Stroke types, risk factors, clinical features and outcomes in a tertiary hospital, Myanmar, a descriptive study

Stroke types, risk factors, clinical features and outcomes in a tertiary hospital, Myanmar, a descriptive study | 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 Stroke types, risk factors, clinical features and outcomes in a tertiary hospital, Myanmar, a descriptive study Thant Zin Tun, Su Myat Han, Kazuhiko Moji, Mitsuaki Matsui This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3810130/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Mar, 2024 Read the published version in Tropical Medicine and Health → Version 1 posted 5 You are reading this latest preprint version Abstract Background Stroke is one of the leading causes of death and majority of the stroke burden was observed in middle- and low-income countries. Understanding the risk factors, complications and outcomes is useful in healthcare planning and resource allocation. However, little information on stroke is available in Myanmar. Methods A review of medical records of stroke admission during 2017 in a tertiary hospital was conducted. Final diagnosis, risk factors, clinical features, complications and outcomes were systematically collected both from computer-based and from paper-based medical records. Results 1153 cases were identified, and 977 cases were analysed. Haemorrhagic stroke was the most common type (48.8%), followed by ischaemic stroke (43.4%). Unimproved cases were 31.5%. Identified risk factors of unimproved were 'haemorrhagic stroke' [adjusted odds ratio (aOR): 1.67], 'having fever during hospitalisation' [aOR: 2.53], and 'Glasgow Coma Scale at the admission between 9 and 14 [aOR: 4.64], and less than 9 [aOR: 42.37]. Conclusion Intracranial haemorrhage and unconsciousness were significantly associated with poor prognosis. Fever during the hospitalisation, which was also a risk factor of unimproved cases, could be associated with aspiration pneumonia. This could be an associated symptom of unconsciousness. The findings imply how to prevent and control fever among stroke patients during hospital stay is a key for better prognosis. Stroke Hypertension Myanmar risk factors of stroke Figures Figure 1 Figure 2 Figure 3 Background Stroke is characterized as sudden onset of loss of focal neurological function due to infarction or haemorrhage in the central nervous system.[1] It is caused by the interruption of blood supply to culprit lesion of the brain, which is either by haemorrhage or embolism at certain part of blood vessel.[2] Despite the progress of prevention and treatment against stroke, it is the 2 nd leading cause of adult deaths in the world, and the 4 th leading cause of deaths in low-income countries in 2019.[3] A majority of the stroke burden was observed in developing countries, accounting for 75.2% of all stroke-related deaths and 81.0% of the associated DALYs lost.[4] Epidemiological studies on stroke's prevalence, and its associated factors enable us to understand the disease epidemiology and its prevention strategies. The risk factors can be categorized broadly into dnon-modifiable and modifiable factors. Age, gender, race, ethnicity, and heredity are among the non-modifiable factors, while hypertension, atrial fibrillation, dyslipidaemia, diabetes, cigarette smoking, physical inactivity, carotid stenosis, transient ischemic attack, and other cardiac disorders are modifiable risk factors. However, studies on factors related to strokes prevalence are notably lacking in resource-limited settings. Although stroke is becoming a major health problem in low- and middle-income countries, there are few available data on stroke in Myanmar. Very limited information is available on the demography, risk factors and burden of stroke in Myanmar. Therefore, this study aims to assess the type of stroke, the risk factors, clinical features and outcomes of stroke patients admitted to a top referral hospital in Myanmar. Methods Study site, setting and population This study was conducted in a 1,000-bedded General Hospital, in the capital city Nay Pyi Taw, Myanmar. It is one of the highest-level referral hospitals in Myanmar, and the only hospital with neurology and neurosurgical units in Nay Pyi Taw. We retrospectively identified the cases admitted to the hospital by reviewing the hospital medical records for International Classification of Diseases, tenth revision (ICD-10), with stroke coded for (I60: non-traumatic subarachnoid haemorrhagic, I61: non-traumatic intracerebral haemorrhagic, I62: other and unspecified intracranial haemorrhagic, I63: cerebral infarction, I64: stroke, not specified as haemorrhagic or infarction, I69: sequelae of cerebrovascular diseases). All stroke diagnosed patients admitted to the hospital between 1st January to 31st December 2017 were eligible for this study. Data collection and outcomes The following data were extracted from the Computer Assisted Medical Record System (CAMRS) database and paper-based medical records: admission and discharge date, duration of hospital stay, discharge status (D/C: normal discharged due to recovered or improved, Expired: patients who died during hospital stay, Signed and Left (S/L): patients or family who signed on the statement that they did not want to receive any more treatment and it was their own will and leave the hospital, Absconded (Abs): leave the hospital without any notice to the hospital authority), age, sex and address. In addition to the clinical features, a variety of factors were evaluated through the review of medical records. These included stroke types - ischemic stroke, haemorrhagic stroke (i.e. intra-cranial haemorrhage, ICH; or sub-arachnoid haemorrhage, SAH) - as determined by the diagnosing physician. Additionally, risk factors such as the patient's medical history of hypertension, diabetes mellitus, cardiovascular diseases, previous stroke or transient ischemic attack (TIA), smoking habits, alcohol consumption, and betel chewing were extracted. Statistical analysis Categorical variables are described as count (percentage) and chi-square test was used for analysis. Continuous variables are described either as median with interquartile range or mean with standard deviation; and analysed using Mann-Whitney U test or Student’s t-test as appropriate. Missing data were ignored. For the outcome variable, patients were categorised into two groups which were improved (normal discharge) and unimproved (non-normal discharge). Improved patients were patients who were discharged from hospital with good clinical outcome. Unimproved patients included expired cases, signed and leave (S/L) cases, and absconded (Abs) cases. S/L and Abs were assumed as not improved because most of the cases were considered as ‘hopeless’ by the family members, so that they had not received enough care as stroke cases need continuous support. A multiple logistic regression model was applied to identify factors associated with the unimproved stroke outcome. The type of stroke, history of hypertension, diabetes, and previous stroke, Glasgow Coma Scale (GCS) at the time of admission, and fever during the hospital stay were considered as confounding factors in the multiple logistic regression. Stata (IC version 15.1) and Microsoft Excel (version 16.26) were used for data analysis. Results General characteristics of the stroke patients A total of 1,153 stroke patients were identified, and 176 cases were removed from the analysis due to incomplete medical records; therefore, 977 cases were analysed. Table 1 describes the characteristics of the admitted stroke patients. Majority of the cases were male (60.8%), living in rural area (65.3%). One-third of the cases (314 patients) were referred from other hospitals or health care facilities. Hypertension was the most common risk factor among the stroke patients (79.7%) followed by tobacco usage (26.4%) and regular alcohol consumption (20.6%). CT scan results were recorded in 94% of the cases (918 patients). Haemorrhagic stroke (48.8%, 477 patients) was the most common type of stroke, and intracranial haemorrhage (ICH) was dominant (453 cases) followed by subarachnoid haemorrhage (SAH) (13 cases) and both ICH and SAH (11 cases). Approximately seven in ten cases discharged normally (improved). Seasonal fluctuations were observed in the number of the admission (Figure 1). April and November had the highest admission numbers (99 and 98 admissions, respectively), and July had the lowest (50 admissions). Coverage area was wide that were from Mandalay Region (45.1%) followed by Bago Region (18.4%), Magway Region (18.1%), Nay Pyi Taw Union Territory (16.2%) (Figure 2). 