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Background: There are many prognostic models and scoring systems in use to predict mortality in ICU patients. The only general ICU scoring system developed and validated for patients after cardiac surgery is the APACHE-IV model. This is, however, a labor-intensive scoring system requiring a lot of data and could therefore be prone to error. The SOFA score on the other hand is a simpler system, has been widely used in ICUs and could be a good alternative. The goal of the study was to compare the SOFA score with the APACHE-IV and other ICU prediction models. Methods: We investigated, in a large cohort of cardiac surgery patients admitted to Dutch ICUs, how well the SOFA score from the first 24 h after admission, predict hospital and ICU mortality in comparison with other recalibrated general ICU scoring systems. Measures of discrimination, accuracy, and calibration (area under the receiver operating characteristic curve (AUC), Brier score, R 2 , and Ĉ-statistic) were calculated using bootstrapping. The cohort consisted of 36,632 Patients from the Dutch National Intensive Care Evaluation (NICE) registry having had a cardiac surgery procedure for which ICU admission was necessary between January 1st, 2006 and June 31st, 2018. Results: Discrimination of the SOFA-, APACHE-IV-, APACHE-II-, SAPS-II-, MPM 24-II-models to predict hospital mortality was good with an AUC of respectively: 0.809, 0.851, 0.830, 0.850, 0.801. Discrimination of the SOFA-, APACHE-IV-, APACHE-II-, SAPS-II-, MPM 24-II-models to predict ICU mortality was slightly better with AUCs of respectively: 0.809, 0.906, 0.892, 0.919, 0.862. Calibration of the models was generally poor. Conclusion: Although the SOFA score had a good discriminatory power for hospital-and ICU mortality the discriminatory power of the APACHE-IV and SAPS-II was better. The SOFA score should not be preferred as mortality prediction model above traditional prognostic ICU-models.

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Acute kidney injury (AKI) is an important risk factor for chronic kidney disease, renal replacement therapy (RRT), and mortality. However, predicting AKI with currently available markers remains problematic. We assessed the predictive value of urinary tissue inhibitor of metalloprotease-2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP7) regarding the need for RRT, and 30-day mortality, in elective cardiac surgery patients. In 344 elective cardiac surgery patients, we measured urinary TIMP-2 and IGFBP7 and serum creatinine at baseline and directly after surgery. Discrimination of both urinary biomarkers was assessed by the C-statistic. Model improvement for each biomarker when added to a basic model containing serum creatinine and duration of surgery was tested by the net-reclassification index (cf-NRI) and integrated discrimination index (IDI). At baseline, mean age was 66 years and 67% were men. Of all patients, 22 required RRT following surgery. IGFBP7 pre- and post-surgery and change in TIMP-2 during surgery predicted RRT with a C-statistic of about 0.80. However, a simple model including baseline serum creatinine and duration of surgery had a C-statistic of 0.92, which was improved to 0.93 upon addition of post-surgery TIMP-2 or IGFBP7, with statistically significant cf-NRIs but non-significant IDIs. Post-surgery TIMP-2 and IGFBP predicted 30-day mortality, with C-statistics of 0.74 and 0.80. In conclusion, in elective cardiac surgery patients, pre- and peri-operative clinical variables were highly discriminating about which patients required RRT after surgery. Nonetheless, in elective cardiac surgery patients, urinary TIMP-2 and IGFBP7 improved prediction of RRT and 30-day mortality post-surgery.

In elective cardiac surgery, MR-pro-adrenomedullin measured between 6 and 18 hours after admission to the ICU is a better predictor of hospital mortality in comparison with the Acute Physiology and Chronic Health Evaluation IV score.