Target, application, and interpretation of scores and alternative methods for risk assessment in cardiac surgery.
BACKGROUND
The more popular the use of different methods for risk adjustment becomes, the more often data are applied without any regard about the primary target and/or about important assumptions. Furthermore, risk adjustment is no longer restricted for quality assurance purposes, but became a "tool" of health policy. Few working groups currently use risk adjustment for the development of new therapeutic concepts. The aim of our study is to clarify possibilities and limitations of popular risk adjustment methods.


METHODS
4985 Patients underwent isolated CABG. Statistics was performed by calculating descriptive statistics, Parsonnet, and Higginsscores. Furthermore, the parametric, time-adjusted hazard function by Blackstone was used.


RESULTS
Descriptive statistics allows intra-, and interinstitutional comparisons of single items to identify "outlying" results. Risk scores aim to predict preoperatively the risk category of the patient who undergoes cardiac surgery. However, since different scores are based on a score-specific combination of variables, and different definitions of the investigation interval, different results may occur, when different scores are calculated for a single patient. However, the use for example, of scores in patient groups allows description of changing risk structures. Most of the scores derive from univariate analyses and monophasic functions. However, survival curves are predominantly multiphasic and require a consideration of the time-dependency of "risk factors".


CONCLUSIONS
An increasing number of patients with severe comorbidity undergoes cardiac surgery. To evaluate reliably present and futurous therapeutic options, risk adjustment is necessary. Since various tools for risk-adjustment are available, a serious discussion about reliability and application is necessary.
Osswald
B R
BR
Department of Cardiac Surgery, University of Heidelberg, Germany. brigitte_osswald@med.uni-heidelberg.de
Tochtermann
U
U
Schweiger
P
P
Thomas
C
C
Göhring
D
D
Vahl
C F
CF
Hagl
S
S
D000368:Aged; D013504:Cardiovascular Surgical Procedures; D001026:Coronary Artery Bypass / Q000401:mortality / Q000706:statistics & numerical data*; D003327:Coronary Disease / Q000150:complications / Q000401:mortality / Q000503:physiopathology / Q000601:surgery*; D048909:Diabetes Complications; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D011787:Quality of Health Care; D012044:Regression Analysis; D018570:Risk Assessment / Q000379:methods*; D016019:Survival Analysis; D013997:Time Factors