Vol.3, No.8, 487-490 (2013) Open Journal of Preventiv e Me dic ine
Awareness and use of cardiovascular risk scores by
family physicians in southeastern Ontario*
Murray F. Matangi1#, David W. J. Armstrong1, Amer M. Johri2, Ursula Jurt1, Peter M. Hollett3,
Robert W. Del Grande4, J. Paul DeYoung5, Joel M. Niznick6, Daniel D. Broiullard1
1The Kingston Heart Clinic, Kingston, Canada; #Corresponding Author: murraymatangi@hotmail.com
2Division of Cardiology, Kingston General Hospital and Queen’s University, Kingston, Canada
3Belleville General Hospital, Belleville, Canada
4Perth & Smiths Falls District Hospital, Perth, Canada
5Cornwall General Hospital, Cornwall, Canada
6Ottawa Cardiovascular Centre, Ottawa, Canada
Received 11 September 2013; revised 14 October 2013; accepted 26 October 2013
Copyright © 2013 Murray F. Matangi et al. This is an open access article distributed under the Creative Commons Attribution Li-
cense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background: Our objective was to determine the
assessment of cardiovascular risk by family
physicians. Methods: A questionnaire was sent
by mail or f ax regarding both a wareness and us e
of the various CV risk scores in southeastern
Ontario. Results: Of 181 family physicians sur-
veyed, 96% were aware of at least one CV risk
score and 40% were aware of the JUPI TER study.
Despite this awareness, 72% simply counted
risk factors to assess risk, rather than to calcu-
late risk using established scoring methods.
Only 23% used the JUPITER study criteria. This
suggests an under-estimated of overall CV risk
by family physician’s practicing in southeastern
Ont ario. Interpetation: Cardiovascular risk in pri-
mary care is being underestimated in southeas-
tern Ontario. Additional knowledge translation
strategies are required to enhance the family
physician’s awareness and use of established
risk scoring meth ods i f we are to re duce the bur-
den of CV disease.
Keyw ords: Risk Assessment; Primary Prevention;
Cardiovascular Disease
Cardiovascular (CV) risk stratification using a method
such as the Framingham risk score (FRS) for total CV
events is recommended in the 2012 Canadian lipid
guidelines [1]. Gupta and colleagues have recently pub-
lished data indicating that two-thirds of motivated Cana-
dian family physicians calculate the FRS [2]. They also
indicated that there were substantial gaps in knowledge
regarding the implementation of the FRS with respect to
modification of the risk by family history and clinical
scenarios that warrant hsCRP measurement, a marker of
inflammation [2]. Gupta and colleagues have stated their
results indicating a “best case scenario” as the physicians
selected from the 105 clinical sites across Canada chosen
for their expertise and heightened awareness of the Ca-
nadian lipid guidelines [2]. We feel it unlikely that this
best case scenario translates into routine family practice.
The purpose of our study was to conduct a survey of
family physicians to assess the awareness and use of the
various CV risk scores.
A group of community CV specialists and general in-
ternists conducted a survey of their referring family phy-
sicians in southeastern Ontario. The survey (Table 1)
was sent by facsimile (FAX) or letter to the family phy-
sicians’ office. All completed surveys were returned by
FAX to our facility, where the data were collected and
analyzed. We asked two simple series of questions: the
first was to assess whether the physician was aware of
the various CV risk scores and the second question was
what method(s) the physician used in day-to-day practice
to assess CV risk. The questionnaire was anonymous and
it was stressed to participating family physicians that
they should indicate what they actually do in daily prac-
tice, as opposed to what they think they should be doing.
The questionnaire was on a single sheet of pape (Table
1). HEART Score [3], a European CV risk assessment
*Funding sources: none; Disclosures: none.
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M. F. Matangi et al. / Open Journal of Preventive Medicine 3 (2013) 487-490
Table 1. Cardiovascular awareness and use questionnaire.
