Associated Factors of Stroke Severity Among Young Adult Stroke Patients in Malaysia from National Neurology Registry 2014 - 2018 Presentation Slides by Ms Fara Waheda Jusoh, presented on the 14th National Conference for Clinical Research (NCCR) 2021 Dr Wu Lien Teh Youth Investigator Awards (YIA) on 19th August 2021 Following are the links for this presentation on Zenodo Repository: Presentation Slides: https://zenodo.org/record/5348488 E-Poster: https://zenodo.org/record/5348580

1. ASSOCIATED FACTORS OF STROKE
SEVERITY AMONG YOUNG ADULT
STROKE PATIENTS IN MALAYSIA FROM
NATIONAL NEUROLOGY REGISTRY
2014 - 2018
Fara Waheda J1, Najib Majdi Y2, Anis Kausar G2, Norsima Nazifah S3, Zariah AA4, Zuhaini M¹
1Pharmacy Department HSNZ, Kuala Terengganu, Terengganu
2Unit of Biostatistics & Research Methodology, School of Medical Sciences, USM Health Campus,
Kelantan
3Clinical Research Centre HSNZ, Kuala Terengganu, Terengganu
4Neurology Unit HSNZ, Kuala Terengganu, Terengganu
P-77

2. INTRODUCTION
➢ Stroke is an abrupt onset of a focal neurological deficit secondary to
a vascular event lasting more than 24 hours. (WHO, 2012)
➢ Globally, 15 million people worldwide suffered stroke every year.
(WHO, 2019)
➢ Stroke remained the third cause of death throughout the years in
Malaysia.
( Department of Statistics, Malaysia 2020)

3. INTRODUCTION
➢ The incidence of young ischaemic stroke varies widely from 6.6 to 11.4
in 100,000 people per year across the world and is generally higher in
developing countries than in developed countries
(Boot E, et al 2020, Lutski M, Zucker I et al 2017)
➢ In Malaysia, stroke incidence has increased significantly, with the greatest
increase of 53.3 % in men aged 35–39 years and 50.4 % in women in the
same age range
(Hwong WY, et a 2021)

4. PROBLEM STATEMENT
➢ The incidence of stroke in young adults has been rising over recent
decades by 1.2% between 2010 and 2016 (Hwong et. al.,2021)
➢ Most of the previous study focusing either on associated factors of
stroke among older patients or ischaemic patients
➢ Identification of predictors’ stroke severity among young adult was
less extensively studied
➢ Information on proportions and stroke severity predictors could be used
to develop effective prevention and treatment strategies in the future

5. OBJECTIVES
Specific Objectives
To determine the factors
associated with stroke severity
among young adults’ stroke
patients.
Specific Objectives
To estimate the proportion of young
adult stroke patients based on
severity (mild, moderate and severe
stroke by NIHSS classification)
.
General Objective
To study proportion and factors associated with
stroke severity among young adult stroke patients
who were registered in the Malaysian National
Neurology Registry

6. METHODOLOGY
Study Design
• A cross-sectional study
Source of Data
• Data were extracted from National Neurology Registry (NNR); a national
system established for the non-mandatory notification of stroke admissions
in Malaysia public hospitals since July 2009
Study Duration
• October 2019 - May 2020
Sampling Frame
• All young adult stroke patients registered from January 2014 until December
2018 that fulfilled the study criteria
6

7. DEFINITION
Young stroke
¹Adults aged 18-49 years old
Stroke severity
²Based on NIHSS score
• Mild (1–6)
• Moderate (7–15)
• Severe (≥ 16)
¹ Yesilot Barlas et al., 2013; Putaala et al., 2009; Kappelle et al., 1994
² Tseng and Chang, 2006
7

8. STUDY CRITERIA
INCLUSION
Young adult (18 to 49 years old)
First stroke event
EXCLUSION
Traumatic haemorrhagic stroke due
to motor vehicle accident or head
injury
Intra-cerebral haemorrhage due to
known cerebral metastasis or brain
tumour
Pregnancy related stroke
8

