors of secondary prevention in patients with stroke 1 year after discharge in southwest of China: A cross-sectional survey | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Cognition and influencing factors of secondary prevention in patients with stroke 1 year after discharge in southwest of China: A cross-sectional survey Xuemin Zhong, Li Li, Qing Ye, Jian Wang, Lanying He, Changqing Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3935281/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: The risk of recurrent stroke is very high in patients with ischemic stroke (IS), but the implementation of secondary prevention of IS has not been paid enough attention. In this study, we aimed to investigate the cognition and compliance status of secondary prevention in patients with IS in Western China and explore the factors affecting compliance with secondary prevention 1 year after discharge. Methods : We conducted a cross-sectional survey of ischemic stroke patients 1 year after discharge in western Southwest China by convenience sampling. The patients were divided compliant and noncompliant groups, and differences in factors affecting compliance with secondary prevention between the two groups were analyzed. Results : A total of 1,041 patients were followed up in our study. Nearly one third of patients did not perform secondary prevention according tothe guidelines, and animprovement in lifestyle was even less likely. Livingwith or without children did not significantly affect patient compliance (OR,1.11; 95% CI, 0.83–1.49; P=0.47). Furthermore, there was no difference in the prevalence of risk factors between patients with one or two of the three cardiovascular diseases (hypertension, diabetes, and hyperlipidemia) and those with all three. Conclusions : Patients with IS had low compliance with secondary prevention. There is a particular lack of emphasis on lifestyle improvement. Further interventions are needed to improve compliance with secondary prevention in patients with IS, especiallypatients with all of three cardiovascular diseases (hypertension, diabetes, and hyperlipidemia). Ischemic stroke recurrence rate secondary prevention patient compliance lifestyle Figures Figure 1 1. Introduction Stroke is the second leading cause of death worldwide and the leading cause of death in China, where one-fifth of the world’s population resides [1,2]. The overall stroke recurrence rates for patients at 3, 6, and 12 months after onset are 12.3%, 15.5%, and 17.7%, respectively, and the stroke recurrence rate is >40% within 5 years [3,4]. Effective secondary prevention measures, including lifestyle improvements and prevention of risk factors can reduce ischemic stroke (IS) recurrence and mortality [5-7]. The incidence of IS is regional, and different regions within a country may have different incidence and recurrence rates of stroke owing to differences in race, geographical location, and living habits [8-11]. This study aimed to investigate the cognition and compliance status of secondary prevention in patients with IS in Western China and explore the factors affecting compliance with secondary prevention 1 year after discharge. 2. Methods 2.1 Study population We selected patients admitted for acute IS between June 2021 and June 2022 in Grade III and Class A public general hospitals in Chongqing and Chengdu, which are in the Southwest of China, using convenient sampling. The patients met the following diagnostic criteria for IS: age>18 years; the diagnosis of hospitalized IS met the diagnostic criteria of the Chinese Guidelines for the Diagnosis and Treatment of Acute Ischemic Stroke 2018 and was confirmed through head computed tomography (CT) or magnetic resonance imaging (MRI) [11] patients with a high risk of recurrence; complete medical records and contact information; patients or their families were willing to participate in the study and signed the informed consent form. Exclusion criteria were patient death during hospitalization; voluntary discharge; incomplete medical records, which hindered obtaining major indicators, such as previous medical history and imaging results of stroke; inability to communicate with investigators and family members owing to critical illness; refusal to participate in the survey. 2.2 Survey content We classified traditional risk factors such as smoking, hypertension, diabetes, hyperlipidemia, and lifestyle (attention to dietary diversity, low-salt diet, low-fat diet, physical activity appropriate to one's strength, and alcohol consumption) as preventable and controllable factors according to the Chinese Guidelines for the Secondary Prevention of Ischemic Stroke and Transient Ischemic Attack 2022 [12]. 2.3 Survey methods Hospitalization data survey: This involved collecting demographic information, such as age, sex, marital status, education level, and cardiovascular risk factors (smoking, drinking, hypertension, diabetes, and hyperlipidemia) through the patients' hospitalization records. Outpatient visits and information survey: patients or family members were contacted via telephone interviews by four experienced neurologists with unified training based on inpatient and outpatient electronic records. We investigated the following patient information: 1) general information: marital life status, whether they live with their children, and type of medical insurance; 2) control of risk factors: whether they quit smoking, are aware of their disease (including hypertension, diabetes, or hyperlipidemia history), or adhere to drug treatment (at a certain or previous observation point, the patient adhered to the prescription and took the discharge medication prescribed by the doctor; this is defined as drug compliance (yes if the patient changed to other drug types with the same effect such as changing the type of antihypertensive drug; no if they had not taken discharge medicine or other drug types with the same effect); 3) Lifestyle: whether they monitor the various dietary types (yes if they deliberately increased the consumption of whole grains, legumes, fruits, vegetables, and low-fat dairy products in daily life and reduced the intake of saturated and trans fatty acids; otherwise, no); whether they were on a low-salt diet (yes if they deliberately reduced sodium intake or replaced salt containing potassium; otherwise, no); whether they were on a low-fat diet (yes if fat intake was deliberately reduced; otherwise, no); whether they had appropriately enhanced activity; whether they abstained from alcohol; whether there was a regular follow-up and follow-up time interval. The follow-up period was between June and September 2023. 2.4 Statistical analysis Continuous variables are presented as means and standard deviations, and categorical variables are presented as counts and proportions. We used a t-test to detect statistical differences in continuous variables between compliant and noncompliant patients. Additionally, we used Fisher’s exact test to discern statistical differences in categorical variables among the two patient groups. Logistic regression was used to determine the risk factors associated with noncompliance with IS treatment. The logistic regression model was expressed as follows: where Y i is the dependent variable. Two variables were used to measure treatment compliance: adherence to follow-up procedures (1=Yes, 0=No). The above model was used to analyze the data for the two dependent variables. Patient i represents a vector of patient-level independent variables, including sex, age, marital status, type of medical insurance, and whether the patient lives with a child. β is a vector of the parameters of interest, exp( β ) represents the odds ratio (OR). Subsequently, we included indicators for hypertension, diabetes, and hyperlipidemia, along with their interaction terms in Model 1. This study aimed to evaluate whether patients diagnosed with multiple cardiovascular diseases (all three conditions) exhibit higher treatment compliance rates than those with one or two of these conditions. Patients with all three cardiovascular diseases were included in the reference group. Statistical analyses were performed using R version 4.1.2. 