Vascular risk scoring systems that I know Yes No
Framingham risk score for global events
Framingham risk score for coronary events
Reynolds risk score
Heart score
JUPITER study criteria
ARIC risk score with carotid imaging
for coronary events
I use the following on eligible patients Yes No
Framingham risk score for global events
Framingham risk score for coronary events
Reynolds risk score
Heart score
JUPITER study criteria
ARIC risk score with carotid imaging for
coronary events
I count vascular risk factors to determine Statin Rx
I do not use any risk scoring system to
determine the need for Statin Rx
Note: This survey is anonymous so please indicate what you actually do and
not what you think you should be doing.
tool was added as a “control”. Most Canadian physicians
would not be familiar with this CV risk assessment tool.
Therefore an affirmative response rate to the awareness
and use of HEART Score was expected to be very low.
A considerable percentage of FPs stated they counted
vascular risks scores instead of using a conventional risk
score. We therefore calculated the diagnostic accuracy of
counting vascular risk factors (age, family history,
smoking, diabetes). In CARDIOfile™, our comprehen-
sive cardiology database, we selected males 40 and
females with 50 with no history of vascular disease and
not taking a statin (N = 1465 consecutive patients). There
were 647 patients who met these criteria and had their
FRS calculated: 292 females, mean age 65.1 ± 9.9, LDL
cholesterol 3.21 ± 0.97, HDL cholesterol 1.60 ± 0.42;
13.5% had diabetes, 8.2% were current smokers, 15.8%
had a family history of premature coronary disease. The
mean FRS for total CV events for females was 13.7 ± 8.4
There were 355 males, mean age 60.3 ± 12.0, LDL cho-
lesterol 3.05 ± 0.91, HDL cholesterol 1.42 ± 0.42; 10.7%
had diabetes, 20.3% were current smokers, 18.9% had a
family history of premature coronary disease. The mean
FRS for total CV events for males was 22.1 ± 10.0.
One hundred and eighteen family physicians out of
231 (51.1%) contacted by FAX returned the survey by
FAX compared to only 63 of 500 (12.6%) who were
contacted by letter giving an overall response of 181 of
731 (24.8%).
Ninety-six percent of family physicians were aware of
at least one of the various CV risk scores (mostly FRS);
44% were aware of the Reynolds risk score, and 40%
were aware of the JUPITER trial [4]. Only 5% had
awareness of the ARIC (Atherosclerosis risk in commu-
nities) risk score 5 which utilizes carotid ultrasound
(Figure 1, solid bars). As expected, the response rate to
the HEART score (1%) was very low. Sixty-six percent
were aware that the current FRS was a global risk score,
and 30% thought the currently recommended FRS was
still a coronary risk score. Despite this awareness of CV
risk scores, 72% of family physicians stated they count
risk factors to assess CV risk and the need for statin
therapy. Only 23% of those questioned used the JUPI-
TER study criteria for hsCRP (Figure 1, hatched bars).
Our cardiology database was used to determine the
accuracy of counting vascular risk factors to identify
high-risk patients, using the FRS for total CV events as
the gold standard (Table 2). The sensitivity and specific-
ity of counting vascular risk factors were relatively poor,
suggesting that counting vascular risk scores underesti-
mates CV risk in high risk patients and overestimates CV
risk in low and intermediate risk patients. Various risk
factor profiles demonstrate that simply counting risk fac-
tors is a poor method of stratifying vascular risk (Table
Our survey indicated that while 96% of family physi-
cians are aware of at least one of the many CV risk
scores, 72% often simply counted vascular risk factors to
assess CV risk. Counting vascular risk factors is quick
and is likely preferred because of the short time allotted
for each patient interview. Counting vascular risk factors
has a poor accuracy for detecting high-risk patients, as
many eligible patients will be excluded from therapeutic
Figure 1. Family physician cardiovascular risk score aware-
ness and use.
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M. F. Matangi et al. / Open Journal of Preventive Medicine 3 (2013) 487-490
Copyright © 2013 SciRes. SS OPEN A CCE
Table 2 . The accuracy of counting vascular risk scores for the detection of high risk patients according to Framingham risk score for
total CV events.