9. DATA ANALYSIS
Data were analysed using STATA (SE) version 14 (Stata Corp, 2015)
• Descriptive statistics - Frequency, mean and standard deviation
• Univariable analysis – Simple ordinal logistic regression
• Multivariate analysis – Multiple Ordinal logistic regression
9

10. STUDY FLOW
N=17,883
• All stroke patients in NNR
• Data were sorted by sequence number (ID) & merged
• Checked for duplicate ID
n=16,462
• Exclude
• Respondents registered before 2014 and after 2018
(n=7,619)
• Patients with recurrent stroke event (n=2,044)
• Aged <18 & ≥ 50 years (n=6,799)
n=1,421
• Final sampling frame
• Data collection (socio-demo, stroke subtype, comorbidities)
• Recode NIHSS according to 3 categories
• Data analysis & interpretation

11. RESULTS & DISCUSSION
11
Variables Severity of stroke
Overall
n (%)
Mild
n (%)
Moderate
n (%)
Severe
n (%)
Age (year)ª 41(7.6) 41(8.3) 41(6.8) 41(7.3)
Gender
Male 896 (63.1) 347(52.0) 261(39.1) 59(8.9)
Female 525 (36.9) 192(48.6) 171(43.3) 32(8.1)
Ethnicity
Malay 1038(73.6) 391(50.7) 320(41.5) 61(7.9)
Chinese 161(11.4) 59 (47.9) 51(41.5) 13(10.6)
Indian 34(2.4) 11(45.8) 11(45.8) 2(8.3)
Foreigner 29(1.9) 8(40.0) 10(50.0) 2(10.0)
Others 150(10.6) 63(55.8) 37(32.7) 13(11.5)
ªmean (SD)
Table 1: Demographic data (n=1421)

12. RESULTS & DISCUSSION
12
Severity of Stroke Unweighted
count (n)
Proportionᵃ
(%)
95% CI
Mild (NIHSS 1-6) 539 0.50 0.48, 0.54
Moderate (NIHSS 7-15) 432 0.41 0.38, 0.44
Severe (NIHSS ≥ 16) 91 0.09 0.07, 0.10
Table 2: Proportion of stroke based on severity among young adults’ stroke patients (n=1421)
ᵃ Stroke proportion equal to the number of stroke case for each category/total of stroke cases among young adult

13. Proportion of Stroke in Young Adult According to Severity
Findings ;
• The proportion of stroke severity among young adults for mild, moderate and severe was
50%, 41% and 9% respectively
• Finland, young adults: 75.8% for mild stroke, 13.8% for moderate stroke and 10.4% for
severe stroke (Putaala et al. 2009)
• In Greece, 53.3% had a mild neurological deficit, 33.3% had moderate and 13.3% had
severe stroke accordingly (Spengos and Vemmos, 2010)
• In Taiwan, 53.5% of them had a mild stroke, 27% had a moderate stroke and 19.5% had a
severe stroke (Chang et al., 2010)
▲Greater stroke severity was a significant factor of death after stroke
(Mogensen et al., 2013; Kelly-Hayes et al., 2003)
13
RESULTS & DISCUSSION

14. Table 3: Associated factors with stroke severity by simple ordinal logistic regression (n=1421)
Variables bᵃ Crude OR
(95% CI)
Wald statistics
(df)
P-value
Age (year) 0.004 1.00 (0.99, 1.02) 0.50 0.616
Gender
Male 0 1
Female 0.103 1.11 (0.87,1.41) 0.84 0.402
Ethnicity
Malay 0 1
Chinese 0.141 1.51(0.79,1.66) 0.75 0.451
Indian 0.168 1.18 (0.55,2.57) 0.43 0.669
Foreigner 0.388 1.47 (0.64,3.40) 0.91 0.364
Others -0.57 0.89 (0.6,1.32) -0.57 0.567
Stroke classificationᵃ
Non-ischaemic 0 1
Ischaemic 0.774 2.17 (1.44,3.25) 3.75 <0.001
Hypertension
No 0 1
Yes -0.084 0.92 (0.72,1.18) -0.66 0.506
ᵃvariables included in the variable selection of regression analysis
ᵇVariables dropped since only No observations available 14
RESULTS & DISCUSSION