3. Results 3.1 Baseline characteristics A total of 1,041 patients were followed up in our study. The median age of the patients with regular follow-up at 1 year after discharge was 65.73 years, and the proportion of females was 35.7. The median age of patients with irregular follow-up was 68.01, and the proportion of females was 37.7. Additional general information is presented in Table 1. Table 1 Descriptive statistics a Variables follow-up No Yes P-value Age, mean (SD) 68.01 (11.45) 65.73 (11.71) 0.006 Sex=female, n (%) 101 (37.7) 277 (35.7) 0.609 Marital status, n (%) 0.449 Unmarried 2 (0.7) 7 ( 0.9) Married 248 (92.5) 699 (90.1) Widowed 14 (5.2) 62 (8.0) Divorced 4 (1.5) 8 (1.0) Insurance type, n (%) <0.001 UEBMI 177 (66.0) 394 (50.8) URBMI 67 (25.0) 225 (29.0) NCMS 21 (7.8) 138 (17.8) Self-payment 3 (1.1) 19 ( 2.4) living with children = Yes, n (%) 129 (48.1) 414 (53.4) 0.161 hypertension = Yes, n (%) 173 (64.6) 551 (71.0) 0.058 diabetes = Yes, n (%) 112 (41.8) 314 (40.5) 0.757 hyperlipidemia = Yes, n (%) 145 (54.1) 506 (65.2) 0.002 N 268 776 Abbreviations: NCMS=New Cooperative Medical Scheme, SD=standard deviation, URBMI=Urban Residents Basic Medical Insurance, UEBMI=Urban Employment Basic Medical Insurance. a For continuous variables, we used a t-test to estimate the P -value; for category variables, Fisher’s exact test was used. [Table 1 here] 3.2 Patient's knowledge of their illness There were 103, 19, and 45 patients diagnosed with diabetes, hypertension, and hyperlipidemia, respectively, who were unaware of their illness (Table 2). Table 2. Patient's knowledge of their illness Patient perception Diagnosis of medical record No Yes Diabetes No 281 103 Yes 39 621 Hypertension No 599 19 Yes 45 381 Hyperlipidemia no 348 45 yes 92 559 3.3 Secondary prevention in patients with acute non-cardiogenic stroke 1 year after discharge Regarding lifestyle, only 18.3% of patients with acute non-cardiogenic stroke combined with obesity lost weight. The proportion of patients with abstinence was 58.0%, 55.5% quit smoking, and less than 80% adhered to the three high levels of treatment and antithrombotic therapy (Table 3). Table 3 Compliance with risk factor prevention Variables Compliance rate（%） Alcohol abstinence 177/305 (58.0) Low-salt diet 774/1041 (74.4) Variety of dietary types 692/1041 (66.5) Enhanced activity 730/1041 (70.1) Weight loss 53/290 (18.3) Hypoglycemic therapy 326/424 (76.9) Antihypertensive therapy 566/723 (78.3) Hypolipidemic therapy 483/650 (74.3) Antiplatelet therapy 821/1041 (78.9) Smoking cessation 213/384 (55.5) Anticoagulant therapy 63/77 (81.8) Note: Rates of smoking cessation, alcohol abstinence, and weight loss were calculated by dividing the number of people who quit smoking, abstained from alcohol, and lost weight by the number of those who smoked, drank, and were obese. The adherence rates to treatment of hyperglycemia, hypertension, and hyperlipidemia were obtained by dividing the number of patients with hyperglycemia, hypertension, and hyperlipidemia by the number of those with hyperglycemia, hypertension, and hyperlipidemia. 3.4 Analysis of influencing factors on secondary prevention in patients with acute non-cardiogenic stroke 1 year after discharge The results of the logistic regression with follow-up as the dependent variable are presented in Table 4. The older the patient, the less likely they were to accept treatment (Odds ratio [OR]=0.99, 95% confidence interval [CI)]: 0.97, 0.99). Furthermore, patients under the New Cooperative Medical Scheme (NCMS) are more likely to accept treatment than those with Urban Employment Basic Medical Insurance (UEBMI) (OR=2.19, 95% CI: 1.34, 3.74). Patients with hypertension (OR=1.51, 95% CI: 1.11, 2.06) or hyperlipidemia (OR=1.49, 95% CI: 1.10, 2.01) were more likely to accept treatment. Table 4 Logistic regression results for follow-up variable Variables OR 95% CI P-value Intercept 5.33 (0.85, 47.13) 0.09 Age 0.99 (0.97, 0.99) 0.03 Sex (ref=male) 0.85 (0.62, 1.15) 0.28 Education level (ref= illiterate) Elementary school or below 0.57 (0.36, 0.90) 0.02 Junior high school or above 0.49 (0.30, 0.80) 0.01 Marital status (ref= unmarried) Married 1.23 (0.18, 5.54) 0.8 Widowed 2.07 (0.27, 10.72) 0.42 Divorced 0.88 (0.09, 6.56) 0.9 Insurance type (ref= UEBMI) URBMI 1.26 (0.88, 1.81) 0.21 NCMS 2.19 (1.34, 3.74) <0.001 Self-payment 1.75 (0.55, 7.84) 0.39 Living with children (ref=No) 1.11 (0.83, 1.49) 0.47 Hypertension (ref=No) 1.51 (1.11, 2.06) 0.01 Diabetes (ref=No) 1 (0.75, 1.34) 0.99 Hyperlipidemia (ref=No) 1.49 (1.1, 2.01) 0.01 Abbreviations: OR=Odds ratio; CI= Confidence interval; NCMS, new cooperative medical scheme; URBMI, urban residents’ basic medical insurance; UEBMI, urban employment basic medical insurance. [Table 4 here] 3.5 Correlation analysis of secondary prevention in patients with acute non-cardiogenic stroke complicated with "hypertension, diabetes, and hyperlipidemia" Figure 1 displays the ORs between patients with one or two of the three cardiovascular diseases (hypertension, diabetes, and hyperlipidemia) and those with all three. There were no statistically significant differences in the probability of treatment acceptance between patients experiencing one or two of the three cardiovascular diseases and those afflicted with all three, with treatment as the dependent variable (Fig 1a). There was no statistically significant differences in the probability of treatment acceptance between patients experiencing one or two of the three cardiovascular diseases and those afflicted with all three (Fig 1b), with follow-up as the dependent variable. The results align with those of Fig 1a. 4. Discussion Patients with IS had low compliance with secondary prevention. Second, living with or without children did not significantly affect patient compliance. Furthermore, there was no difference in the prevalence of risk factors between patients with one or two of the three cardiovascular diseases (hypertension, diabetes, and hyperlipidemia) and those with all three. Although these patients had already experienced an acute ischemic stroke (AIS), their adherence to secondary prevention was low. A previous study from the Chinese National Stroke Registry-II (CNSR-II) found that the compliance rates with antiplatelet, hypoglycemic, and antihypertensive drugs were 57.58%, 63.68%, and 61.90%, respectively, 1 year after discharge [1,7]. The results of the Adherence eValuation After Ischemic stroke–Longitudinal (AVAIL) study showed that the regimen persistence for secondary prevention medications at 12 months was 65.6% [13]. The patients surveyed in our study in 2023 had relatively high medication compliance compared with the CNSR-II study in 2018, which may be owing to the recent health education related to AIS. Adherence in western China is lower than that in developed countries. In the AVAIL study, the 12-month persistence was the highest for antihypertensive medications (87.9 %), followed by those of antiplatelet (87.1%), diabetes (82.3%), and lipid-lowering (77.6%) [13]. Other studies, such as Preventing Recurrence of Thromboembolic Events through Coordinated Treatment reported that antithrombotic and statin use was maintained at 98% and 99%, respectively at 1-year follow-up [14]. Another study conducted in Nova Scotia, Canada showed that patients with stroke had a self-reported persistence of 90% for all categories of stroke-prevention medications [15]. The Riks-Stroke Register [16] in Sweden found that persistence by medication category at 2-years post-discharge (56% for statins and 74% for antihypertensive drugs) was close to our 1-year follow-up results. Taking strong measures for the health education of secondary prevention of AIS is essential. Age and type of medical insurance affect outpatient follow-up. Similarly, previous studies found that age and type of medical insurance are factors that affect the medication compliance of patients with cerebral infarction after discharge [17-19]. Our study also found that the proportion of follow-up visits by insurance type of patients with new