80.9% of ischaemic and 54.5% of haemorrhagic stroke patients were discharged with clinical improvement. 41.9% and 23.4 % of haemorrhagic and ischaemic stroke patients respectively were referred from other health facilities (p <0.01). Characteristic of improved versus unimproved patients Table 2 shows characteristic, risk factors, clinical features, and complications among improved and unimproved patients. The proportion of improved outcome was higher among the patients who were admitted directly to the hospital than those referred from other health facilities (p< 0.01). Unimproved patients exhibited a higher prevalence of hypertension (p< 0.01), whereas a history of previous stroke or TIA was more common in improved patients (p< 0.01). The improved patients had lower admission blood pressure and blood sugar levels compared to unimproved patients (p < 0.01). The median Glasgow Coma Scale (GCS) score at the time of admission was 15 for improved patients and 8 for unimproved patients (p < 0.01). Presence of fever and aspiration pneumonia during hospital stay (p = 0.01) was more common in unimproved patients. Improved patients had longer hospital stays compared to their unimproved counterpart (p <0.01). Risk factors association with unimproved stroke outcome Results from univariate logistic regression showed that haemorrhagic stroke patients were associated with unimproved outcome (OR 3.53, 95% CI 2.61 – 4.78). (Table 3) Among the risk factors, hypertension was associated with unimproved outcome (OR 1.62, 95% CI 1.13 – 2.32). Patients with admission GCS lower than 14 were likely to have unimproved outcome (OR 6.37, 95% CI 4.27 – 9.50 for GCS 9-14; OR 59.20, 95% CI 36.29 – 96.60 for GCS <9). Fever (OR 4.82, 95% CI 3.61 – 6.44) and aspiration pneumonia (OR 2.08, 95% CI 1.16 – 3.72) were two complications which were associated with unimproved outcome. Patients who were referred from other health facilities were less likely to improve (OR 1.53, 95% CI 1.15 – 2.03). Patients who had suffered previous stroke/TIA were more likely to improve (OR 0.36, 95% CI 0.20 – 0.63). Systolic blood pressure > 150 mmHg at the time of admission (OR 1.43, 95% CI 1.08 – 1.90) and blood sugar level > 200mg/dl at the time of admission (OR 1.50, 95% CI 1.09 – 2.06) were less likely to improve. Results from the multivariate analysis indicated that haemorrhagic stroke (Adjusted Odd Ratios: AOR 1.66, 95% CI 1.11 – 2.50), development of fever during the hospital stay (AOR 2.53, 95% CI 1.72 – 3.71), and lower GCS levels (AOR 4.64, 95% CI 2.94 – 7.02 for GCS 9-14 and AOR 42.37, 95% CI 25.13 – 71.43 for GCS <9) were associated with a poor prognosis (Figure 3) Hypertension was associated with unimproved outcome in bivariate analysis; however, this significance was not observed in multivariate analysis (AOR 1.45, 95% CI 0.89 – 2.38). (Figure 3) DISCUSSION This is a first study about the stroke types, risk factors, clinical features, and outcomes among hospitalised patients in Myanmar. Key finding is that haemorrhagic stroke, low GCS at the admission, and signs of secondary infection were associated with poor prognosis. Out of haemorrhagic stroke cases, most were ICH and 45.5% were poor prognosis. This finding was in accordance with what Andersen and colleague [ 5 ], which also reported the severity and higher risk of death among the haemorrhagic stroke patients compared to ischaemic stroke. The same study also stated that case fatality of ICH was 40% at one month and 54% at one year, which is also consistent with our finding. [ 5 ] In this study, among the stroke admissions, hypertension was the most common risk factor. The prevalence of hypertension among the stroke cases was one of the highest among South, East and South-East Asia. [ 4 ] For acute stroke, hypertension is a major risk factor and maintaining optimal blood pressure during the management of stroke is also important for the outcome.[ 6 ] In this study, the history of previous stroke and TIA was observed in 10% of stroke cases and more common in patients with ischaemic stroke. It is reported that 7.4% of TIA patients develops stroke within 90 days of the attack.[ 7 ] The follow up system of the patients with management of risk factors should be established. Conscious level at the admission assessed by GCS was a good predictor of prognosis in this study, as it has been shown elsewhere.[ 8 ] In our study, admission GCS among improved patients was significantly higher than admission GCS among unimproved patients. This finding was compatible with the studies done in Nigeria.[ 9 , 10 ] This is due to the nature of the diseases itself, as haemorrhage causes increased intracranial pressure by haematoma, perihaematomal oedema, and intraventricular extension.[ 11 ] Having fever was revealed as predictor of poor prognosis. This finding was compatible with the result of meta-analysis which reported fever as consistent association with worse outcome whether of either ischaemic or haemorrhagic stroke.[ 12 ] Fever is a sign of infection, and it is known that stroke patients frequently experiences infections. The main causes of infection are aspiration pneumonia, and infections caused by common commensal bacteria due to bacterial translocation.[ 13 ] Therefore, consolidation in infection control including appropriate application of antibiotics could be a possible contributor to improve the prognosis. As it is not integrated yet into stroke management in Myanmar, standardised management procedure should be established. The median duration of hospital stay was 4 days which was similar to the result of a study done in this hospital in 2016 [ 14 ] and results from a study of stroke epidemiology in Thailand [ 15 ] and shorter than in Ethiopia.[ 16 ] There was no significant difference between duration of hospital stay in ischaemic and haemorrhagic stroke. However, the duration of hospital stays among the improved patients was longer than the patients who were not improved. S/L and absconded cases were classified as unimproved cases in the analysis, and this may be one of the reasons of longer hospital stays among the improved patients. The proportion of the S/L (25.2%) were higher than the earlier year (15.5%) .[ 14 ] In Myanmar, no health insurance system exists, and the OOP payment for the health care services were high.[ 17 ] Moreover, the opportunity costs such as absence from work as the duration of hospital stays became longer may be one the challenges of the reasons of S/L or absconded. In this study, we were not able to include the income status of the stroke patients and thus it was not possible to assess the income status of those S/L and absconded cases. In this study, the haemorrhagic stroke was the most common type of stroke (48.8%). This is contrary to studies in other countries, which reported that ischaemic stroke as the common type.[ 9 , 15 , 16 , 18 , 19 ] This difference could be due to selection bias of the study setting. The Nay Pyi Taw General Hospital is one of the only four hospitals in the country with neurology departments and Neurosurgical departments for the optimal care of the haemorrhagic stroke cases. As ischemic stroke cases were mostly managed at the other hospitals, relatively higher proportion of haemorrhagic stroke cases may be observed in the current study. Despite this difference in the study population, the finding of analysis on poor prognosis will be still valid. Conclusion Stroke is more common among the older age group population in Myanmar, and haemorrhagic stroke is the most common type among the hospitalised stroke patients. Hypertension is the most common risk factor for both types of strokes (Ischemic and haemorrhagic). It is important to raise awareness among the population on the risk factor of strokes, and the prevention measures against the stroke. It is also important to increase the number of stroke units within the country to cover the wider geographical population of Myanmar. Abbreviations Abs: Absconded AOR: Adjusted Odds Ratio CAMRS: Computer Assisted Medical Record System CT Scan: Computed Tomography Scan D/C: Normal Discharged (improved) DALY: Disability-adjusted Life Year DBP: Diastolic Blood Pressure DM: Diabetes Mellitus GCS: Glasgow Coma Scale ICD: International Classification of Diseases ICH: Intracerebral Haemorrhagic OR: Odds Ratio S/L: Signed and Left SAH: Subarachnoid Haemorrhagic SBP: Systolic Blood Pressure TIA: Transient Ischaemic Attack WHO: World Health