Barnes et al developed an index for identifying a patient at risk for late-onset dementia. The authors are from the University of California at San Francisco, the San Francisco Veterans Affairs Medical Center, Kaiser Division of Research and the University of Pittsburgh.
Parameters:
(1) age of the patient in years
(2) modified mini-mental state examination (modified MMSE)
(3) digit symbol substitution test (DSST)
(4) body mass index (BMI)
(5) number of APOE epsilon 4 alleles
(6) grade of white matter disease on MRI
(7) grade of cerebral ventricle enlargement on MRI
(8) maximal thickness of the internal carotid artery in mm on ultrasound
(9) history of coronary artery surgery
(10) time to put on and button a shirt in seconds
(11) alcohol consumption
|
Parameter |
Finding |
Points |
|
age of the patient in years |
< 74 years of age |
0 |
|
|
75 to 79 years of age |
1 |
|
|
>= 80 years of age |
2 |
|
modified MMSE |
intermediate to high |
0 |
|
|
low |
2 |
|
digit symbol substitution test |
intermediate to high |
0 |
|
|
low |
2 |
|
body mass index (BMI) |
>= 18.5 kg per square m |
0 |
|
|
< 18.5 (underweight) |
2 |
|
number of APOE episolon 4 alleles |
0 |
0 |
|
|
>= 1 |
1 |
|
grade of white matter disease |
< Grade 3 |
0 |
|
|
>= Grade 3 |
1 |
|
grade for enlarged ventricles |
< Grade 4 |
0 |
|
|
Grade 4 |
1 |
|
thickness of internal carotid artery |
< 2.2 mm |
0 |
|
|
>= 2.2 mm |
1 |
|
history of coronary artery surgery |
no |
0 |
|
|
yes |
1 |
|
time to put on and button a shirt |
<= 45 seconds |
0 |
|
|
> 45 seconds |
1 |
|
alcohol consumed |
yes |
0 |
|
|
no |
1 |
where:
• The internal carotid artery measurement is given as total wall thickness and not intimal thickness.
late-life dementia risk index =
= SUM(points for all 11 parameters)
Interpretation:
• minimum score: 0
• maximum score: 15
• The higher the score the greater the risk of late-life dementia onset.
If the data in the figure on page 177 is analyzed:
percent probability of dementia =
= MIN(100, (0.6034 * ((index)^2)) + (1.199 * (index)) + 0.253)
Specialty: Neurology