cooperative medical scheme was higher than that of other insurance types. The chronic disease management of community hospitals has ensured that patients with hypertension, diabetes and cerebral infarction are treated with special medical insurance for chronic diseases in community hospitals, and the reimbursement ratio is high. However, this may be related to the insurance type of urban residents’ basic medical insurance (URBMI) and UEBMI, who can visit the pharmacy to brush the medical insurance card to buy drugs and do not need to register at the hospital. Meanwhile, living with children did not promote regular follow-up. It may be related to young people's high work pressure and inadequate time to care for patients. Previous studies show that caregivers are important in patient compliance after discharge [20,21]. Furthermore, we found less emphasis on lifestyle improvements to prevent recurrent cerebral infarction than regular outpatient follow-up. More emphasis should be placed on high-value lifestyle interventions, which are always reasonable and effective treatments for patients with cerebral infarction, and their effect on improving dyslipidemia and reducing blood pressure, blood sugar, and cardiovascular risk is positive and should be used in all patients [22-25]. In addition to strengthening patients' medication compliance, lifestyle and health education should be strengthened. Consistent with previous studies, most patients with a history of hypertension and hyperlipidemia had regular follow-up [13,26]. Patients with one or two of the above three risk factors have a lower risk of cerebral infarction recurrence than those with IS having the above three risk factors; however, these patients do not closely monitor the prevention of lifestyle and risk factors in our study. Hypertension, hyperglycemia, and dyslipidemia have an evident tendency to aggregate and usually occur in pairs or triplets in the same patient, forming a "two-high" or "three-high" coexistence [27-29]. The risk of IS recurrence in patients with "three-highs" exponentially increases, and the implementation of "three-highs" co-management can produce good health and economic benefits [30,31] . Strengthening secondary prevention interventions for patients with cerebral infarction at three high levels is essential. Our study had some limitations. First, we could not analyze the education level of the patients. Second, we could not analyze from the perspective of doctors, hospitals, and patients' families. Third, we did not discuss whether to stop smoking and consuming alcohol before or after cerebral infarction. We discussed the secondary prevention of patients with cerebral infarction after discharge and did not compare it with the control of patients without cerebral infarction. 5. Conclusion The recurrence rate of cerebral infarction is high; however, nearly one third of patients do not perform secondary prevention per the guidelines, particularly for lifestyle improvement. In the future, strengthening the secondary prevention of health publicity for patients with cerebral infarction and their families is essential. Abbreviations AIS: acute ischemic stroke AVAIL: Adherence eValuation After Ischemic stroke–Longitudinal CI: confidence interval CNSR-II: Chinese National Stroke Registry-II CT: computed tomography IS: ischemic stroke MRI: magnetic resonance imaging NCMS: New Cooperative Medical Scheme OR: odds ratio SD: standard deviation UEBMI: Urban Employment Basic Medical Insurance URBMI: Urban Residents Basic Medical Insurance Declarations Ethics approval and consent to participate This study was approved by the Hospital Ethics Committee of Chengdu Second People's Hospital. Informed consent was obtained from all participants. Consent for publication No application. Availability of data and materials The dataset generated for this study can be obtained upon request from the corresponding author. Competing interests The authors declare that they have no competing interests. Funding Chengdu Science and Technology Bureau (Grant/Award Number: 2022-YF05-01776-SN). Author contributions Xuemin Zhong and Li Li were responsible for the concept and design of the study, data collection, and the first and final drafts of the paper. Qing Ye was responsible for the concept and design of the study, and data collection. Jian Wang, Changqing Li, and Lanying He were responsible for the study concept and design and interpretation. All authors have read and approved the final manuscript for publication. Acknowledgments The authors thank the Chengdu Science and Technology Bureau, Second People’s Hospital of Chengdu, all the patients with IS who cooperated with the investigation and the experts who helped in the design of this study. References Wu S, Wu B, Liu M, Chen Z, Wang W, Anderson CS, et al. Stroke in China: advances and challenges in epidemiology, prevention, and management. Lancet Neurol. 2019;18:394–405. https://doi.org/10.1016/S1474-4422(18)30500-3. Li Z, Jiang Y, Li H, Xian Y, Wang Y. China’s response to the rising stroke burden. 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Prevention of coronary and stroke events with atorvastatin in hypertensive patients who have average or lower-than-average cholesterol concentrations, in the Anglo-Scandinavian Cardiac Outcomes Trial–Lipid Lowering Arm (ASCOT-LLA): a multicentre randomised controlled trial. Lancet. 2003;361:1149–58. https://doi.org/10.1016/S0140-6736(03)12948-0. Additional Declarations No competing interests reported. Supplementary Files data.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3935281","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":273673547,"identity":"74f49c0b-c3f3-4bbe-8a7d-92bd1b17a0d2","order_by":0,"name":"Xuemin Zhong","email":"","orcid":"","institution":"The second affiliated hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xuemin","middleName":"","lastName":"Zhong","suffix":""},{"id":273673548,"identity":"691b06a5-e355-4a68-94e2-3942d55e39e5","order_by":1,"name":"Li Li","email":"","orcid":"","institution":"The second affiliated hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Li","suffix":""},{"id":273673549,"identity":"c2315eb2-a94c-4608-a4fe-83295b69335f","order_by":2,"name":"Qing Ye","email":"","orcid":"","institution":"The affiliated hospital of Southwest Jiaotong University \u0026 The Third People's Hospital of Chengdu","correspondingAuthor":false,"prefix":"","firstName":"Qing","middleName":"","lastName":"Ye","suffix":""},{"id":273673550,"identity":"074f3751-2bf8-4676-8814-a33aab39f7c2","order_by":3,"name":"Jian Wang","email":"","orcid":"","institution":"The Second Hospital of Chengdu","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Wang","suffix":""},{"id":273673551,"identity":"687efd40-c507-4a3a-a9e0-2ae50eda638d","order_by":4,"name":"Lanying He","email":"","orcid":"","institution":"The Second Hospital of Chengdu","correspondingAuthor":false,"prefix":"","firstName":"Lanying","middleName":"","lastName":"He","suffix":""},{"id":273673552,"identity":"ec995655-b036-4f7f-b65f-15c05067fb5d","order_by":5,"name":"Changqing Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIiWNgGAWjYBACPmYg8aFCor6fmfnwA6K0sAG1MM44Y8E4s50tzYA4LUDMzNtWwbjhPI+CBHFa2Jkf3uZhk2A2PszDYMBQYxNNhMPYjC3n8EiwmR3mPfCA4VhabgNhLUAr3khI8Jgd5kswYGw4TKQWHgMJCeNmIEm0FkmeBAkDA2bitQD9MuOARILEYWAgJxDjF37+ww9vfPxXl8Dff/jwgw81NoS1gAAiOhKIUY6qZRSMglEwCkYBNgAAELMzKmfXMbMAAAAASUVORK5CYII=","orcid":"","institution":"The second affiliated hospital of Chongqing Medical University","correspondingAuthor":true,"prefix":"","firstName":"Changqing","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-02-07 00:45:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3935281/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3935281/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51443485,"identity":"4921ad92-1114-4cc5-9619-b54d80453528","added_by":"auto","created_at":"2024-02-21 18:00:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":103709,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation analysis of secondary prevention in patients with acute non-cardiogenic stroke complicated with \"hypertension, diabetes and hyperlipidemia\"\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3935281/v1/d015d952303b7df8ac461a1e.png"},{"id":63067827,"identity":"6302d07e-6ce3-4097-bac0-0745eb666cd1","added_by":"auto","created_at":"2024-08-22 18:23:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":489132,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3935281/v1/485e9040-f295-4a8a-b457-2ac5dc9580bd.pdf"},{"id":51444960,"identity":"a2adae0d-432d-4cf4-9a19-8c112620b0f5","added_by":"auto","created_at":"2024-02-21 18:08:23","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16928,"visible":true,"origin":"","legend":"","description":"","filename":"data.