Organization Declarations ACKNOWLEDGEMENTS Thant Zin Tun acknowledged the scholarship from Japanese Grant Aid for Human Resource Development (JDS), the government of Japan. The authors thanks to medical superintendents, staffs and all patients of 1,000 Bedded General Hospital, for giving permission and especially staffs from the medical record department for the supporting the data collection. Special thanks to Dr. Han Win Naing who helped in extraction of the clinical data from the medical records. Ethics approval This research was approved by the Academic and Ethical committee from the Graduate School of Tropical Medicine and Global Health, Nagasaki University, Japan (Ref. No. 60, 27 th September 2018) and Institutional Technical and Ethical Review Board, University of Public Health, Yangon, Myanmar (Ref. No. UPH-IRB (2018/Research/40), 15 th October 2018). Funding This study was funded by JDS (The Project for Human Resource Development Scholarship by Japanese Grant Aid) and School of Tropical Medicine and Global Health (TMGH), Nagasaki University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Availability of data and materials The dataset used in this study are not publicly available according to the Myanmar law but available from the corresponding author on reasonable request. Contributions TZT, KM, and MM designed the study. TZT and SMH wrote the manuscript. TZT performed the statistical analysis. KM and MM supervised and checked for the consistency of the manuscript. All authors revised the manuscript for important intellectual content and read and approved the final version of the manuscript. Competing interests The authors declare that they have no competing interests. References Hankey GJ. Stroke Lancet. 2017;389(10069):641–54. World Health Organization. Prevent brain stroke. 2016 [cited 2023 February 3]; Available from: https://www.who.int/southeastasia/news/detail/29-10-2016-prevent-brain-stroke . World Health Organization. The top 10 causes of death. 2022 [cited 2023 February 3]; Available from: https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death . Venketasubramanian N, et al. Stroke Epidemiology in South, East, and South-East Asia: A Review. J Stroke. 2017;19(3):286–94. An SJ, Kim TJ, Yoon BW. Epidemiology, Risk Factors, and Clinical Features of Intracerebral Hemorrhage: An Update. J Stroke. 2017;19(1):3–10. Brooks I. Acute stroke and transient ischaemic attack. InnovAiT. 2021;15(2):80–8. Najib N, et al. Contemporary prognosis of transient ischemic attack patients: A systematic review and meta-analysis. Int J Stroke. 2019;14(5):460–7. Mena JH, et al. Effect of the modified Glasgow Coma Scale score criteria for mild traumatic brain injury on mortality prediction: comparing classic and modified Glasgow Coma Scale score model scores of 13. J Trauma. 2011;71(5):1185–92. discussion 1193. Abubakar S, Sabir A. Profile of stroke patients seen in a tertiary health care center in Nigeria. Annals of Nigerian Medicine. 2013;7:55. Eze CO, Kalu UA. The prognosis of acute stroke in a tertiary health centre in south-east Nigeria. Niger J Med. 2014;23(4):306–10. Balami JS, Buchan AM. Complications of intracerebral haemorrhage. Lancet Neurol. 2012;11(1):101–18. Greer DM, et al. Impact of fever on outcome in patients with stroke and neurologic injury: a comprehensive meta-analysis. Stroke. 2008;39(11):3029–35. Stanley D, et al. Translocation and dissemination of commensal bacteria in post-stroke infection. Nat Med. 2016;22(11):1277–84. Goto N. A study on the characteristics of patients who are discharged against medical advice (Signed & Left and Absconded) in Nay Pyi Taw General Hospital, Myanmar MPH thesis , in School of Tropical Medicine and Global Health . 2017, Nagasaki University. Suwanwela NC. Stroke epidemiology in Thailand. J Stroke. 2014;16(1):1–7. Deresse B, Shaweno D. Epidemiology and in-hospital outcome of stroke in South Ethiopia. J Neurol Sci. 2015;355(1–2):138–42. Han SM, et al. Progress towards universal health coverage in Myanmar: a national and subnational assessment. Lancet Glob Health. 2018;6(9):e989–97. O'Donnell MJ, et al. Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries (the INTERSTROKE study): a case-control study. Lancet. 2010;376(9735):112–23. Dehghani Firoozabadi M, et al. Stroke in birjand, iran: a hospital-based study of acute stroke. Iran Red Crescent Med J. 2013;15(3):264–8. Tables Table 1. General characteristics of the stroke patients (n=977) Characteristics Number Percentage Age group, years <39 82 8.4 40-49 123 12.6 50-59 223 22.8 60-69 273 27.9 70-79 190 19.5 80+ 86 8.8 Sex Male 594 60.8 Female 383 39.2 Residence Urban 336 34.7 Rural 632 65.3 Origin of patient Mandalay Region 436 44.6 Bago Region 178 18.2 Magway Region 175 17.9 Nay Pyi Taw 156 16.0 Others 32 3.3 Type of stroke Haemorrhagic 477 48.8 Ischaemic 424 43.4 Mixed 2 0.2 Not recorded 74 7.6 Outcome Improved 669 68.5 Unimproved 308 31.5 Table 2. Characteristic, risk factors, clinical features and complications among improved patients and unimproved patients Characteristics Improved (n=669) Unimproved (n=308) P value Age : mean years ± SD 60.6 ± 14 60.1 ± 15 0.63 Sex (%) Male 410 (61.3) 184 (59.7) 0.65 Female 259 (38.7) 124 (40.3) Residence (%) Urban 230 (34.4) 106 (35.5) 0.75 Rural 439 (65.6) 193 (64.6) Referred from a health facility (%) 195 (29.2) 119 (38.6) < 0.01 Duration of hospital stayed : median days (IQR) 5 (0 - 27) 2 (0 - 32) < 0.01 Risk Factors (%) Hypertension 518 (77.4) 261 (84.7) < 0.01 Diabetes mellitus 108 (16.1) 65 (21.1) 0.06 Tobacco usage 195 (29.2) 63 (20.5) <0.01 Regular alcohol drinking 140 (20.9) 61 (19.8) 0.69 Previous stroke/TIA 84 (12.6) 15 (4.9) < 0.01 Cardiovascular diseases 47 (7.0) 12 (3.9) 0.06 Clinical Features SBP: mean mmHg ± SD 151 ± 27 162 ± 38 < 0.01 DBP: mean mmHg ± SD 91 ± 15 96 ± 22 < 0.01 GCS: median (IQR) 15 (13 - 15) 8 (4 - 11) < 0.01 Blood sugar level: mean ± SD 136 ± 52 165 ± 58 < 0.01 Type of stroke (%) Haemorrhagic 260 (43.1) 217 (72.8) <0.01 Ischaemic 343 (56.9) 81 (27.2) Complications (%) Seizures 27 (4.0) 19 (6.2) 0.14 Fever 164 (24.5) 188 (61.0) < 0.01 Aspiration pneumonia 25 (3.7) 23 (7.5) 0.01 Note: SBP: Systolic blood pressure; DBP: Diastolic blood pressure Table 3. Factor associated with unimprovement among stroke patients Characteristics Crude OR 95% CI P value Age 60 0.87 0.53 - 1.42 0.58 Sex Female 1 Reference Male 0.93 0.71 - 1.24 0.65 Residence Urban 1 Reference Rural 0.95 0.72 - 1.27 0.75 Referred from a health facility 1.53 1.15 - 2.03 <0.01 Risk factors Hypertension 1.62 1.13 - 2.32 <0.01 Diabetes mellitus 1.39 0.99 – 1.96 0.06 Tobacco Use 0.56 0.39 - 0.81 <0.01 Alcohol drinking 0.93 0.67 - 1.30 0.69 Previous Stroke/TIA 0.36 0.20 - 0.63 150mmHg) 1.43 1.08 - 1.90 0.01 DBP (>90mmHg) 1.24 0.92 - 1.66 0.15 BS on admission (>200mg/dl) 1.50 1.09 - 2.06 0.01 GCS at the time of admission 15 - 14 1 Reference 13 - 9 6.37 4.27 – 9.50 <0.01 8 59.20 36.29 – 96.60 <0.01 Type of stroke Ischaemic 1 Reference Haemorrhagic 3.53 2.61 - 4.78 <0.01 Complications Seizure 1.56 0.86 - 2.85 0.15 Fever 4.82 3.61 - 6.44 <0.01 Aspiration Pneumonia 2.08 1.16 - 3.72 0.01 Note: SBP: Systolic blood pressure; DBP: Diastolic blood pressure; BS: Blood Sugar Cite Share Download PDF Status: Published Journal Publication published 18 Mar, 2024 Read the published version in Tropical Medicine and Health → Version 1 posted Editorial decision: Major revision 18 Jan, 2024 Reviewers agreed at journal 01 Jan, 2024 Reviewers invited by journal 27 Dec, 2023 Editor assigned by journal 27 Dec, 2023 First submitted to journal 26 Dec, 2023 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-3810130","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":263884566,"identity":"41ede042-a3eb-4d9e-ad96-8411b096d273","order_by":0,"name":"Thant Zin Tun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFElEQVRIiWNgGAWjYDCCAwwMzGAGhLTh4QdRCQV4tTA2AykJoBbGBgaGNDnJBpAWA2K0MIC1HDY2OAASxqOF7/YB9scFNXfq5Nt5jz/m3XE4cfP51YkfHhgwyPOLHcCqRfJcAmPzjGPPJBib+RKbec+kJ2678XazBNBhhjNnJ2DVYnAG6DAetsMSzMw8hs28bdZALWc3gLQkGNzGp+XfYQk2iBbmxM0zzm7+QVALb9thCR6IFmdjA/7ebXhtkTzD2Dibt++w5Ayglplz29LkJG7wbrNIMJDA6Re+M8wHPvN8O8wv33/G4MPbNmBU9p/dfPNHhY08vzR2LZDYQAESYJUSOJRjBfwHSFE9CkbBKBgFIwAAACOUXaQdG7ZKAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0009-0001-4044-914X","institution":"Nagasaki University School of Tropical Medicine and Global Health: Nagasaki Daigakuin Nettai Igaku Global Health Kenkyuka","correspondingAuthor":true,"prefix":"","firstName":"Thant","middleName":"Zin","lastName":"Tun","suffix":""},{"id":263884567,"identity":"85c22489-4415-4fd4-9b30-7c899d375e34","order_by":1,"name":"Su