CARDIOVASCULAR JOURNAL OF AFRICA • Vol 23, No 3, April 2012
AFRICA
163
statistical power to achieve enough statistical accuracy for
individual predictions.
27
Lastly, the focus of cardiac risk models was originally on
pre-operative prediction of mortality, but complications and
potentially preventable morbidity are also important outcomes.
1,3
Ideally, a range of outcomes should be reported: mortality,
morbidity, changes in functional status and quality of life, cost of
care as well as patient-reported perceptions of the non-technical
aspects of care.
3
Discussion
Open-heart surgery is one of the most expensive surgical
procedures in a hospital. The cost of surgery can vary enormously
between patients with an uncomplicated recovery and those who
suffer from postoperative complications.
28
Risk stratification is not only essential for improvement
of surgical outcomes, but also allows quality analysis and
meaningful comparison of outcomes. Kolh (2006) stated that it
should be an integral part of cardiac surgical practice, and quoted
‘... being as essential to the surgeon as the knowledge of anatomy
and techniques’.
Clinical research and treatment strategies of cardiovascular
disease as well as risk-prediction models have largely been
developed in North America and Europe. However, the
applicability of results derived from these investigations is
unknown.
29
Popular risk models have been studied extensively
around the world. Of these models, the European System for
Cardiac Operative Risk Evaluation (EuroSCORE) has been
validated in different population settings and remains for many,
the gold standard.
1,12
Even though the mortality outcome predicted with the
EuroSCORE seems applicable in South African practice,
different stages of epidemiological transition are often at work
in South Africa and changing patterns in the development
of cardiovascular disease are observed in the various ethnic
populations.
11,30
Predictions of postoperative recovery in the
South African setting are therefore less well established. Given
the economic impact of interventional therapy and complications
related to intervention, it is incumbent on clinicians in South
Africa to ensure the optimal application of interventional therapy
and resource allocation.
As a result, cardiac surgeons in South Africa face three
options with regard to risk stratification: to simply use external
risk scores, knowing that the identified risks and attributed
weights might not correctly reflect their patient population; to
adjust the weight of the risk factors on the basis of their own
data; or to derive a new internal model from their own data
and recalibrate it periodically.
8
Despite continuous research, no
perfect risk-prediction model exists and the shortcomings of the
different models and criticism of the modelling processes have
been comprehensively discussed.
1,3,25
Variables that may affect patient outcome but which are
not necessarily related to pre-operative patient characteristics,
are often not taken into account. These include the skill and
experience of the surgical and postoperative care team, which
influences various aspects of the intra-operative and immediate
postoperative period.
1
For that reason, current risk-stratification
models can only score the risk of care and not the quality of
suitable care.
Conclusion
It is our hypothesis that the development of an integrated model
that includes hitherto unutilised intra-operative risk factors
as well as other known peri-operative risk factors predictive
of outcome should enable more accurate risk stratification
and consequently improved quality management of surgical
treatment of patients with cardiovascular disease in the South
African setting. Such a model would allow for improved clinical
decision making, assessment of surgical performance and quality
of care. Increasing efficiency through prediction of postoperative
complications would ultimately facilitate decisions to operate,
allocate resources and estimate costs.
28
References
1.
Granton J, Cheng D. Risk stratification models for cardiac surgery.
Semin Cardiothorac Vasc Anesth
2008;
12
(3): 167–174.
2.
Shahian DM, Blackstone EH, Edwards FH, Grover FL, Grunkemeier
GL, Naftel DC,
et al
. Cardiac Surgery Risk Models: A Positon Article.
Ann Thorac Surg
2004;
78
: 1868–1877.
3.
Heijmans JH, Maessen JG, Roekaerts HJ. Risk stratification for adverse
outcome in cardiac surgery.
Eur J Anaesth
2003;
20
: 515–527.
4.
Nilsson J, Algotsson L, Hoglund P, Luhrs C, Brandt J. Comparison of
19 preoperative risk stratification models on open-heart surgery
. Eur
Heart J
2006;
27
: 867–874.
5.
Kolh P. Importance of risk stratification models in cardiac surgery.
Eur
Heart J
2006;
27
: 768–769
6.
Chong C-F, Li Y-C, Wang T-L, Chang H. Stratification of adverse
outcomes by preoperative risk factors in coronary artery bypass graft
patients: An artificial neural network prediction model [online].
AMIA
Ann Symp Proc
2003; 160–164. Available from:
nih.gov/articlerender.fcg?artid=1480326. [Accessed 13.03.2008].
7.
Stoica SC, Sharples LD, Ahmed I, Roques F, Large SR, Nashef SAM.
Preoperative Risk Prediction And Intraoperative Events In Cardiac
Surgery.
Eur J Cardiothorac Surg
2002;
21
: 41–46.
8.
Ranucci M, Castelvecchio S, Menicanti L, Frigiola A, Pelissero G.
Risk of asessessing mortality risk in elective cardiac operations – age,
creatinine, ejection fraction, and the law of parsimoy.
Circulation
2009;
119
: 3053–3061.
9.
Biancari F, Kangasniemi O-P, Luukkonen J, Vuorisalo S, Satta J, Pokela
R, Juvonen T. Euroscore predicts immediate and late outcome after
coronary artery bypass surgery.
Ann Thorac Surg
2006;
82
: 57–61.
10. Roques F, Nashef SAM, Michel P, Gauducheau E, Vincentiis C,
Baudet E,
et al
. Risk factors and outcome in European cardiac surgery:
Analysis of the Euroscore multinational database of 19030 patients.
Eur
J Cardiothorac Surg
1999;
15
: 816–823.
11. Swart MJ, Joubert G. The Euroscore does well for the surgeon outside
Europe (Letter to the Editor).
Eur J Cardiothorac Surg
2004;
25
: 145.
12. Cortina Romero JM. Criteria for using risk models in cardiac surgery.
Rev Esp Cardiol
2008;
61
(6): 567–571.
13. Jin R, Grunkemeier GL. Additive vs. logistic risk models for cardiac
surgery mortality.
Eur J Cardiothorac Surg
2005;
28
: 240–243.
14. European SystemFor Cardiac Operative Risk Evaluation (EuroSCORE).
What is EuroSCORE [online]. Available from:
.
org/what_is_euroscore.htm. [Accessed: 09.12.2010].
15. Nashef SAM. The new EuroSCORE project.
Kardiol Pol
2010;
68
:
128–129.
16. Michel P, Roques F, Nashef SAM, The EuroSCORE Project group.
Logistic or additive EuroSCORE for high risk patients?
Eur J
Cardiothorac Surg
2003;
23
: 684–687.
17. ZingoneB, PappalardoA, Dreas L. Logistic versus additive EuroSCORE.
A comparative assessment of the two models in an independent popula-
tion sample.
Eur J Cardiothorac Surg
2004;
26
: 1134–1140.
18. European System for Cardiac Operative Risk Evaluation (EuroSCORE).
New EuroSCORE 2010 [online]. Available from:
.
org/EuroSCORE2010.htm. [Accessed: 09.03.2010].