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3935281/v1/ab1ce5f68615130cbd75c88a.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Cognition and influencing factors of secondary prevention in patients with stroke 1 year after discharge in southwest of China: A cross-sectional survey","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eStroke is the second leading cause of death worldwide and the leading cause of death in China, where one-fifth of the world\u0026rsquo;s population resides [1,2]. The overall stroke recurrence rates for patients at 3, 6, and 12 months after onset are 12.3%, 15.5%, and 17.7%, respectively, and the stroke recurrence rate is \u0026gt;40% within 5 years [3,4]. Effective secondary prevention measures, including lifestyle improvements and prevention of risk factors can reduce ischemic stroke (IS) recurrence and mortality [5-7]. The incidence of IS is regional, and different regions within a country may have different incidence and recurrence rates of stroke owing to differences in race, geographical location, and living habits [8-11]. This study aimed to investigate the cognition and compliance status of secondary prevention in patients with IS in Western China and explore the factors affecting compliance with secondary prevention 1 year after discharge.\u0026nbsp;\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e2.1 Study population\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;We selected patients admitted for acute IS between June 2021 and June 2022 in Grade III and Class A public general hospitals in Chongqing and Chengdu, which are in the Southwest of China, using convenient sampling.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe patients met the following diagnostic criteria for IS: age\u0026gt;18 years; the diagnosis of hospitalized IS met the diagnostic criteria of the Chinese Guidelines for the Diagnosis and Treatment of Acute Ischemic Stroke 2018 and was confirmed through head computed tomography\u0026nbsp;(CT) or magnetic resonance imaging\u0026nbsp;(MRI) [11]\u003csup\u003e\u0026nbsp;\u003c/sup\u003epatients with a high risk of recurrence; complete medical records and contact information; patients or their families were willing to participate in the study and signed the informed consent form.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eExclusion criteria were patient death during hospitalization; voluntary discharge; incomplete medical records, which hindered obtaining major indicators, such as previous medical history and imaging results of stroke; inability to communicate with investigators and family members owing to critical illness; refusal to participate in the survey.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2.2 Survey content\u003c/p\u003e\n\u003cp\u003eWe\u0026nbsp;classified traditional risk factors such as smoking, hypertension, diabetes, hyperlipidemia, and lifestyle (attention to dietary diversity, low-salt diet, low-fat diet, physical activity appropriate to one\u0026apos;s strength, and alcohol consumption) as preventable and controllable factors\u0026nbsp;according to the Chinese Guidelines for the Secondary Prevention of Ischemic Stroke and Transient Ischemic Attack 2022 [12].\u003c/p\u003e\n\u003cp\u003e2.3 Survey methods\u003c/p\u003e\n\u003cp\u003eHospitalization data survey: This involved collecting demographic information, such as age, sex, marital status, education level, and cardiovascular risk factors (smoking, drinking, hypertension, diabetes, and hyperlipidemia) through the patients\u0026apos; hospitalization records.\u003c/p\u003e\n\u003cp\u003eOutpatient visits and information survey: patients or family members were contacted via telephone interviews by four experienced neurologists with unified training\u0026nbsp;based on inpatient and outpatient electronic records.\u0026nbsp;We investigated the following patient information: 1) general information: marital life status, whether they live with their children, and type of medical insurance; 2) control of risk factors: whether they quit smoking, are aware of their disease (including hypertension, diabetes, or hyperlipidemia history), or adhere to drug treatment (at a certain or previous observation point, the patient adhered to the prescription and took the discharge medication prescribed by the doctor; this is defined as drug compliance\u0026nbsp;(yes if\u0026nbsp;the patient changed to other drug types with the same effect such as changing the type of antihypertensive drug; no if\u0026nbsp;they had not taken discharge medicine or other drug types with the same effect);\u0026nbsp;3) Lifestyle: whether they monitor the various dietary types (yes if they\u0026nbsp;deliberately\u0026nbsp;increased\u0026nbsp;the consumption of whole grains, legumes, fruits, vegetables, and low-fat dairy products in daily life and\u0026nbsp;reduced\u0026nbsp;the intake of saturated and trans fatty acids; otherwise, no); whether they were on a low-salt diet (yes\u0026nbsp;if they deliberately reduced sodium intake or replaced salt containing potassium; otherwise, no); whether they were on a low-fat diet (yes if fat intake was deliberately reduced; otherwise,\u0026nbsp;no); whether they had appropriately enhanced activity; whether they abstained from alcohol; whether there was a regular follow-up and follow-up time interval. The follow-up period was between June and September 2023.\u003c/p\u003e\n\u003cp\u003e2.4 Statistical analysis\u003c/p\u003e\n\u003cp\u003eContinuous variables are presented as means and standard deviations, and categorical variables are presented as counts and proportions. We used a t-test to detect statistical differences in continuous variables between compliant and noncompliant patients. Additionally, we used Fisher\u0026rsquo;s exact test to discern statistical differences in categorical variables among the two patient groups.\u003c/p\u003e\n\u003cp\u003eLogistic regression was used to determine the risk factors associated with noncompliance with IS treatment. The logistic regression model was expressed\u0026nbsp;as follows:\u003c/p\u003e\n\u003cp\u003e\u003cimg 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width=\"263\" height=\"76\"\u003e\u003c/p\u003e\n\u003cp\u003ewhere \u003cem\u003eY\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e is the dependent variable. Two variables were used to measure treatment compliance: adherence to follow-up procedures (1=Yes, 0=No). The above model was used to analyze the data for the two dependent variables. \u003cem\u003ePatient\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e represents a vector of patient-level independent variables, including sex, age, marital status, type of medical insurance, and whether the patient lives with a child. \u003cstrong\u003e\u0026beta;\u003c/strong\u003e is a vector of the parameters of interest, exp(\u003cem\u003e\u0026beta;\u003c/em\u003e) represents the odds ratio (OR).\u003c/p\u003e\n\u003cp\u003eSubsequently, we included indicators for hypertension, diabetes, and hyperlipidemia, along with their interaction terms in Model 1. This study aimed to evaluate whether patients diagnosed with multiple cardiovascular diseases (all three conditions) exhibit higher treatment compliance rates than those with one or two of these conditions. Patients with all three cardiovascular diseases were included in the reference group. Statistical analyses were performed using R version 4.1.2.