Risk Stratification Models for Cardiac Surgery

Abstract

A wide variety of risk stratification systems have been developed to quantify the risk of cardiac surgery. Generally, the focus has been on mortality; however, more recently models have been developed that allow the preoperative prediction of the incidence of morbidity, including renal failure, infection, prolonged ventilation, and neurologic deficit. Many of these risk stratification models are developed from large databases of cardiac surgical patients. Patient and surgical factors that are present preoperatively are assessed for their predictive value for postoperative complications. Risk factors that are found to be significant are assigned a specific weight in the overall summation of risk. These models have been used as tools to compare surgeon's results, institutional outcomes, individual patient risk, and within quality improvement programs. This article will focus on the European System for Cardiac Operative Risk Evaluation, the Society of Thoracic Surgeons score, the Parsonnet score, Cleveland Clinic Model, the Bayes model, and the Northern New England Score.

Prevalence of co-morbidities among adult patients presented for open heart surgery and the implication on convalescence period

“…doctors to aid patient counseling and decision making. [8][9][10][11][12] Validation of these risk stratification tools and comparisons between their performances was investigated thoroughly in recent literature. [13][14][15][16][17][18][19] Although risk scoring was originally designed to predict perioperative mortality after cardiac surgery its use for prediction intensive care unit length of stay and duration of hospitalization has been increasing.…”

A new heart surgery clinic: Open Heart Surgery Outcomes at Karabuk Training and Research Hospital: Assessment of the first year

“…We believe that the reasons of the high total mortality rate in our study include the limited number of patients (n=71), high rate of emergency surgeries (n=10, 14.2%), and the high proportion of high-risk patients (40.6%) although the difference was not statistically significant. Risk factors for operative mortality have been analyzed in a number of studies [15,[17][18][19][20][21]. In these studies, the mortality predictors according to decreasing importance were listed as follows: emergency surgical operation, renal dysfunction, re-operation, advanced age (>75 years), low EF (<30%), female gender, other comorbidities (COPD, peripheral vascular disease, Diabetes Mellitus, cerebrovascular diseases, etc.).…”

Risk Prediction and Outcome Analysis

“…This is where there is great utility in having access to a reliable, easy-to-use risk prediction scoring system and tool. Granton and Cheng [32] have gathered information describing several of the predictive scoring systems available: the EuroSCORE [33,34], the STS score, the Parsonnet score [35,36], and regional models such as the Cleveland Clinic model and the NNE score. Additionally, the AusSCORE [37] has been developed and studied for Australian patients.…”