Prediction of prolonged length of stay in the intensive care unit after cardiac surgery: the need for a multi-institutional risk scoring system.
OBJECTIVE
Predictive models for the length of stay (LOS) in the intensive care unit (ICU) following cardiac surgery have been developed in the last decade. These risk models use different endpoint and risk factor definitions. This review discusses the need for a uniform multi-institutional risk scoring system for a prolonged ICU LOS.


METHODS
The MEDLINE database was searched for studies assessing the prognostic value of clinical variables predicting ICU LOS. Information on study design, patient population, extended ICU LOS definition, and predictors was retrieved.


RESULTS
There is no consensus on the definition of a prolonged ICU LOS. This is mainly because some studies take the continuous variables of "days in the intensive care unit" and try to make it dichotomous when actually the LOS should be analyzed as a "continuous variable." We also report a cardiac surgeon-related component. The most important risk factors were: increased age, no elective surgery, type of cardiac surgery, low left ventricular ejection fraction, recent myocardial infarction, history of pulmonary disease, history of renal disease, and reoperation/reexploration.


CONCLUSIONS
There is a need for the development of a multi-institutional risk scoring system for prolonged ICU LOS following cardiac surgery. This predictive model could aid in quality assessment, practice improvement, patient counseling, and decision making. In order to develop this risk model, uniformed and standardized definitions are needed.
Messaoudi
Nouredin
N
Department of Cardiac Surgery, University Hospital of Antwerp, Edegem, Belgium.
De Cocker
Jeroen
J
Stockman
Bernard
B
Bossaert
Leo L
LL
Rodrigus
Inez E R
IE
D000465:Algorithms; D001530:Belgium; D006305:Health Status Indicators; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D007902:Length of Stay / Q000706:statistics & numerical data*; D016015:Logistic Models; D008962:Models, Theoretical; D018570:Risk Assessment; D013903:Thoracic Surgery / Q000706:statistics & numerical data*; D013997:Time Factors