Myat Han","email":"","orcid":"","institution":"Nagasaki University School of Tropical Medicine and Global Health: Nagasaki Daigakuin Nettai Igaku Global Health Kenkyuka","correspondingAuthor":false,"prefix":"","firstName":"Su","middleName":"Myat","lastName":"Han","suffix":""},{"id":263884568,"identity":"e15d0a2e-72be-4726-ba22-a572abc4dbe0","order_by":2,"name":"Kazuhiko Moji","email":"","orcid":"","institution":"Nagasaki University School of Tropical Medicine and Global Health: Nagasaki Daigakuin Nettai Igaku Global Health Kenkyuka","correspondingAuthor":false,"prefix":"","firstName":"Kazuhiko","middleName":"","lastName":"Moji","suffix":""},{"id":263884569,"identity":"24673a07-bc0e-4b70-99d0-d3c7a2de4d68","order_by":3,"name":"Mitsuaki Matsui","email":"","orcid":"","institution":"Nagasaki University School of Tropical Medicine and Global Health: Nagasaki Daigakuin Nettai Igaku Global Health Kenkyuka","correspondingAuthor":false,"prefix":"","firstName":"Mitsuaki","middleName":"","lastName":"Matsui","suffix":""}],"badges":[],"createdAt":"2023-12-27 02:22:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3810130/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3810130/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s41182-024-00592-6","type":"published","date":"2024-03-18T15:00:55+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":49090146,"identity":"05e313ef-5839-474f-8f42-39fd96f027c1","added_by":"auto","created_at":"2024-01-03 01:41:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":323815,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNumber of monthly stroke admissions and discharge status\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3810130/v1/fbc9e30aceb5d25db6e91bb0.png"},{"id":49090147,"identity":"a35e863b-d300-4dc1-81fc-5b56be6a2f15","added_by":"auto","created_at":"2024-01-03 01:41:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":231944,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe location (township level) of admitted stroke cases admitted to the 1,000 Bedded General Hospital, Nay Pyi Taw\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3810130/v1/db3877fdfb061541ff8b3f52.png"},{"id":49090148,"identity":"6055b0fb-8f62-4f93-9f9c-e9077f99f3bd","added_by":"auto","created_at":"2024-01-03 01:41:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":63928,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMultivariate analysis of selected factors associated with unimproved outcome.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-3810130/v1/1dc24b22d5b56761a491dda7.png"},{"id":53403509,"identity":"b6b586cb-ab00-4e13-ab75-e2f81792e2ce","added_by":"auto","created_at":"2024-03-25 15:12:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":880434,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3810130/v1/a00dad9a-6163-4603-8735-ab4c98a0e2db.pdf"}],"financialInterests":"","formattedTitle":"Stroke types, risk factors, clinical features and outcomes in a tertiary hospital, Myanmar, a descriptive study","fulltext":[{"header":"Background","content":"\u003cp\u003eStroke is characterized as sudden onset of loss of focal neurological function due to infarction or haemorrhage in the central nervous system.[1]\u0026nbsp;It is caused by the interruption of blood supply to culprit lesion of the brain, which is either by haemorrhage or embolism at certain part of blood vessel.[2]\u0026nbsp; Despite the progress of prevention and treatment against stroke, it is the 2\u003csup\u003end\u0026nbsp;\u003c/sup\u003eleading cause of adult deaths in the world, and the 4\u003csup\u003eth\u003c/sup\u003e leading cause of deaths in low-income countries in 2019.[3]\u0026nbsp;A majority of the stroke burden was observed in developing countries, accounting for 75.2% of all stroke-related deaths and 81.0% of the associated DALYs lost.[4]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEpidemiological studies on stroke\u0026apos;s prevalence, and its associated factors enable us to understand the disease epidemiology and its prevention strategies. The risk factors can be categorized broadly into dnon-modifiable and modifiable factors. Age, gender, race, ethnicity, and heredity are among the non-modifiable factors, while hypertension, atrial fibrillation, dyslipidaemia, diabetes, cigarette smoking, physical inactivity, carotid stenosis, transient ischemic attack, and other cardiac disorders are modifiable risk factors. However, studies on factors related to strokes prevalence are notably lacking in resource-limited settings.\u003c/p\u003e\n\u003cp\u003eAlthough stroke is becoming a major health problem in low- and middle-income countries, there are few available data on stroke in Myanmar. Very limited information is available on the demography, risk factors and burden of stroke in Myanmar. Therefore, this study aims to assess the type of stroke, the risk factors, clinical features and outcomes of stroke patients admitted to a top referral hospital in Myanmar.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy site, setting and population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in a 1,000-bedded General Hospital, in the capital city Nay Pyi Taw, Myanmar. It is one of the highest-level referral hospitals in Myanmar, and the only hospital with neurology and neurosurgical units in Nay Pyi Taw. We retrospectively identified the cases admitted to the hospital by reviewing the hospital medical records for International Classification of Diseases, tenth revision (ICD-10), with stroke coded for (I60: non-traumatic subarachnoid haemorrhagic, I61: non-traumatic intracerebral haemorrhagic, I62: other and unspecified intracranial haemorrhagic, I63: cerebral infarction, I64: stroke, not specified as haemorrhagic or infarction, I69: sequelae of cerebrovascular diseases). All stroke diagnosed patients admitted to the hospital between 1st January to 31st December 2017 were eligible for this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection and outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe following data were extracted from the Computer Assisted Medical Record System (CAMRS) database and paper-based medical records: admission and discharge date, duration of hospital stay, discharge status (D/C: normal discharged due to recovered or improved, Expired: patients who died during hospital stay, Signed and Left (S/L): patients or family who signed on the statement that they did not want to receive any more treatment and it was their own will and leave the hospital, Absconded (Abs): leave the hospital without any notice to the hospital authority), age, sex and address. In addition to the clinical features, a variety of factors were evaluated through the review of medical records. These included stroke types - ischemic stroke, haemorrhagic stroke (i.e. intra-cranial haemorrhage, ICH; or sub-arachnoid haemorrhage, SAH) - as determined by the diagnosing physician. Additionally, risk factors such as the patient\u0026apos;s medical history of hypertension, diabetes mellitus, cardiovascular diseases, previous stroke or transient ischemic attack (TIA), smoking habits, alcohol consumption, and betel chewing were extracted.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCategorical variables are described as count (percentage) and chi-square test was used for analysis. Continuous variables are described either as median with interquartile range or mean with standard deviation; and analysed using Mann-Whitney U test or Student\u0026rsquo;s t-test as appropriate. \u0026nbsp;Missing data were ignored.\u003c/p\u003e\n\u003cp\u003eFor the outcome variable, patients were categorised into two groups which were improved (normal discharge) and unimproved (non-normal discharge). Improved patients were patients who were discharged from hospital with good clinical outcome. Unimproved patients included expired cases, signed and leave (S/L) cases, and absconded (Abs) cases. S/L and Abs were assumed as not improved because most of the cases were considered as \u0026lsquo;hopeless\u0026rsquo; by the family members, so that they had not received enough care as stroke cases need continuous support. A multiple logistic regression model was applied to identify factors associated with the unimproved stroke outcome. The type of stroke, history of hypertension, diabetes, and previous stroke, Glasgow Coma Scale (GCS) at the time of admission, and fever during the hospital stay were considered as confounding factors in the multiple logistic regression. Stata (IC version 15.1) and Microsoft Excel (version 16.26) were used for data analysis.