15. Table 3: Associated factors with stroke severity by simple ordinal logistic regression (continued)
Variables bᵃ Crude OR
(95% CI)
Wald statistics (df) P-value
Diabetes Mellitus
No 0 1
Yes -0.089 0.91 (0.72,1.16) -0.73 0.468
Hyperlipidemia
No 0 1
Yes 0.049 1.05 (0.77,1.44) 0.31 0.758
Ischaemic heart
Diseaseᵃ
No 0 1
Yes 0.257 1.29 (0.83,2.0) 1.15 0.250
Atrial fibrillationᵃ
No 0 1
Yes 1.41 4.10 (2.19,7.68) 4.41 <0.001
Peripheral arterial
disease
No 0 1
Yes 1.200 3.31 (0.13, 86.51) 0.72 0.472
15
RESULTS & DISCUSSION

16. Table 3: Associated factors with stroke severity by simple ordinal logistic regression (continued)
Variables bᵃ Crude OR
(95% CI)
Wald statistics (df) P-value
Oral contraceptive
No 0 1
Yes 0.184 1.2 (0.24,5.93) 0.23 0.822
Antiplatelet
No 0 1
Yes 0.099 1.10 (0.80,1.53) 0.60 0.547
Anticoagulantᵃ
No 0 1
Yes 0.649 1.91 (0.82,4.45) 1.51 0.131
Ace-inhibitorᵃ
No 0 1
Yes -0.265 0.77 (0.56,1.06) -1.63 0.103
ARB
No 0 1
Yes 0.039 1.04 (0.57,1.89) 0.13 0.898
16
RESULTS & DISCUSSION

17. Table 3: Associated factors with stroke severity by simple ordinal logistic regression (continued)
Variables bᵃ Crude OR
(95% CI)
Wald statistics (df) P-value
CCB
No 0 1
Yes -0.012 0.99 (0.74,1.32) -0.09 0.931
Beta blockersᵃ
No 0 1
Yes 0.266 1.30 (0.91,1.86) 1.46 0.145
Alpha blockers
No 0 1
Yes 0.475 1.61 (0.73,3.54) 1.18 0.237
Diuretics
No 0 1
Yes -0.252 0.78 (0.50,1.20) -1.13 0.258
Lipid lowering
therapy
No 0 1
Yes -0.109 0.90 (0.68, 1.19) -0.76 0.450
17
RESULTS & DISCUSSION

18. Table 3: Associated factors with stroke severity by simple ordinal logistic regression (continued)
Variables bᵃ Crude OR
(95% CI)
Wald statistics (df) P-value
Antidiabeticsᵃ
No 0 1
Yes -0.243 0.78 (0.59,1.04) -1.64 0.100
Physical inactivity
No 0 1
Yes -0.280 0.76 (0.24, 2.36) -0.48 0.629
Alcohol drinkingᵃ
No 0 1
Yes 0.6630 1.87 (1.04,3.38) 2.10 0.036
Family history
No 0 1
Yes -0.212 0.81 (0. 46,1.43) -0.73 0.468
Migraine with aura ᵇ
Sleep apnoeaᵇ
Hormone replacement
Therapyᵇ
ᵃvariables included in the variable selection of regression analysis
ᵇVariables dropped since only NO observations available
18
RESULTS & DISCUSSION

