
 !"#$%&%#'!(

#)*+,'
 !"
#$%#&'##("##)*+,#-
$%#..(/"##0*(-"#)
*#&

#$-./0/
1'"1+2123/!,4&
5,!!,4&
13)&4-42Tng snhi máu o ñưcñưa vào nghiên cu này là 74 bnh nhân. Trong sut
thi gian ñiu tr, chúng i thu thp an b d liu v dch t hc, nhng yu t nguy cơ mch máu, bnh
cnh ñt qu, tình trng thn kinh. Mi bnh nhân ñu ñưc kim tra v tâm thn kinh hc qua các test:
MMSE, IST, ZCT, 4-IADL. '0#067189"sa sút trí tê 
#0:8:61$8;<:&'0 #"#$%#=#0>#+#
#?@A&
1567/8'*2BTn s sa4làCDE(#4CF&CE(
4FGE&CNgòai tui tnh ñ hc vn thp, hai lai yu t nguy cơ liên quan
mt thit ñn sa sút t tê sau ñt qu là (a): yu t nguy cơ mch máu: cao huyt áp, ñái to ñưng , hút
thuc lá , thiu máu cơ tim, xơ va ñng mch và (b): nhng yu t nguy cơ ñt qu: knói, ñt qu trưc
ñó, nhi u bán cu trái, nhi máu não nhiu , bnh mch máu nh, nhi máu não l khuyt nhi
u não vùng chin lưc.
Kt lun: Tn sut ca sa sút t tê sau ñt qu nhi máu não trong vòng 3tháng ñu ¼. Nhng yu t
nguy cơ d ñóan ñc lp cho sa sút trí tê sau ñt qu bao gm: tui, trình ñ hc vn thp, nhng yu t
nguy cơ ca ñt qu . Nhng yu t nguy cơ mch máu liên quan ñn sa sút trí tê sau ñt qu như ñã k
trên là nhng yu t nguy cơ có th ñiu tr ñưc. Phòng nga, chn ñóanñiu tr sm là quan trng.
Abstract:
1-Purpose:
-Study the prequency of poststroke dementia (PSD)
- Identify the predictors of PSD.
2-Methods:
-A total of 74 consecutive patients with ischemic stroke were enrolled in this study. During admission, the
demographic data, vascular risk factors,
stroke features and neurological status information were colleted.
All subjects were examined by a set of neuropsychological tests: MMSE, IST, ZCT, 4-IADL, at first and
3months after stroke.
Diagnotic Dementia was classified according to DSM-IV and Vascular Dementia was classified according to
NINDS-AIREN. Differential diagnosis with Alzheimer’s disease was determined by a modified Hachinski
scale.
3- Results:
(1) The frequency of poststroke dementia was 27%, that of stroke related dementia was 25.2%, and that of
dementia after first – ever stroke was 50%.
(2) In addition to age, and low educational level, two types of risk factors show a close relationship with
poststroke dementia :(a) vascular risk factors such as: hypertention, hyperlipidemia, diabetes mellitus,
smoking, myocardial ischemic, atherosclerosis, (b) stroke risk factors such as: dysphasia, prior stroke, left
