measuring cholesterol by l-b the liebermann-burchard method is used by the cdc to establish...
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Measuring cholesterol by L-B
• The Liebermann-Burchard method is used by the CDC to
establish reference materials
• Cholesterol esters are hydrolyzed and extracted into hexane
prior to the L-B reaction
HO
H2SO4/HOAc
HOO2S
Cholesterol Cholestahexaene sulfonic acid
max = 620 nm
L-B reagent
Enzymatic cholesterol methods
• Enzymatic methods are most commonly adapted to automated chemistry
analyzers
• The reaction is not entirely specific for cholesterol, but interferences in
serum are minimal
Cholesterol esters
Cholesterol
Cholesterylester
hydroxylase
Choles-4-en-3-one + H2O2
Cholesteroloxidase
Quinoneimine dye (max500 nm)
Phenol4-aminoantipyrinePeroxidase
Measuring HDL cholesterol
• Ultracentrifugation is the most accurate method
–HDL has density 1.063 – 1.21 g/mL
• Routine methods precipitate Apo-B-100 lipoprotein with a polyanion/divalent
cation
–Includes VLDL, IDL, Lp(a), LDL, and chylomicrons
HDL, IDL, LDL, VLDL HDL + (IDL, LDL, VLDL)Dextran sulfate
Mg++
• Newer automated methods use a modified form of cholesterol esterase, which selectively reacts with HDL cholesterol
• Newer automated methods use a modified form of cholesterol esterase, which selectively reacts with HDL cholesterol
HDL-C
• Determined using an anti human-β-lipoprotein antibody
that binds to non-HDL lipoproteins and allows the
quantification of HDL-C by the presence of a cholesterol
esterase and cholesterol oxidase/peroxidase (CHE and
CHO/POD) enzyme chromogen system
• Need for saline dilution when the triglycerides >1000
mg/dL (11.3 mmol/L)
HDL-C
• Audit - 0/18 specimens with triglycerides >1000 mg/dL
were diluted
• So, we decided to dilute when triglycerides >1000
mg/dL
• Re-audit - 0/17 specimens with triglycerides >1000
mg/dL (11.3 mmol/L) were diluted
HDL-C
• So, we decided to investigate the use of an
automated alert for the technical staff via the
LIS
• Re-audit showed that of 21/25 specimens with
triglycerides >1000 mg/dL were diluted
HDL-C
• Can we improve on this?
• Middleware may automatically result in:
–dilution
–re-analysis
–phoning of results
Measuring triglycerides
• LDL is often estimated based on triglyceride concentration, using the
Friedewald Equation:
[LDL chol] = [Total chol] – [HDL chol] – [Triglyceride]/2.19
Triglycerides
Glycerol + FFAsLipase
Glycerophosphate + ADPGlycerokinase
ATP
Dihydroxyacetone + H2O2
Glycerophasphateoxidase
PeroxidaseQuinoneimine dye (max 500 nm)
IS IT NOT EASIER TO PUT STATINS IN TAP WATER?
Pat Twomey
Royal Infirmary Edinburgh
How low should we go?
INTRODUCTION
• Atherosclerosis-related disease is the
principal cause of mortality in the
Western world
• Atherosclerosis-related disease is
destined to become the principal
cause of worldwide morbidity by 2020
INTRODUCTION
• How do we identify which patients would
benefit from cardiovascular risk factor
intervention as universal pharmacological
treatment is not
– practically possible,
– economically feasible nor
– psychologically desirable
INTRODUCTION
• Do we treat individual risk factors?
–Raised Cholesterol
–Low HDL-C
–Raised BP
• What threshold?
Serum Cholesterol Levels in Men*Framingham Heart Study
% P
op
ula
tio
n
0
10
20
30
40
*During first 16 years of study: Entry ages 30–40 yearsAdapted from Castelli WP Can J Cardiol 1988;4(suppl A):5A-10A.
MINo MI
150 200 250 300 350 400 450
Serum cholesterol
3.9(mg/dl)
(mmol/L)5.2 6.5 7.8 9.1 10.3 11.6
INTRODUCTION
Cardiovascular disease risk profiles Am Heart J 1991; 121:293-8.
FRAMINGHAM EQUATIONS
• Several sets of data
– 1967
–1973
–1976
– 1991
– 1998
Cardiovascular disease risk profiles Am Heart J 1991; 121:293-8.
FRAMINGHAM EQUATIONS
• Within each set, there are different disease types
–a CHD risk
–b Stoke risk (inc TIA)
–c Total cardiovascular disease risk
–d MI
–e Death from CHD
–f Death from cardiovascular disease
Cardiovascular disease risk profiles Am Heart J 1991; 121:293-8.
FRAMINGHAM EQUATIONS
=15.5305 + (28.4441*sex) + (-1.4792*ln(age)) + (-14.4588*ln(age)*sex) + (1.8515*(ln(age)2)*sex) + (-0.9119*ln(sysBP)) + (-0.2767*smoker) + (-0.7181*ln(t-cho/HDL-cho)) + (-0.1759*diabetes) + (-0.1999*diabetes*sex) + (-0.5868*LVH)
=e(0.9145 + (-0.2784*)
p(CHD – 10-yr) =
1-e(-e(ln(10)-/))
Sex: Male = 0; female = 1DM, smoke, LVH: 0 = No; 1 = Yes
FRAMINGHAM EQUATIONS
Joint British Recommendations Dec 1998
FRAMINGHAM EQUATIONS
Female?(yes=1,no=0) 0Age(years) 64SBP (mmHg) 150DBP (mmHg) 85Smokes?(yes=1,no=0) 0Total - C (mmol/ l) 5.5HDL - C (mmol/ l) 0.7Diabetes(yes=1,no=0) 0
Known to haveECG-LVH? (yes=1,no=0) 0
Period of predicted risk 10(years)
Joint British Recommendations Dec 1998
FRAMINGHAM EQUATIONS
CHD risk % Stroke risk %over 10 years over 10 years
SBP 29.8 4.9
DBP 27.7 3.6
Cardiovascular disease risk profiles Am Heart J 1991; 121:293-8.