19. Variables Full model of multiple ordinal logistic regression
b (SE) Adjusted OR
(95% CI)
Adjusted Wald
statistics
P-value
Stroke classification
Non-ischaemic 0 1
Ischaemic 0.76 (0.448) 2.15
(1.43, 3.23)
3.65 <0.001
Atrial fibrillation
No 0 1
Yes 1.37 (1.286) 3.94
(2.08, 7.47)
4.21 <0.001
Alcohol drinking
No 0 1
Yes 0.66 (0.586 1.93
(1.06, 3.50)
2.16 0.030
19
Table 4: Associated Factors with Stroke Severity (n=1421)
RESULTS & DISCUSSION

20. Variables Full model of multiple ordinal logistic regression
b (SE) Adjusted OR
(95% CI)
Adjusted Wald
statistics
P-value
Stroke classification
Non-ischaemic 0 1
Ischaemic 0.76 (0.448) 2.15
(1.43, 3.23)
3.65 <0.001
20
Table 4: Associated Factors with Stroke Severity (n=1421)
• Ischaemic stroke was less severe as compared to haemorrhagic stroke
(Kõrv et. al., 2021)
• Survival probability for patients ischemic stroke was higher as compared to hemorrhagic stroke
(Wan-Arfah et. al., 2018)
RESULTS & DISCUSSION

21. Variables Full model of multiple ordinal logistic regression
b (SE) Adjusted OR
(95% CI)
Adjusted Wald
statistics
P-value
Atrial fibrillation
No 0 1
Yes 1.37 (1.286) 3.94
(2.08, 7.47)
4.21 <0.001
21
Table 4: Associated Factors with Stroke Severity (n=1421)
• AF was significantly correlated with NIHSS (Kim et al. 2012)
• Registry of the Canadian Stroke Network; Patients with AF had a more severe stroke compared to the
non-AF patients (Saposnik et al. 2013)
• AF highly related to stroke because it leads to inadequate contraction of atrial, and hence the formation
of thrombus within, the LAA. (Gretarsdottir et al., 2008)
RESULTS & DISCUSSION

22. Variables Full model of multiple ordinal logistic regression
b (SE) Adjusted OR
(95% CI)
Adjusted Wald
statistics
P-value
Alcohol drinking
No 0 1
Yes 0.66 (0.586 1.93
(1.06, 3.50)
2.16 0.030
22
Table 4: Associated Factors with Stroke Severity (n=1421)
• Despite being risk factors, alcohol consumption does not have a significant influence on stroke
severity either for short- or long-term outcome (Fekete et al., 2014)
• Alcohol consumption mostly caused haemorrhagic stroke and generally more severe than ischaemic
(Andersen et al., 2009)
RESULTS & DISCUSSION

23. CONCLUSION
1. The model demonstrated that there were 50% of young adults’ stroke
patients have a mild stroke, 41% had a moderate stroke and 9% had a
severe stroke.
2. Ischemic stroke, atrial fibrillation and alcohol drinking were factors that
influenced in having a more severe stroke among young adult stroke
patients in Malaysia.
23

24. Study Strength & Limitation
Strength
▪ Using the largest stroke database in Malaysia and therefore representing sample
of Malaysia population
Limitation
• This is a retrospective study and thus was potentially prone to systematic bias.
• The notification of stroke to NNR was not mandatory for medical centres,
therefore there was a possibility of underreported cases.
• Missing and incomplete data are very common in secondary data and some of
the variables which could influence in the result were not included in this study.
24

25. ❖ Director General of Health KKM
❖ Pharmacy Department of Hospital Sultanah Nur Zahirah
❖ Committee members of R&D Pharmacy of Hospital Sultanah Nur Zahirah
❖ Neurology Unit Hospital Sultanah Nur Zahirah
❖ Clinical Research Center (CRC) HSNZ
❖ Committee members of R&D Pharmacy of JKNT
❖ Unit of Biostatistics & Research Methodology, School of Medical Sciences, USM
Health Campus, Kelantan
ACKNOWLEDGEMENT
THANK YOU!
https://nccrconference.com.my/

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