cerebral infarctions, multiple stroke lesions, small vessell lesions, lacunar infarctions, strategic infarctions.
4-Conclusions:
The frequency of dementia is about one in four for patients with ischemic stroke, 3 months after stroke.
Indepent predictors of poststroke dementia include: age, low educational level and stroke risk factors. The
vascular risk factors related to post stroke dementia can be treated. Prevention , early diagnosis and
treatment are very important.
#3)&4-4
17,(.&
1H!+I, H&
13###JKGF1BCKGL&
96%'1':+3;<$
1'#-4#*)4#**0I)
"/,&
1''3"K7;8I)0""),#0&
1MNOBF#0&
13,#0 út tr í tu 67189"-#0:8:61
$8;<:&
1>#+##?@A&
13#,PMMSE, IST, ZCT, 4-IADL.
96%'1':=$"9/>3<
1Q!!*&
1R#R+S*("#*('3:(T!
# (#!UBCVW&
13, #&
1M#,),,!"##+#0&
#?(&@1-1A967+$B1=B4C
30#XLF"LF
3/"!2 G1F( L1J( @BG&
Y4)Z+#!+!+###! (#CP#(/,
0I)0#(")(,4&:#*0!'37;8
+!I!!&'0R! #R##1'<!
Z!+!#Z/!&'00#!*R0
2RI"*(,2T+!! (#&
Y#0#!4 ,#(#("#!(#4(4 (
!!,4'>$(Y#(Z(:33!(#(!(I*
(;['>[H(!!4#+&
'#0,!!2
1'! 2>$@BPGKJG>+##)'>$
1Y#2!@BB&BK[(>$B'&L(FE+#R
8#!!!
1Q*#6 ,,I"*&
1;['>[H2'@F&LK[([6[@A&PK[(3M@B&\\K[&
#-/96B;<1:+$-D'-//>2/'6B
'033R"#0267189
 ( 9 89 ##( :8:61$8;<:  : #R# U ]  :#
8#]:#6#RR+:8:61
$8;<:("#0>$'>8:58&
Y#33" #R"77<(83(^'3(P18$6[&
1D'-//>2/'6B ."1.-'96)Z #   '# &(BJJC_
;&BJJABB(AP0R4"0+R4&
43##BJJP(&H#`[(BJJDPB(PC(AG&
1D'-//>2/'6BD'+$B/8'EH+16#2)ZI,
#"#4&5 ##0#!#4H#`[(BJJD
AG&
1D'-//>2/'6B=96%8'+67+$B/8'E+1RR#2)Z
I,46R"#R>CGGPBA&
#567/8'*
a#0 R0(#0/,+#
#*#U,B&32#0/77<bBJ&\(83XCA(^'3
XBA"K@A\#&P18$6[/\&AF&3#083XCJ!!R
&
3DP+,CG+CDE(PP)
(F L&\E960
 (4H6CGCDE(#4;6BJCF&CE(
4ADFGE(BGBA&FEU,C
U,A2!!"R)0#*"+
!0#("!! R# BG"## #!!&
U,P2!!#*C(#!(#!!
 "#+(
#! (!#T# #R(I"*(#!#(!(4
,+0&
cd,F,4+! "#+#(4(#*
#(#*#00+!0(0"#!(#!.&
U,L2")0,"#!(#0#"#!"0
"##!!,&
U,D2'")0"#!20#0"##"#"
#! !# &
F#$D-1-1/&+96:.+-&9-&93!G$-.DD'-//>2/'6B;<H$%&DD'-//>2/'6B


27.4 26.7
18.9
30.6 27.9
18.2
0.3 2.3
8.35
0
10
20
30
40
%
MMSE IST 4-IADL
5$%& $-&' 1) 


&+96:.I

0
10
20
30
40
50
60
%
J
/3)<&
KFL+96:. MLN&9% *9

G#%=$"9
27
6.8
27 25.2
13.5
0
5
10
15
20
25
30
%
5$%&

O O O $-&'
1)
3-D(1/6:$"1


12.2
37.8
16.4
46
9.5
33.8
0
10
20
30
40
50
%
'$:9MPQ KFR 3!
5$%& 

S#-1 67'/$7&' 1)."1.-'
24.3 12.2
8.1 10.8
2.7 4.1
60.8
39.2
24.3 28.4
18.9
5.4 9.5
0
20
40
60
80
%
5$%& 
-1
$ TT  ??
'$71=- UO '&@ $.$1 D/69
Q#-1+V1+96:.1'*+$B/8'E


5.4
25.7
12.2
1.4
38.8
50
23.2
28.4
0
5
10
15
20
25
30
35
40
45
50
%
5$%& 
?ððW
5$-$-9 ?WFT, ?WGT, -1,' 9A-1,'
