Outcome prediction in cardiac surgery: the first logistic scoring model for cardiac surgical intensive care patients.

BACKGROUND: In the process of risk stratification, a logistic calculation of mortality risk in percentage is easier to interpret. Unfortunately, there is no reliable logistic model available for postoperative intensive care patients. The aim of this study was to present the first logistic model for postoperative mortality risk stratification in cardiac surgical intensive care units. This logistic version is based on our previously presented and established additive model (CASUS) that proved a very high reliability. METHODS: In this prospective study, data from all adult patients admitted to our ICU after cardiac surgery over a period of three years (2007-2009) were collected. The Log-CASUS was developed by weighting the 10 variables of the additive CASUS and adding the number of postoperative day to the model. Risk of mortality is predicted with a logistic regression equation. Statistical performance of the two scores was assessed using calibration (observed/expected mortality ratio), discrimination (area under the receiver operating characteristic curve), and overall correct classification analyses. The outcome measure was ICU mortality. RESULTS: A total of 4054 adult cardiac surgical patients was admitted to the ICU after cardiac surgery during the study period. The ICU mortality rate was 5.8%. The discriminatory power was very high for both additive (0.865-0.966) and logistic (0.874-0.963) models. The logistic model calibrated well from the first until the 13th postoperative day (0.997-1.002), but the additive model over- or underestimated mortality risk (0.626-1.193). CONCLUSION: The logistic model shows statistical superiority. Because of the precise weighing the individual risk factors, it offers a reliable risk prediction. It is easier to interpret and to facilitate the integration of mortality risk stratification into the daily management more than the additive one.

Comparison between Sequential Organ Failure Assessment score (SOFA) and Cardiac Surgery Score (CASUS) for mortality prediction after cardiac surgery.

BACKGROUND: Our purpose was to evaluate and compare the accuracy of the "Sequential Organ Failure Assessment" score (SOFA) and the "Cardiac Surgery Score" (CASUS) for the prediction of mortality after cardiac surgery. METHODS: Between January 1, 2007 and December 31, 2008 we prospectively included all consecutive adult patients admitted to our intensive care unit (ICU) after cardiac surgery. Both scoring systems were calculated daily from the 1st day in the ICU (day of operation) until the 7th ICU day. We evaluated the ICU mortality prediction of both models using calibration and discrimination statistics. RESULTS: 2801 patients (29.6% females) were included. Mean age was 66.9 ± 10.7 years. Intensive care unit mortality was 5.2%. The calibration of the "Sequential Organ Failure Assessment Score" and "Cardiac Surgery Score" was reliable for all days (p ≥ 0.05). CASUS was more accurate in predicting survival and mortality compared to SOFA for all days, as evidenced by the larger areas under the Receiver Operating Characteristic curves. CONCLUSIONS: Both CASUS and SOFA are reliable mortality prediction tools after cardiac surgery. However, CASUS was more accurate in predicting the individual patient's risk of mortality. Thus, use of the CASUS in cardiac surgery intensive care units is recommended.

Prognostic value of daily cardiac surgery score (CASUS) and its derivatives in cardiac surgery patients.

BACKGROUND: We aimed to validate the usefulness of CASUS derivatives for cardiac surgery patients and their reliability for daily decision making. METHODS: We included, prospectively, the data of all adult cardiac surgery patients who had an ICU stay of at least 12 hours between 20 January 2003 and 14 October 2005 in the Department of Cardiothoracic Surgery of the University of Cologne, Germany. Data were collected until ICU discharge and included initial, maximum, mean, and total CASUS values. δ CASUS (difference from initial value) was calculated at 48 and 96 hours postoperatively. The predictive efficacy of the derivatives was tested with calibration and discrimination statistics. RESULTS: 2372 patients were included with a mean age of 66.2 ± 11.2 years. ICU mortality was 3.6 % (n =85). Mean ICU stay was 3.0 ± 6.1 days. The discrimination was very good for all derivatives (area under the curve ranged between 0.988 and 0.926). The calibration was also good except for the total CASUS, which showed a significant difference between the expected and observed mortality. Increased δ CASUS at 48 hours (1038 patients) and 96 hours (435 patients) correlated with an increase in mortality (23.1 % and 42.9 %, respectively), and conversely a decreased mortality rate was observed with decreasing values (1.9 % and 3.8 %, respectively). CONCLUSION: CASUS derivatives including δ CASUS have a good prognostic value for cardiac surgery patients with regard to the prediction of mortality and survival during ICU stay, with the exception of total CASUS which was not informative.