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eGeneral characteristics of the stroke patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 1,153 stroke patients were identified, and\u0026nbsp;176 cases were removed from the analysis due to incomplete medical records; therefore, 977 cases were analysed. Table 1 describes the characteristics of the admitted stroke patients. Majority of the cases were male (60.8%), living in rural area (65.3%). One-third\u0026nbsp;of the cases (314 patients) were referred from other hospitals or health care facilities. Hypertension was the most common risk factor among the stroke patients (79.7%) followed by tobacco usage (26.4%) and regular alcohol consumption (20.6%). CT scan results were recorded in 94% of the cases (918 patients). Haemorrhagic stroke (48.8%, 477 patients) was the most common type of stroke, and\u0026nbsp;intracranial haemorrhage (ICH) was dominant (453 cases) followed by subarachnoid haemorrhage (SAH) (13 cases) and both ICH and SAH (11 cases). Approximately\u0026nbsp;seven in ten cases\u0026nbsp;discharged normally (improved).\u0026nbsp;Seasonal fluctuations were observed in the number of the admission\u0026nbsp;(Figure 1). April and November had the highest admission numbers (99 and 98 admissions, respectively), and July had the lowest (50 admissions).\u0026nbsp;Coverage area was wide that\u0026nbsp;were from Mandalay Region (45.1%) followed by Bago Region (18.4%), Magway Region (18.1%), Nay Pyi Taw Union Territory (16.2%) (Figure 2). 80.9% of ischaemic and 54.5% of haemorrhagic stroke patients were discharged with clinical improvement. 41.9% and 23.4 % of haemorrhagic and ischaemic stroke patients respectively were referred from other health facilities (p \u0026lt;0.01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCharacteristic of improved versus unimproved patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 shows characteristic, risk factors, clinical features, and complications among improved and unimproved patients. The proportion of improved outcome was higher among the\u0026nbsp;patients who were admitted directly to the hospital than those referred from other health facilities (p\u0026lt; 0.01). Unimproved patients exhibited a higher prevalence of hypertension (p\u0026lt; 0.01), whereas a history of previous stroke or TIA was more common in improved patients (p\u0026lt; 0.01). The improved patients had lower admission blood pressure and blood sugar levels compared to unimproved patients (p \u0026lt; 0.01). The median Glasgow Coma Scale (GCS) score at the time of admission was 15 for improved patients and 8 for unimproved patients (p \u0026lt; 0.01). Presence of fever and aspiration pneumonia during hospital stay (p = 0.01) was more common in unimproved patients. Improved patients had longer hospital stays compared to their unimproved counterpart (p \u0026lt;0.01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRisk factors association with unimproved stroke outcome\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResults from univariate logistic regression showed that haemorrhagic stroke patients were associated with unimproved outcome (OR 3.53, 95% CI 2.61 \u0026ndash; 4.78). (Table 3) Among the risk factors, hypertension was associated with unimproved outcome (OR 1.62, 95% CI 1.13 \u0026ndash; 2.32). Patients with admission GCS lower than 14 were likely to have unimproved outcome (OR 6.37, 95% CI 4.27 \u0026ndash; 9.50 for GCS 9-14; OR 59.20, 95% CI 36.29 \u0026ndash; 96.60 for GCS \u0026lt;9). Fever (OR 4.82, 95% CI 3.61 \u0026ndash; 6.44) and aspiration pneumonia (OR 2.08, 95% CI 1.16 \u0026ndash; 3.72) were two complications which were associated with unimproved outcome. Patients who were referred from other health facilities were less likely to improve (OR 1.53, 95% CI 1.15 \u0026ndash; 2.03). Patients who had suffered previous stroke/TIA were more likely to improve (OR 0.36, 95% CI 0.20 \u0026ndash; 0.63). Systolic blood pressure \u0026gt; 150 mmHg at the time of admission (OR 1.43, 95% CI 1.08 \u0026ndash; 1.90) and blood sugar level \u0026gt; 200mg/dl at the time of admission (OR 1.50, 95% CI 1.09 \u0026ndash; 2.06) were less likely to improve.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults from the multivariate analysis indicated that haemorrhagic stroke (Adjusted Odd Ratios: AOR 1.66, 95% CI 1.11 \u0026ndash; 2.50), development of fever during the hospital stay (AOR 2.53, 95% CI 1.72 \u0026ndash; 3.71), and lower GCS levels (AOR 4.64, 95% CI 2.94 \u0026ndash; 7.02 for GCS 9-14 and AOR 42.37, 95% CI 25.13 \u0026ndash; 71.43 for GCS \u0026lt;9) were associated with a poor prognosis (Figure 3) Hypertension was associated with unimproved outcome in bivariate analysis; however, this significance was not observed in multivariate analysis (AOR 1.45, 95% CI 0.89 \u0026ndash; 2.38). (Figure 3)\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis is a first study about the stroke types, risk factors, clinical features, and outcomes among hospitalised patients in Myanmar. Key finding is that haemorrhagic stroke, low GCS at the admission, and signs of secondary infection were associated with poor prognosis. Out of haemorrhagic stroke cases, most were ICH and 45.5% were poor prognosis. This finding was in accordance with what Andersen and colleague [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], which also reported the severity and higher risk of death among the haemorrhagic stroke patients compared to ischaemic stroke. The same study also stated that case fatality of ICH was 40% at one month and 54% at one year, which is also consistent with our finding. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eIn this study, among the stroke admissions, hypertension was the most common risk factor. The prevalence of hypertension among the stroke cases was one of the highest among South, East and South-East Asia. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] For acute stroke, hypertension is a major risk factor and maintaining optimal blood pressure during the management of stroke is also important for the outcome.[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] In this study, the history of previous stroke and TIA was observed in 10% of stroke cases and more common in patients with ischaemic stroke. It is reported that 7.4% of TIA patients develops stroke within 90 days of the attack.[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] The follow up system of the patients with management of risk factors should be established.\u003c/p\u003e \u003cp\u003eConscious level at the admission assessed by GCS was a good predictor of prognosis in this study, as it has been shown elsewhere.[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] In our study, admission GCS among improved patients was significantly higher than admission GCS among unimproved patients. This finding was compatible with the studies done in Nigeria.[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] This is due to the nature of the diseases itself, as haemorrhage causes increased intracranial pressure by haematoma, perihaematomal oedema, and intraventricular extension.[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eHaving fever was revealed as predictor of poor prognosis. This finding was compatible with the result of meta-analysis which reported fever as consistent association with worse outcome whether of either ischaemic or haemorrhagic stroke.[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] Fever is a sign of infection, and it is known that stroke patients frequently experiences infections. The main causes of infection are aspiration pneumonia, and infections caused by common commensal bacteria due to bacterial translocation.[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] Therefore, consolidation in infection control including appropriate application of antibiotics could be a possible contributor to improve the prognosis. As it is not integrated yet into stroke management in Myanmar, standardised management procedure should be established.\u003c/p\u003e \u003cp\u003eThe median duration of hospital stay was 4 days which was similar to the result of a study done in this hospital in 2016 [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and results from a study of stroke epidemiology in Thailand [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and shorter than in Ethiopia.