% [95% CI]
% [95% CI]
Positive Predictive Value,
% [95% CI]
Negative Predictive Value,
% [95% CI]
Males 74.6 [67.9 - 80.3] 82.5 [75.4 - 87.9] 49.9 [44.5 - 55.1] 50.1 [44.8 - 55.4]
Females 78.3 [66.4 - 86.9] 51.1 [44.4 - 57.8] 55.8 [49.9 - 61.6] 44.2 [38.4 - 50.1]
Table 3 . The proportion of patients with various risk factor profiles that have low, intermediate or high Framingham Risk Score for
total cardiovascular events. These data demonstrate that simply counting risk factors is a poor method for stratifying vascular risk.
FH = family history.
Age 50 - 69 yrs + FH (28) 3 (10.7) 8 (28.6) 17 (60.7)
Age 50 - 69 yrs + Smoking (22) 1 (5.0) 5 (22.7) 16 (72.7)
Age 50 - 69 yrs + FH + smoking (11) 1 (9.0) 3 (27.2) 7 (63.6)
Age 50 - 69 yrs and diabetic (25) 0 (0.0) 0 (0.0) 25 (100)
Males > 69 years (91) 0 (0.0) 6 (6.6) 85 (93.1)
Age 50 - 69 yrs + FH (28) 15 (53.6) 13 (46.8) 0 (0.0)
Age 50 - 69 yrs + Smoking (19) 6 (31.6) 8 (42.1) 5 (26.3)
Age 50 - 69 yrs + FH + smoking (9) 3 (33.3) 1 (11.1) 5 (55.6)
Age 50 - 69 yrs and diabetic (14) 3 (21.4) 5 (35.7) 6 (42.9)
Males > 69 years (93) 24 (25.8) 31 (33.3) 38 (40.8)
intervention. Interestingly, the sensitivity and specificity
of counting risk factors was lower in women compared
to men, and there is evidence that vascular risk remains
underestimated in women [5,6].
There is definite confusion regarding the current rec-
ommended version of the FRS, which is for total CV
events. We have published data indicating that simply
changing from the coronary version of the FRS to the
global version more than doubles the number of patients
who qualify for lipid lowering therapy [7]. Our current
survey indicated that 30% were aware of only the coro-
nary version of the FRS. However, it is important to note
that family physicians calculating the FRS for total CV
events may be unaware that it is for global CV risk strati-
The awareness and utilization of hsCRP were low.
Only 40% of family physicians were aware of the
JUPITER trial and only 23% indicated they use this
study in the risk assessment of their patients. Most
JUPITER patients appear to be low or intermediate risk
simply because their LDL-cholesterol is “normal” (<3.40
mmol/L). However, if one does not measure hsCRP then
one cannot detect these high-risk patients with a normal
LDL-cholesterol. Although the JUPITER trial 4 has re-
ceived widespread attention, it has been reported that
only half of family physicians view inflammation as im-
portant in the progression of atherosclerosis, and that
there is a significant knowledge and implementation
deficit when it comes to this important method of as-
sessing CV risk [2].
It is important to also consider data challenging the
tenets of the FRS as the gold standard of CV risk strati-
fication. For instance, half of patients that suffer a myo-
cardial infarction have normal LDL cholesterol levels [8].
Furthermore, based on current guidelines 75% of patients
do not qualify for statin therapy prior to suffering their
first myocardial infarction [8]. Clearly, more accurate
methods of risk assessment are essential, but it is equally
imperative that the use of emerging tools be translated
into clinical practice. Frankly, a useful tool, unused, is
Given the knowledge deficits identified, we believe as
cardiologists and educators a better job can be done to
enhance the family physician’s awareness and under-
M. F. Matangi et al. / Open Journal of Preventive Medicine 3 (2013) 487-490
standing of CV risk assessment. Additionally, we believe
simple technology should play an important role in the
assessment and implementation of CV risk in primary
care. The use of electronic medical records (EMR) has
been increasing in Ontario [9], and an electronic version
of the CV risk assessment should be an integral part of
any EMR. This would permit a streamlined and stan-
dardized method of efficiently identifying patients whose
quality for risk assessment, as well as any necessary
blood work and imaging may be required for a com-
plete risk assessment.
Our survey was an awareness and use survey, and we
did not assess either the knowledge or ability to imple-
ment the various CV risk scores.
The overall response rate to our survey was low (25%).