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e3.1 Baseline characteristics\u003c/p\u003e\n\u003cp\u003eA total of 1,041 patients were followed up in our study. The median age of the patients with regular follow-up at 1 year after discharge was 65.73 years, and the proportion of females was 35.7. The median age of patients with irregular follow-up was 68.01, and the proportion of females was 37.7. Additional general information is presented in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003eDescriptive statistics\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"64%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.46341463414634%\" rowspan=\"2\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"58.53658536585366%\" colspan=\"3\"\u003e\n \u003cp\u003efollow-up\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.348837209302324%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.348837209302324%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.302325581395348%\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.57608695652174%\"\u003e\n \u003cp\u003eAge, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\"\u003e\n \u003cp\u003e68.01 (11.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\"\u003e\n \u003cp\u003e65.73 (11.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.119565217391305%\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.57608695652174%\"\u003e\n \u003cp\u003eSex=female, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\"\u003e\n \u003cp\u003e101 (37.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\"\u003e\n \u003cp\u003e277 (35.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.119565217391305%\"\u003e\n \u003cp\u003e0.609\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.57608695652174%\"\u003e\n \u003cp\u003eMarital status, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.119565217391305%\" rowspan=\"5\"\u003e\n \u003cp\u003e0.449\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.16393442622951%\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.918032786885245%\"\u003e\n \u003cp\u003e2 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.918032786885245%\"\u003e\n \u003cp\u003e7 ( 0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.16393442622951%\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.918032786885245%\"\u003e\n \u003cp\u003e248 (92.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.918032786885245%\"\u003e\n \u003cp\u003e699 (90.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.16393442622951%\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.918032786885245%\"\u003e\n \u003cp\u003e14 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.918032786885245%\"\u003e\n \u003cp\u003e62 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.16393442622951%\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.918032786885245%\"\u003e\n \u003cp\u003e4 (1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.918032786885245%\"\u003e\n \u003cp\u003e8 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.57608695652174%\"\u003e\n \u003cp\u003eInsurance type, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.119565217391305%\" rowspan=\"5\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.16393442622951%\"\u003e\n \u003cp\u003eUEBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.918032786885245%\"\u003e\n \u003cp\u003e177 (66.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.918032786885245%\"\u003e\n \u003cp\u003e394 (50.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.16393442622951%\"\u003e\n \u003cp\u003eURBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.918032786885245%\"\u003e\n \u003cp\u003e67 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.918032786885245%\"\u003e\n \u003cp\u003e225 (29.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.16393442622951%\"\u003e\n \u003cp\u003eNCMS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.918032786885245%\"\u003e\n \u003cp\u003e21 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.918032786885245%\"\u003e\n \u003cp\u003e138 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.16393442622951%\"\u003e\n \u003cp\u003eSelf-payment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.918032786885245%\"\u003e\n \u003cp\u003e3 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.918032786885245%\"\u003e\n \u003cp\u003e19 ( 2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.57608695652174%\"\u003e\n \u003cp\u003eliving with children = Yes, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\"\u003e\n \u003cp\u003e129 (48.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\"\u003e\n \u003cp\u003e414 (53.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.119565217391305%\"\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.57608695652174%\"\u003e\n \u003cp\u003ehypertension = Yes, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\"\u003e\n \u003cp\u003e173 (64.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\"\u003e\n \u003cp\u003e551 (71.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.119565217391305%\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.57608695652174%\"\u003e\n \u003cp\u003ediabetes = Yes, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\"\u003e\n \u003cp\u003e112 (41.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\"\u003e\n \u003cp\u003e314 (40.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.119565217391305%\"\u003e\n \u003cp\u003e0.757\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.57608695652174%\"\u003e\n \u003cp\u003ehyperlipidemia = Yes, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\"\u003e\n \u003cp\u003e145 (54.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\"\u003e\n \u003cp\u003e506 (65.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.119565217391305%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.57608695652174%\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\"\u003e\n \u003cp\u003e268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.652173913043477%\"\u003e\n \u003cp\u003e776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.119565217391305%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: NCMS=New Cooperative Medical Scheme, SD=standard deviation, URBMI=Urban Residents Basic Medical Insurance, UEBMI=Urban Employment Basic Medical Insurance. \u003csup\u003ea\u003c/sup\u003eFor continuous variables, we used a t-test to estimate the \u003cem\u003eP\u003c/em\u003e-value; for category variables, Fisher\u0026rsquo;s exact test was used.\u003c/p\u003e\n\u003cp\u003e[Table 1 here]\u003c/p\u003e\n\u003cp\u003e3.2 Patient\u0026apos;s knowledge of their illness\u003c/p\u003e\n\u003cp\u003eThere were 103, 19, and 45 patients diagnosed with diabetes, hypertension, and hyperlipidemia, respectively, who were unaware of their illness (Table 2).\u003c/p\u003e\n\u003cp\u003eTable 2. Patient\u0026apos;s knowledge of their illness\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"583\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.171232876712327%\" valign=\"top\" style=\"width: 28.7247%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.828767123287673%\" rowspan=\"2\" valign=\"top\" style=\"width: 28.0644%;\"\u003e\n \u003cp\u003ePatient perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.82876712328767%\" colspan=\"2\" valign=\"top\" style=\"width: 38.2996%;\"\u003e\n \u003cp\u003eDiagnosis of medical record\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.56164383561644%\" valign=\"top\" style=\"width: 28.7247%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.10502283105023%\" valign=\"top\" style=\"width: 27.5691%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.10502283105023%\" valign=\"top\" style=\"width: 10.7305%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.214408233276156%\" rowspan=\"2\" valign=\"top\" style=\"width: 28.7247%;\"\u003e\n \u003cp\u003eDiabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.871355060034304%\" valign=\"top\" style=\"width: 28.0644%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.871355060034304%\" valign=\"top\" style=\"width: 27.5691%;\"\u003e\n \u003cp\u003e281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.871355060034304%\" valign=\"top\" style=\"width: 10.7305%;\"\u003e\n \u003cp\u003e103\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.25688073394495%\" valign=\"top\" style=\"width: 28.0644%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.25688073394495%\" valign=\"top\" style=\"width: 27.5691%;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.25688073394495%\" valign=\"top\" style=\"width: 10.7305%;\"\u003e\n \u003cp\u003e621\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.214408233276156%\" valign=\"top\" style=\"width: 28.7247%;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.871355060034304%\" valign=\"top\" style=\"width: 28.0644%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.871355060034304%\" valign=\"top\" style=\"width: 27.5691%;\"\u003e\n \u003cp\u003e599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.871355060034304%\" valign=\"top\" style=\"width: 10.7305%;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.214408233276156%\" valign=\"top\" style=\"width: 28.7247%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.871355060034304%\" valign=\"top\" style=\"width: 28.0644%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.871355060034304%\" valign=\"top\" style=\"width: 27.5691%;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.871355060034304%\" valign=\"top\" style=\"width: 10.7305%;\"\u003e\n \u003cp\u003e381\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.95755517826825%\" valign=\"top\" style=\"width: 29.7152%;\"\u003e\n \u003cp\u003eHyperlipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.617996604414262%\" valign=\"top\" style=\"width: 28.0644%;\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.617996604414262%\" valign=\"top\" style=\"width: 27.5691%;\"\u003e\n \u003cp\u003e348\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.617996604414262%\" valign=\"top\" style=\"width: 10.7305%;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.214408233276156%\" valign=\"top\" style=\"width: 28.7247%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.871355060034304%\" valign=\"top\" style=\"width: 28.0644%;\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.871355060034304%\" valign=\"top\" style=\"width: 27.5691%;\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.871355060034304%\" valign=\"top\" style=\"width: 10.7305%;\"\u003e\n \u003cp\u003e559\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3.3 Secondary prevention in patients with acute non-cardiogenic stroke\u0026nbsp;1\u0026nbsp;year after discharge\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRegarding lifestyle, only 18.3% of patients with acute non-cardiogenic stroke combined with obesity lost weight. The proportion of patients with abstinence was 58.0%, 55.5% quit smoking, and less than 80% adhered to the three high levels of treatment and antithrombotic therapy (Table 3).\u003c/p\u003e\n\u003cp\u003eTable 3 Compliance with risk factor prevention\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.345794392523366%\" valign=\"top\" style=\"width: 49.6924%;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.654205607476634%\" valign=\"top\" style=\"width: 44.9656%;\"\u003e\n \u003cp\u003eCompliance rate（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.61878453038674%\" valign=\"top\" style=\"width: 49.6924%;\"\u003e\n \u003cp\u003eAlcohol abstinence\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.90791896869245%\" valign=\"top\" style=\"width: 50.2433%;\"\u003e\n \u003cp\u003e177/305\u0026nbsp;(58.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.61878453038674%\" valign=\"top\" style=\"width: 49.6924%;\"\u003e\n \u003cp\u003eLow-salt diet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.90791896869245%\" valign=\"top\" style=\"width: 50.2433%;\"\u003e\n \u003cp\u003e774/1041\u0026nbsp;(74.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.61878453038674%\" valign=\"top\" style=\"width: 49.6924%;\"\u003e\n \u003cp\u003eVariety of dietary types\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.90791896869245%\" valign=\"top\" style=\"width: 50.2433%;\"\u003e\n \u003cp\u003e692/1041\u0026nbsp;(66.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.61878453038674%\" valign=\"top\" style=\"width: 49.6924%;\"\u003e\n \u003cp\u003eEnhanced\u0026nbsp;activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.90791896869245%\" valign=\"top\" style=\"width: 50.2433%;\"\u003e\n \u003cp\u003e730/1041\u0026nbsp;(70.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.61878453038674%\" valign=\"top\" style=\"width: 49.6924%;\"\u003e\n \u003cp\u003eWeight loss\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.90791896869245%\" valign=\"top\" style=\"width: 50.2433%;\"\u003e\n \u003cp\u003e53/290\u0026nbsp;(18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.61878453038674%\" valign=\"top\" style=\"width: 49.6924%;\"\u003e\n \u003cp\u003eHypoglycemic therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.90791896869245%\" valign=\"top\" style=\"width: 50.2433%;\"\u003e\n \u003cp\u003e326/424\u0026nbsp;(76.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.61878453038674%\" valign=\"top\" style=\"width: 49.6924%;\"\u003e\n \u003cp\u003eAntihypertensive therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.90791896869245%\" valign=\"top\" style=\"width: 50.2433%;\"\u003e\n \u003cp\u003e566/723\u0026nbsp;(78.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.61878453038674%\" valign=\"top\" style=\"width: 49.6924%;\"\u003e\n \u003cp\u003eHypolipidemic therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.90791896869245%\" valign=\"top\" style=\"width: 50.2433%;\"\u003e\n \u003cp\u003e483/650\u0026nbsp;(74.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.61878453038674%\" valign=\"top\" style=\"width: 49.6924%;\"\u003e\n \u003cp\u003eAntiplatelet therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.90791896869245%\" valign=\"top\" style=\"width: 50.2433%;\"\u003e\n \u003cp\u003e821/1041\u0026nbsp;(78.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.61878453038674%\" valign=\"top\" style=\"width: 49.6924%;\"\u003e\n \u003cp\u003eSmoking\u0026nbsp;cessation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.90791896869245%\" valign=\"top\" style=\"width: 50.2433%;\"\u003e\n \u003cp\u003e213/384\u0026nbsp;(55.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.61878453038674%\" valign=\"top\" style=\"width: 49.6924%;\"\u003e\n \u003cp\u003eAnticoagulant therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.90791896869245%\" valign=\"top\" style=\"width: 50.2433%;\"\u003e\n \u003cp\u003e63/77\u0026nbsp;(81.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: Rates of smoking cessation, alcohol abstinence, and weight loss were calculated by dividing the number of people who quit smoking, abstained from alcohol, and lost weight by the number of those who smoked, drank, and were obese.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe adherence rates to treatment of hyperglycemia, hypertension, and hyperlipidemia were obtained by dividing the number of patients with hyperglycemia, hypertension, and hyperlipidemia by the number of those with hyperglycemia, hypertension, and hyperlipidemia.\u003c/p\u003e\n\u003cp\u003e3.4 Analysis of influencing factors on secondary prevention in patients with acute non-cardiogenic stroke 1 year after discharge\u003c/p\u003e\n\u003cp\u003eThe results of the logistic\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eregression with follow-up as the dependent variable are presented in Table 4.\u0026nbsp;The\u0026nbsp;older the patient, the less likely they were to accept treatment (Odds ratio [OR]=0.99, 95% confidence interval\u0026nbsp;[CI)]:\u0026nbsp;0.97, 0.99).