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] There was no significant difference between duration of hospital stay in ischaemic and haemorrhagic stroke. However, the duration of hospital stays among the improved patients was longer than the patients who were not improved. S/L and absconded cases were classified as unimproved cases in the analysis, and this may be one of the reasons of longer hospital stays among the improved patients. The proportion of the S/L (25.2%) were higher than the earlier year (15.5%) .[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] In Myanmar, no health insurance system exists, and the OOP payment for the health care services were high.[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] Moreover, the opportunity costs such as absence from work as the duration of hospital stays became longer may be one the challenges of the reasons of S/L or absconded. In this study, we were not able to include the income status of the stroke patients and thus it was not possible to assess the income status of those S/L and absconded cases.\u003c/p\u003e \u003cp\u003eIn this study, the haemorrhagic stroke was the most common type of stroke (48.8%). This is contrary to studies in other countries, which reported that ischaemic stroke as the common type.[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] This difference could be due to selection bias of the study setting. The Nay Pyi Taw General Hospital is one of the only four hospitals in the country with neurology departments and Neurosurgical departments for the optimal care of the haemorrhagic stroke cases. As ischemic stroke cases were mostly managed at the other hospitals, relatively higher proportion of haemorrhagic stroke cases may be observed in the current study. Despite this difference in the study population, the finding of analysis on poor prognosis will be still valid.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eStroke is more common among the older age group population in Myanmar, and haemorrhagic stroke is the most common type among the hospitalised stroke patients. Hypertension is the most common risk factor for both types of strokes (Ischemic and haemorrhagic). It is important to raise awareness among the population on the risk factor of strokes, and the prevention measures against the stroke. It is also important to increase the number of stroke units within the country to cover the wider geographical population of Myanmar.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAbs: Absconded\u003c/p\u003e\n\u003cp\u003eAOR: Adjusted Odds Ratio\u003c/p\u003e\n\u003cp\u003eCAMRS: Computer Assisted Medical Record System\u003c/p\u003e\n\u003cp\u003eCT Scan: Computed Tomography Scan\u003c/p\u003e\n\u003cp\u003eD/C: Normal Discharged (improved)\u003c/p\u003e\n\u003cp\u003eDALY: Disability-adjusted Life Year\u003c/p\u003e\n\u003cp\u003eDBP: Diastolic Blood Pressure\u003c/p\u003e\n\u003cp\u003eDM: Diabetes Mellitus\u003c/p\u003e\n\u003cp\u003eGCS: Glasgow Coma Scale\u003c/p\u003e\n\u003cp\u003eICD: International Classification of Diseases\u003c/p\u003e\n\u003cp\u003eICH: Intracerebral Haemorrhagic\u003c/p\u003e\n\u003cp\u003eOR: Odds Ratio\u003c/p\u003e\n\u003cp\u003eS/L: Signed and Left\u003c/p\u003e\n\u003cp\u003eSAH: Subarachnoid Haemorrhagic\u003c/p\u003e\n\u003cp\u003eSBP: Systolic Blood Pressure\u003c/p\u003e\n\u003cp\u003eTIA: Transient Ischaemic Attack\u003c/p\u003e\n\u003cp\u003eWHO: World Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThant Zin Tun acknowledged the scholarship from Japanese Grant Aid for Human Resource Development (JDS), the government of Japan. \u0026nbsp;The authors thanks to medical superintendents, staffs and all patients of 1,000 Bedded General Hospital, for giving permission and especially staffs from the medical record department for the supporting the data collection. Special thanks to Dr. Han Win Naing who helped in extraction of the clinical data from the medical records.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was approved by the Academic and Ethical committee from the Graduate\u003c/p\u003e\n\u003cp\u003eSchool of Tropical Medicine and Global Health, Nagasaki University, Japan (Ref. No.\u003c/p\u003e\n\u003cp\u003e60, 27\u003csup\u003eth\u003c/sup\u003e September 2018) and Institutional Technical and Ethical Review Board, University of Public Health, Yangon, Myanmar (Ref. No. UPH-IRB (2018/Research/40), 15\u003csup\u003eth\u003c/sup\u003e October 2018).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by JDS (The Project for Human Resource Development Scholarship by Japanese Grant Aid) and School of Tropical Medicine and Global Health (TMGH), Nagasaki University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset used in this study are not publicly available according to the Myanmar law but available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTZT,\u0026nbsp;KM, and MM designed the study. TZT and SMH wrote the manuscript. TZT performed the statistical analysis. KM and MM supervised and checked for the consistency of the manuscript. All authors revised the manuscript for important intellectual content and read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHankey GJ. Stroke Lancet. 2017;389(10069):641\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Prevent brain stroke. 2016 [cited 2023 February 3]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/southeastasia/news/detail/29-10-2016-prevent-brain-stroke\u003c/span\u003e\u003cspan address=\"https://www.who.int/southeastasia/news/detail/29-10-2016-prevent-brain-stroke\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. The top 10 causes of death. 2022 [cited 2023 February 3]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death\u003c/span\u003e\u003cspan address=\"https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVenketasubramanian N, et al. Stroke Epidemiology in South, East, and South-East Asia: A Review. J Stroke. 2017;19(3):286\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAn SJ, Kim TJ, Yoon BW. Epidemiology, Risk Factors, and Clinical Features of Intracerebral Hemorrhage: An Update. J Stroke. 2017;19(1):3\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrooks I. Acute stroke and transient ischaemic attack. InnovAiT. 2021;15(2):80\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNajib N, et al. Contemporary prognosis of transient ischemic attack patients: A systematic review and meta-analysis. Int J Stroke. 2019;14(5):460\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMena JH, et al. Effect of the modified Glasgow Coma Scale score criteria for mild traumatic brain injury on mortality prediction: comparing classic and modified Glasgow Coma Scale score model scores of 13. J Trauma. 2011;71(5):1185\u0026ndash;92. discussion 1193.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbubakar S, Sabir A. Profile of stroke patients seen in a tertiary health care center in Nigeria. Annals of Nigerian Medicine. 2013;7:55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEze CO, Kalu UA. The prognosis of acute stroke in a tertiary health centre in south-east Nigeria. Niger J Med. 2014;23(4):306\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBalami JS, Buchan AM. Complications of intracerebral haemorrhage. Lancet Neurol. 2012;11(1):101\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreer DM, et al. Impact of fever on outcome in patients with stroke and neurologic injury: a comprehensive meta-analysis. Stroke. 2008;39(11):3029\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStanley D, et al. Translocation and dissemination of commensal bacteria in post-stroke infection. Nat Med. 2016;22(11):1277\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoto N. \u003cem\u003eA study on the characteristics of patients who are discharged against medical advice (Signed \u0026amp; Left and Absconded) in Nay Pyi Taw General Hospital, Myanmar MPH thesis\u003c/em\u003e, in \u003cem\u003eSchool of Tropical Medicine and Global Health\u003c/em\u003e. 2017, Nagasaki University.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuwanwela NC. Stroke epidemiology in Thailand. J Stroke. 2014;16(1):1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeresse B, Shaweno D. Epidemiology and in-hospital outcome of stroke in South Ethiopia. J Neurol Sci. 2015;355(1\u0026ndash;2):138\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHan SM, et al. Progress towards universal health coverage in Myanmar: a national and subnational assessment. Lancet Glob Health. 2018;6(9):e989\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO'Donnell MJ, et al. Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries (the INTERSTROKE study): a case-control study. Lancet. 2010;376(9735):112\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDehghani Firoozabadi M, et al. Stroke in birjand, iran: a hospital-based study of acute stroke. Iran Red Crescent Med J. 2013;15(3):264\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. General characteristics of the stroke patients\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(n=977)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"473\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003eAge group, years\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026lt;39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; 40-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e12.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; 50-59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e22.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; 60-69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e27.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp;70-79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e19.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;80+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e60.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e39.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; Urban\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e336\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e34.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; Rural\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e65.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003eOrigin of patient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; Mandalay Region\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e436\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e44.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; Bago Region\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e18.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; Magway Region\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e17.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; Nay Pyi Taw\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e16.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; Others \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003eType of stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; Haemorrhagic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e48.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; Ischaemic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e43.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; Mixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp; Not recorded\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003eOutcome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp;Improved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e669\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e68.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"43.97463002114165%\"\u003e\n \u003cp\u003e\u0026nbsp;Unimproved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.021141649048626%\"\u003e\n \u003cp\u003e308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.004228329809724%\"\u003e\n \u003cp\u003e31.5\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\u003e\u003cstrong\u003eTable 2. Characteristic, risk factors, clinical features and complications among improved\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003epatients and unimproved patients\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"105%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eImproved (n=669)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnimproved (n=308)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e: mean years \u0026plusmn; SD\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e60.6 \u0026plusmn; 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e60.1 \u0026plusmn; 15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e410 (61.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e184 (59.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e259 (38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e124 (40.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidence\u003c/strong\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Urban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e230 (34.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e106 (35.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Rural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e439 (65.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e193 (64.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eReferred from a health facility\u003c/strong\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e195 (29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e119 (38.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; \u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDuration of hospital stayed\u003c/strong\u003e: median days (IQR)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e5 (0 - 27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e2 (0 - 32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk Factors\u003c/strong\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Hypertension\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e518 (77.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e261 (84.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Diabetes mellitus\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e108 (16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e65 (21.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Tobacco usage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e195 (29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e63 (20.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Regular alcohol drinking\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e140 (20.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e61 (19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Previous stroke/TIA\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e84 (12.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e15 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Cardiovascular diseases\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e47 (7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e12 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical Features\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; SBP: mean mmHg \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e151 \u0026plusmn; 27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e162 \u0026plusmn; 38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; DBP: mean mmHg \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e91 \u0026plusmn; 15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e96 \u0026plusmn; 22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; GCS: median (IQR)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e15 (13 - 15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e8 (4 - 11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Blood sugar level: mean \u0026plusmn; SD\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e136 \u0026plusmn; 52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e165 \u0026plusmn; 58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of stroke\u003c/strong\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Haemorrhagic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e260 (43.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e217 (72.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Ischaemic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e343 (56.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e81 (27.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eComplications\u003c/strong\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Seizures\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e27 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e19 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Fever\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e164 (24.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e188 (61.