FRAMINGHAM EQUATIONS
• The Framingham equations are derived by parametric regression model of epidemiological data
• The results produced are valid for populations
• Each population coefficient in the risk equation is subject to a confidence interval
FRAMINGHAM EQUATIONS
• Extrapolation to individuals is
assumed by many
• In addition, it is assumed that precise
results can be obtained from one
determination of risk factor status
and thus neglect the role of variation.
What we think we’re doing
What we think we’re doing
One Target: One Bullet
What we think we’re doing
Take Aim
What we think we’re doing
What we think we’re doing
Getting closer
What we think we’re doing
Identify the different individual from the crowd
What we think we’re doing (1)
Too Many Targets
Some scoring systems miss
What we think we’re doing (2)
Bad Marksmanship
BIOLOGICAL VARIATION
•Average population CV
– Total Cholesterol 6.5%
– HDL-C 7.5%
– SBP 7%
ANALYTICAL VARIATION
•CV
– Total Cholesterol 2.5%
– HDL-C 3.4%
– SBP 5%
TOTAL VARIATION
• CVtotal = [CVbiological2 + CVanalytical
2]1/2
– Total Cholesterol 6.9%
– HDL-C 8.2%
– SBP 8.6%
TOTAL VARIATION
• Average population 95% CI
– TC 5.0 +/- 0.7 mmole/L
– HDL-C 1.0 +/- 0.16 mmole/L
– SBP 140 +/- 24 mm Hg
CV
Biological Analytical Total
Cholesterol 6.5% 2.5% 6.9%
HDL-C 7.5% 3.4% 8.2%
SBP 7% 5% 8.6%
TOTAL VARIATION
• CVtotal = [CVChol2 + CVHDL-C
2 + CVSBP2]1/2
• CVtotal = [6.92 + 8.22 + 8.62]1/2
• CVtotal = 13.7%
POPULATION SIMULATION
1. Population of 5,000 males and 5,000 females
Add intra-individual and laboratory variation (100 simulants for each individual) and calculated CHD risk
POPULATION SIMULATION
• Different Cholesterol & HDL-C data used for male & female
• Lipids based on the Health Survey for England 1998
• Correlation between Cholesterol & HDL-C achieved by Polar-Marsaglia-Bray Cholesky decomposition matrix method
POPULATION SIMULATION
• Smokers - random 25%
• Assumed no diabetics
• SBP as per the Health Survey for
England 1998
• Age range 30 - 70
POPULATION SIMULATION
• LVH defined randomly but with a different frequency
for hypertensive & normotensive groups
• LVH assigned according to known population
frequencies - 29.4 cases /1000 hypertensive simulants
(defined as systolic BP >= 160mmHg) and 6.4 cases /
1000 normotensive simulants (defined as systolic BP
< 160mmHg)
POPULATION SIMULATIONMale mean Female mean
Cholesterol 5.8 mmol/l 5.6 mmol/l
HDL-C 1.3 mmol/l 1.6 mmol/l
TC:HDLcorrelation
r = 0.1 r = 0.07
SBP 136.8 mm Hg 132.5 mm Hg
CUMULATIVE FREQUENCY DISTRIBUTION
0%
20%
40%
60%
80%
100%
0% 10% 20% 30% 40%
'True' 10-year CHD Risk
Fre
qu
en
cy
CUMULATIVE FREQUENCY DISTRIBUTION
• > 15% 10 year CHD risk 15.0%
• > 20% 10 year CHD risk 7.65%
• > 30% 10 year CHD risk1.54%
CONFIDENCE INTERVALS
0%
5%
10%
15%
20%
25%
30%
35%
40%
0% 10% 20% 30% 40%
'True' Risk (%)
Es
tim
ate
d R
isk
(%
)
SINGLE MEASUREMENTS
95% CI CV%
15% +/- 5.1% 16.7%
20% +/- 6.0% 14.9%
30% +/- 6.9% 12.0%
DUPLICATE MEASUREMENTS
95% CI CV%
15% +/- 3.6% 12.0%
20% +/- 4.2% 10.5%
30% +/- 4.9% 8.2%
TRIPLICATE MEASUREMENTS
95% CI CV%
15% +/- 2.8% 9.3%
20% +/- 3.3% 8.3%
30% +/- 3.9% 6.5%
SINGLE v TRIPLICATE
• For every 100 whose mean risk >=
30% threshold
– 20 v 15 false positives
– 30 v 11 false negatives
– 50 v 26 incorrectly assigned
SINGLE v TRIPLICATE
• For every 100 whose mean risk >=
20% threshold
– 18 v 10 false positives
– 16 v 11 false negatives
– 34 v 21 incorrectly assigned
SINGLE v TRIPLICATE
• For every 100 whose mean risk >=
15% threshold
– 15 v 9 false positives
– 13 v 8 false negatives
– 28 v 17 incorrectly assigned
SUMMARY
• There is a significant variation in the Framingham risk equations due to biological and analytical variation
• Biological variation is the major contributor
SUMMARY
• Future risk thresholds will be lower for statin therapy
• Risk assessment imprecision increases with a decreasing risk threshold
• The absolute number of incorrect assignments will increase
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