\u0026nbsp;Furthermore, patients under the New Cooperative Medical Scheme\u0026nbsp;(NCMS) are more likely to accept treatment than those with Urban Employment Basic Medical Insurance (UEBMI)\u0026nbsp;(OR=2.19, 95% CI: 1.34,\u0026nbsp;3.74). Patients with hypertension (OR=1.51, 95% CI: 1.11,\u0026nbsp;2.06) or hyperlipidemia (OR=1.49, 95% CI: 1.10,\u0026nbsp;2.01) were more likely to accept treatment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u0026nbsp;\u003c/strong\u003eLogistic\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eregression results for follow-up variable\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\"\u003e\n \u003cp\u003e5.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\"\u003e\n \u003cp\u003e(0.85, 47.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\"\u003e\n \u003cp\u003e(0.97, 0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eSex (ref=male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\"\u003e\n \u003cp\u003e(0.62, 1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eEducation level (ref= illiterate)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eElementary school or below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\"\u003e\n \u003cp\u003e(0.36, 0.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eJunior high school or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\"\u003e\n \u003cp\u003e(0.30, 0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eMarital status (ref=\u0026nbsp;unmarried)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\"\u003e\n \u003cp\u003e(0.18, 5.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\"\u003e\n \u003cp\u003e2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\"\u003e\n \u003cp\u003e(0.27, 10.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\"\u003e\n \u003cp\u003e(0.09, 6.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eInsurance type (ref= UEBMI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eURBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\"\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\"\u003e\n \u003cp\u003e(0.88, 1.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eNCMS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\"\u003e\n \u003cp\u003e2.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\"\u003e\n \u003cp\u003e(1.34, 3.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eSelf-payment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\"\u003e\n \u003cp\u003e(0.55, 7.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eLiving with children (ref=No)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\"\u003e\n \u003cp\u003e(0.83, 1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eHypertension (ref=No)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\"\u003e\n \u003cp\u003e1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\"\u003e\n \u003cp\u003e(1.11, 2.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eDiabetes (ref=No)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\"\u003e\n \u003cp\u003e(0.75, 1.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.77855887521968%\"\u003e\n \u003cp\u003eHyperlipidemia (ref=No)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.017574692442881%\"\u003e\n \u003cp\u003e1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.0896309314587%\"\u003e\n \u003cp\u003e(1.1, 2.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.114235500878735%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: OR=Odds ratio; CI= Confidence interval; NCMS, new cooperative medical scheme; URBMI, urban residents\u0026rsquo; basic medical insurance; UEBMI, urban employment basic medical insurance.\u003c/p\u003e\n\u003cp\u003e[Table\u0026nbsp;4\u0026nbsp;here]\u003c/p\u003e\n\u003cp\u003e3.5 Correlation analysis of secondary prevention in patients with acute non-cardiogenic stroke complicated with \u0026quot;hypertension, diabetes, and hyperlipidemia\u0026quot;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 1 displays the ORs between patients with one or two of the three cardiovascular diseases (hypertension, diabetes, and hyperlipidemia) and those with all three. There were no statistically significant differences in the probability of treatment acceptance between patients experiencing one or two of the three cardiovascular diseases and those afflicted with all three, with treatment as the dependent variable (Fig 1a). There was no statistically significant differences in the probability of treatment acceptance between patients experiencing one or two of the three cardiovascular diseases and those afflicted with all three (Fig 1b), with follow-up as the dependent variable. The results align with those of Fig 1a.\u0026nbsp;\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003ePatients\u0026nbsp;with IS had low compliance with secondary prevention. Second, living with or without children did not significantly affect patient compliance.\u0026nbsp;Furthermore, there was no difference in the prevalence of risk factors between patients with one or two of the three cardiovascular diseases (hypertension, diabetes, and hyperlipidemia) and those with all three.\u003c/p\u003e\n\u003cp\u003eAlthough\u0026nbsp;these patients had already experienced an acute ischemic stroke (AIS), their adherence to secondary prevention was\u0026nbsp;low. A previous study from the Chinese National Stroke Registry-II (CNSR-II) found that the compliance rates with antiplatelet, hypoglycemic, and antihypertensive drugs were 57.58%,\u0026nbsp;63.68%, and 61.90%, respectively,\u0026nbsp;1\u0026nbsp;year after discharge\u003csup\u003e\u0026nbsp;\u003c/sup\u003e[1,7]. The results of the Adherence eValuation After Ischemic stroke\u0026ndash;Longitudinal (AVAIL) study showed that the regimen persistence for secondary prevention medications at 12 months was 65.6% [13].\u0026nbsp;The\u0026nbsp;patients surveyed in our study in 2023 had relatively high medication compliance\u0026nbsp;compared with the CNSR-II study in 2018, which may be owing to the recent health education related to AIS. Adherence in western China is lower than that in developed countries. In the AVAIL study, the 12-month persistence was the highest for antihypertensive medications (87.9 %), followed by those of antiplatelet (87.1%), diabetes (82.3%), and lipid-lowering (77.6%) [13]. Other studies, such as Preventing Recurrence of Thromboembolic Events through Coordinated Treatment reported that antithrombotic\u0026nbsp;and statin\u0026nbsp;use was maintained at 98% and 99%, respectively\u0026nbsp;at\u0026nbsp;1-year follow-up [14].\u0026nbsp;Another\u0026nbsp;study conducted in Nova Scotia, Canada\u0026nbsp;showed that\u0026nbsp;patients with stroke had a self-reported persistence of 90% for all categories of stroke-prevention medications [15]. The Riks-Stroke Register [16] in Sweden found that persistence by medication category at\u0026nbsp;2-years post-discharge (56% for statins and 74% for antihypertensive drugs) was close to our\u0026nbsp;1-year follow-up results. Taking strong measures for the health education of secondary prevention of AIS is essential.\u003c/p\u003e\n\u003cp\u003eAge and type of medical insurance affect outpatient follow-up. Similarly, previous studies found that age and type of medical insurance are factors that affect the medication compliance of patients with cerebral infarction after discharge [17-19]. Our study also found that the proportion of follow-up visits by insurance type of patients with new cooperative medical scheme was higher than that of other insurance types. The chronic disease management of community hospitals has ensured that patients with hypertension, diabetes and cerebral infarction are treated with special medical insurance for chronic diseases in community hospitals, and the reimbursement ratio is high. However, this may be related to the insurance type of urban residents\u0026rsquo; basic medical insurance (URBMI) and\u0026nbsp;UEBMI,\u0026nbsp;who can visit the pharmacy to brush the medical insurance card to buy drugs and do not need to register at the hospital.