The response rate to FAX alone was excellent at 51%.
The letter response rate was very low at 13%. We believe
that the family physicians who responded represent the
motivated and are more likely to be committed to CV
risk assessment than those who did not respond.
Cardiovascular risk assessment in primary care in
southeastern Ontario is clearly being under-estimated. If
we are to reduce the burden of CV disease additional
strategies which are required. One strategy should in-
volve in a more active role of the EMR and the use of
email to alerting the family physician. Such a strategy
would lead to a more extensive use of evidenced based
lipid management.
The authors thank the physicians who responded to the question-
[1] Anderson, T.J., Grégoire, J., Hegele, R.A., Couture, P.,
Mancini, G.B., McPherson, R., Francis, G.A., Poirier, P.,
Lau, D.C., Grover, S., Genest, J., Jr., Carpentier, A.C.,
Dufour, R., Gupta, M., Ward, R., Leiter, L.A., Lonn, E.,
Ng, D.S., Pearson, G.J., Yates, G.M., Stone, J.A. and Ur, E.
(2013) 2012 Update of the Canadian Cardiovascular So-
ciety guidelines for the diagnosis and treatment of
dyslipidemia for the prevention of cardiovascular disease
in the adult. Canadian Journal of Cardiology, 29, 151-
157. http://dx.doi.org/10.1016/j.cjca.2012.11.032
[2] Gupta, M., Singh, N., Tsigoulis, M., Kajil, M., Hirjikaka,
S., Quan, A., Teoh, H. and Verma, S. (2012) Perceptions
of Canadian Primary care physicians towards cardiovas-
cular risk assessment and lipid management. Canadian
Journal of Cardiology, 28, 14-19.
[3] Conroy, R.M., Pyörälä, K., Fitzgerald, A.P., Sans, S., Me-
notti, A., De Backer, G., De Bacquer, D., Ducimetière, P.,
Jousilahti, P., Keil, U., Njølstad, I., Oganov, R.G., Thom-
sen, T., Tunstall-Pedoe, H., Tverdal, A., Wedel, H., Whin-
cup, P., Wilhelmsen, L. and Graham, I.M. (2003) Estima-
tion of ten-year risk of fatal cardiovascular disease in
Europe: the SCORE project. European Heart Journal, 24,
[4] Ridker, P.M., Danielson, E., Fonseca, F.A., Genest, J.,
Gotto, A.M., Jr., Kastelein, J.J., Koenig, W., Libby, P.,
Lorenzatti, A.J., MacFadyen, J.G., Nordestgaard, B.G.,
Shepherd, J., Willerson, J.T. and Glynn, R.J. (2008) Ro-
suvastatin to prevent vascular events in men and women
with elevated C-reactive protein. The New England
Journal of Medicine, 359, 2195.
[5] Mosca, L., Barrett-Connor, E. and Wenger, N.K. (2011)
Sex/Gender differences in cardiovascular disease preven-
tion what a difference a decade makes. Circulation, 124,
[6] Linton, M.R.F. and Fazio, S. (2003) A practical approach
to risk assessment to prevent coronary artery disease and
its complications. American Journal of Cardiology, 92,
19-26. http://dx.doi.org/10.1016/S0002-9149(03)00505-8
[7] Armstrong, D.W.J., Brouillard, D. and Matangi, M.F.
(2011) The effect of the change in the Framingham risk
score calculator between the 2006 and 2009 Canadian
lipid guidelines. Canadian Journal of Cardiology, 27,
167-170. http://dx.doi.org/10.1016/j.cjca.2010.12.025
[8] Sachdeva, A., Cannon, C.P., Deedwania, P.C., Labresh,
K.A., Smith, S.C., Jr., Dai, D., Hernandez, A. and Fon-
arow, G.C. (2009) Lipid levels in patients hospitalized
with coronary artery disease: An analysis of 136,905 hos-
pitalizations in Get With The Guidelines. American Heart
Journal, 157, 111-117.
[9] Biro, S.C., Barber, D.T. and Kotecha, J.A. (2012) Trends
in the use of electronic medical records. Canadian Family
Physician, 58, e21.
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