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.474747474747474%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Aspiration pneumonia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.19191919191919%\" valign=\"top\"\u003e\n \u003cp\u003e25 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.22222222222222%\" valign=\"top\"\u003e\n \u003cp\u003e23 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: SBP: Systolic blood pressure; DBP: Diastolic blood pressure\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Factor associated with unimprovement among stroke patients\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"567\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCrude OR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003e40 \u0026ndash; 59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e0.62 - 1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e0.53 - 1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e0.93\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e0.71 - 1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidence\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003eRural \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e0.72 - 1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eReferred from a health facility\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e1.53\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e1.15 - 2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003eHypertension\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e1.62\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e1.13 - 2.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003eDiabetes mellitus\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e1.39\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e0.99 \u0026ndash; 1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003eTobacco Use\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e0.39 - 0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003eAlcohol drinking\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e0.93\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e0.67 - 1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003ePrevious Stroke/TIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e0.36\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e0.20 - 0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003eCardiovascular diseases\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e0.54\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e0.28 - 1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003eSBP (\u0026gt;150mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e1.43\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e1.08 - 1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003eDBP (\u0026gt;90mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e1.24\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e0.92 - 1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003eBS on admission (\u0026gt;200mg/dl)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e1.50\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e1.09 - 2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGCS at the time of admission\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003e15 - 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003e13 - 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e6.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e4.27 \u0026ndash; 9.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e59.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e36.29 \u0026ndash; 96.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of stroke\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003eIschaemic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003eHaemorrhagic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e3.53\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e2.61 - 4.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eComplications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003eSeizure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e1.56\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e0.86 - 2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003eFever\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e4.82\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e3.61 - 6.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.029982363315696%\" valign=\"top\"\u003e\n \u003cp\u003eAspiration Pneumonia\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.98941798941799%\" valign=\"top\"\u003e\n \u003cp\u003e2.08\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e1.16 - 3.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.403880070546737%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: SBP: Systolic blood pressure; DBP: Diastolic blood pressure; BS: Blood Sugar\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"tropical-medicine-and-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tmah","sideBox":"Learn more about [Tropical Medicine and Health](https://tropmedhealth.biomedcentral.com/)","snPcode":"41182","submissionUrl":"https://submission.springernature.com/new-submission/41182/3","title":"Tropical Medicine and Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Stroke, Hypertension, Myanmar, risk factors of stroke","lastPublishedDoi":"10.21203/rs.3.rs-3810130/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3810130/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStroke is one of the leading causes of death and majority of the stroke burden was observed in middle- and low-income countries. Understanding the risk factors, complications and outcomes is useful in healthcare planning and resource allocation. However, little information on stroke is available in Myanmar.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA review of medical records of stroke admission during 2017 in a tertiary hospital was conducted. Final diagnosis, risk factors, clinical features, complications and outcomes were systematically collected both from computer-based and from paper-based medical records.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1153 cases were identified, and 977 cases were analysed. Haemorrhagic stroke was the most common type (48.8%), followed by ischaemic stroke (43.4%). Unimproved cases were 31.5%. Identified risk factors of unimproved were 'haemorrhagic stroke' [adjusted odds ratio (aOR): 1.67], 'having fever during hospitalisation' [aOR: 2.53], and 'Glasgow Coma Scale at the admission between 9 and 14 [aOR: 4.64], and less than 9 [aOR: 42.37].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIntracranial haemorrhage and unconsciousness were significantly associated with poor prognosis. Fever during the hospitalisation, which was also a risk factor of unimproved cases, could be associated with aspiration pneumonia. This could be an associated symptom of unconsciousness. The findings imply how to prevent and control fever among stroke patients during hospital stay is a key for better prognosis.\u003c/p\u003e","manuscriptTitle":"Stroke types, risk factors, clinical features and outcomes in a tertiary hospital, Myanmar, a descriptive study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-03 01:41:51","doi":"10.21203/rs.3.rs-3810130/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2024-01-18T23:00:30+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-01-01T16:51:50+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-12-28T01:12:11+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-12-28T00:44:23+00:00","index":"","fulltext":""},{"type":"submitted","content":"Tropical Medicine and Health","date":"2023-12-26T21:17:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"tropical-medicine-and-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tmah","sideBox":"Learn more about [Tropical Medicine and Health](https://tropmedhealth.biomedcentral.com/)","snPcode":"41182","submissionUrl":"https://submission.springernature.com/new-submission/41182/3","title":"Tropical Medicine and Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1bb34c3c-af45-4ec8-b1a9-3c3281b3a7f9","owner":[],"postedDate":"January 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-03-25T15:04:16+00:00","versionOfRecord":{"articleIdentity":"rs-3810130","link":"https://doi.org/10.1186/s41182-024-00592-6","journal":{"identity":"tropical-medicine-and-health","isVorOnly":false,"title":"Tropical Medicine and Health"},"publishedOn":"2024-03-18 15:00:55","publishedOnDateReadable":"March 18th, 2024"},"versionCreatedAt":"2024-01-03 01:41:51","video":"","vorDoi":"10.1186/s41182-024-00592-6","vorDoiUrl":"https://doi.org/10.1186/s41182-024-00592-6","workflowStages":[]},"version":"v1","identity":"rs-3810130","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3810130","identity":"rs-3810130","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}