\u0026nbsp;Meanwhile,\u0026nbsp;living with children did not promote regular follow-up. It may be related to young people\u0026apos;s high work pressure and inadequate time to care for patients. Previous studies\u0026nbsp;show\u0026nbsp;that caregivers are important in patient compliance after discharge [20,21]. Furthermore, we found less emphasis on lifestyle improvements to prevent recurrent cerebral infarction than regular outpatient follow-up. More emphasis should be placed on high-value lifestyle interventions, which are always reasonable and effective treatments for patients with cerebral infarction, and their effect on improving dyslipidemia and reducing blood pressure, blood sugar, and cardiovascular risk is positive and should be used in all patients [22-25]. In addition to strengthening patients\u0026apos; medication compliance, lifestyle and health education should be strengthened.\u003c/p\u003e\n\u003cp\u003eConsistent with previous studies, most patients with a history of hypertension and hyperlipidemia had regular follow-up [13,26]. Patients with one or two of the above three risk factors have a lower risk of cerebral infarction recurrence than those with IS having the above three risk factors; however, these patients do not closely monitor the prevention of lifestyle and risk factors in our study. Hypertension, hyperglycemia,\u0026nbsp;and dyslipidemia have an evident tendency to aggregate and usually occur in pairs or triplets in the same patient, forming a \u0026quot;two-high\u0026quot; or \u0026quot;three-high\u0026quot; coexistence [27-29]. The risk of IS recurrence in patients with \u0026quot;three-highs\u0026quot; exponentially\u0026nbsp;increases, and the implementation of \u0026quot;three-highs\u0026quot; co-management can produce good health and economic benefits [30,31]\u003csup\u003e.\u003c/sup\u003e Strengthening secondary prevention interventions for patients with cerebral infarction at three high levels is essential.\u003c/p\u003e\n\u003cp\u003eOur study had some limitations. First, we\u0026nbsp;could not\u0026nbsp;analyze the education level of the patients. Second, we could not analyze from the perspective of doctors, hospitals, and patients\u0026apos; families.\u0026nbsp;Third, we did not discuss whether to stop smoking and consuming alcohol before or after cerebral infarction.\u0026nbsp;We\u0026nbsp;discussed the secondary prevention of patients with cerebral infarction after discharge and did not compare it with the control of patients without cerebral infarction.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe recurrence rate of cerebral infarction is high; however, nearly one third of patients do not perform secondary prevention per the guidelines, particularly for lifestyle improvement. In the future, strengthening the secondary prevention of health publicity for patients with cerebral infarction and their families is essential.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAIS: acute ischemic stroke\u003c/p\u003e\n\u003cp\u003eAVAIL: Adherence eValuation After Ischemic stroke\u0026ndash;Longitudinal\u003c/p\u003e\n\u003cp\u003eCI: confidence interval\u003c/p\u003e\n\u003cp\u003eCNSR-II: Chinese National Stroke Registry-II\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCT: computed tomography\u003c/p\u003e\n\u003cp\u003eIS: ischemic stroke\u003c/p\u003e\n\u003cp\u003eMRI: magnetic resonance imaging\u003c/p\u003e\n\u003cp\u003eNCMS: New Cooperative Medical Scheme\u003c/p\u003e\n\u003cp\u003eOR: odds ratio\u003c/p\u003e\n\u003cp\u003eSD: standard deviation\u003c/p\u003e\n\u003cp\u003eUEBMI: Urban Employment Basic Medical Insurance\u003c/p\u003e\n\u003cp\u003eURBMI: Urban Residents Basic Medical Insurance\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Hospital Ethics Committee of Chengdu Second People\u0026apos;s Hospital. Informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo application.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe dataset generated for this study can be obtained upon request from the corresponding author.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eChengdu Science and Technology Bureau\u0026nbsp;(Grant/Award Number: 2022-YF05-01776-SN).\u003c/p\u003e\n\u003cp\u003eAuthor contributions\u003c/p\u003e\n\u003cp\u003eXuemin Zhong and Li Li were responsible for the concept and design of the study, data collection, and the first and final drafts of the paper.\u0026nbsp;Qing Ye was responsible for the concept and design of the study,\u0026nbsp;and\u0026nbsp;data collection.\u0026nbsp;Jian Wang, Changqing Li, and Lanying He were responsible for the study concept and design and interpretation. All\u0026nbsp;authors\u0026nbsp;have read and approved the final manuscript for publication.\u003c/p\u003e\n\u003cp\u003eAcknowledgments\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors thank the Chengdu Science and Technology Bureau, Second People\u0026rsquo;s Hospital of Chengdu, all the patients with IS who cooperated with the investigation and the experts who helped in the design of this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWu S, Wu B, Liu M, Chen Z, Wang W, Anderson CS, et al. Stroke in China: advances and challenges in epidemiology, prevention, and management. Lancet Neurol. 2019;18:394\u0026ndash;405. https://doi.org/10.1016/S1474-4422(18)30500-3.\u003c/li\u003e\n\u003cli\u003eLi Z, Jiang Y, Li H, Xian Y, Wang Y. China\u0026rsquo;s response to the rising stroke burden. BMJ. 2019;364:l879. https://doi.org/10.1136/bmj.l879.\u003c/li\u003e\n\u003cli\u003eDu W, Zhao X, Wang Y, Pan Y, Liu G, Wang A, et al. 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Lancet. 2003;361:1149\u0026ndash;58. https://doi.org/10.1016/S0140-6736(03)12948-0.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Ischemic stroke, recurrence rate, secondary prevention, patient compliance, lifestyle","lastPublishedDoi":"10.21203/rs.3.rs-3935281/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3935281/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e The risk of recurrent stroke is very high in patients with ischemic stroke (IS), but the implementation of secondary prevention of IS has not been paid enough attention. In this study, we aimed to investigate the cognition and compliance status of secondary prevention in patients with IS in Western China and explore the factors affecting compliance with secondary prevention 1 year after discharge.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: We conducted a cross-sectional survey of ischemic stroke patients 1 year after discharge in western Southwest China by convenience sampling. The patients were divided compliant and noncompliant groups, and differences in factors affecting compliance with secondary prevention between the two groups were analyzed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: A total of 1,041 patients were followed up in our study. Nearly one third of patients did not perform secondary prevention according tothe guidelines, and animprovement in lifestyle was even less likely. Livingwith or without children did not significantly affect patient compliance (OR,1.11; 95% CI, 0.83–1.49; P=0.47). Furthermore, there was no difference in the prevalence of risk factors between patients with one or two of the three cardiovascular diseases (hypertension, diabetes, and hyperlipidemia) and those with all three.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: Patients with IS had low compliance with secondary prevention. There is a particular lack of emphasis on lifestyle improvement. Further interventions are needed to improve compliance with secondary prevention in patients with IS, especiallypatients with all of three cardiovascular diseases (hypertension, diabetes, and hyperlipidemia).\u003c/p\u003e","manuscriptTitle":"Cognition and influencing factors of secondary prevention in patients with stroke 1 year after discharge in southwest of China: A cross-sectional survey","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-21 18:00:17","doi":"10.21203/rs.3.rs-3935281/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3fdce53e-4da7-43c9-bda5-d7d41b573bdf","owner":[],"postedDate":"February 21st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-08-22T18:15:09+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-21 18:00:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3935281","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3935281","identity":"rs-3935281","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}