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

CASUS and APACHE II score in predicting mortality after coronary artery bypass grafting

Background

This study aims to compare Cardiac Surgery Score (CASUS) and the Acute Physiology and Chronic Health Evaluation (APACHE II) scoring systems for predicting mortality in patients undergoing isolated coronary artery bypass grafting.

Methods

Between January 2019 and March 2019, a total of 204 patients (166 males, 38 females; mean age: 60.5±0.7 years; range, 59.2 to 61.9 years) who underwent isolated coronary artery bypass grafting and were monitored at least for 24 h in the intensive care unit postoperatively were included. Pre-, intra-, and postoperative data were recorded. The CASUS and APACHE II scores were calculated using the most abnormal values for each variable during the first 24 h, postoperatively. Clinical outcomes were seven-day mortality and 30-day mortality, need for reintubation, readmission to the intensive care unit, length of intensive care unit stay and length of hospital stay.

Results

The 30-day overall mortality was 4.9% (n=10). The CASUS scores were significantly higher for patients developing mortality within 30 days postoperatively (p=0.030) and for patients needing reintubation (p=0.003). In the receiver operating characteristic curve analysis predicting seven-day mortality and prolonged intensive care unit stay, the area under curve was higher for CASUS scoring compared to APACHE II (0.90 vs. 0.72 and 0.82 vs. 0.76).

Conclusion

The CASUS may prove to be a more reliable scoring system than APACHE II for predicting mortality and morbidity in patients undergoing isolated coronary artery bypass grafting.

External Validation of the Cardiac Surgery Score in a Quaternary Hospital in the United States of America

BACKGROUND

The Cardiac Surgery Score (CASUS) was developed to assist in predicting post-cardiac surgery mortality using parameters measured in the intensive care unit. It is calculated by assigning points to ten physiologic variables and adding them to obtain a score (additive CASUS), or by logistic regression to weight the variables and estimate the probability of mortality (logistic CASUS). Both additive and logistic CASUS have been externally validated elsewhere, but not yet in the United States of America (USA). This study aims to validate CASUS in a quaternary hospital in the USA and compare the predictive performance of additive to logistic CASUS in this setting.

METHODS

Additive and logistic CASUS (postoperative days 1-5) were calculated for 7098 patients at Cleveland Clinic from January 2015 to February 2017. 30-day mortality data were abstracted from institutional records and the Death Registries for Ohio State and the Centers for Disease Control. Given a low event rate, model discrimination was assessed by area under the curve (AUROC), partial AUROC (pAUC), and average precision (AP). Calibration was assessed by curves and quantified using Harrell's Emax, and Integrated Calibration Index (ICI).

RESULTS

30-day mortality rate was 1.37%. For additive CASUS, odds ratio for mortality was 1.41 (1.35-1.46, P <0.001). Additive and logistic CASUS had comparable pAUC and AUROC (all >0.83). However, additive CASUS had greater AP, especially on postoperative day 1 (0.22 vs. 0.11). Additive CASUS had better calibration curves, and lower Emax, and ICI on all days.

CONCLUSIONS

Additive and logistic CASUS discriminated well for postoperative 30-day mortality in our quaternary center in the USA, however logistic CASUS under-predicted mortality in our cohort. Given its ease of calculation, and better predictive accuracy, additive CASUS may be the preferred model for postoperative use. Validation in more typical cardiac surgery centers in the USA is recommended.

Analysis of the Performance of Daily Surgery Score (CASUS) in Patients with Mixed Racial Profile after Cardiac Surgery: A Single-Center Retrospective Study

OBJECTIVE

The aim was to look at the Cardiac Surgery Score (CASUS) assessment after cardiac surgery, and compare it with the intensive care unit (ICU) mortality and morbidity, in a racially diverse group of patients, in a single center.

DESIGN

Clinical retrospective study analyzing data from 319 patients over a 1-year duration.

SETTING

Cardiothoracic intensive care unit (CTICU) of a tertiary care center.

PARTICIPANTS

All patients who underwent cardiac surgery between January 1 and December 31, 2017.

INTERVENTIONS

Review of electronic patient records.

MEASUREMENTS AND RESULTS

Daily CASUS assessments (calculated on an online application and recorded on patient electronic records) were retrieved. The variables of CASUS used for the study were CASUS value on postoperative day 1 (POD1-CASUS), on death/discharge from CTICU (Dis-CASUS), mean of all CASUS values during CTICU stay (M-CASUS), and differential CASUS (Dif- CASUS) [CASUS POD 1 - CASUS on discharge]. The receiver operating characteristic (ROC) curve for the diagnostic level of POD 1-CASUS, indicating mortality, was calculated. A value of >6.5 for POD 1 CASUS had 80% sensitivity and 84% specificity, with area under the curve value 0.756 (95% confidence interval: 0.46 to 1). The mean values of POD1-CASUS (8.6 ± 6), M-CASUS (8.2 ± 5.2), and Dis-CASUS (7.8 ± 5.7) were significantly higher in cases of mortality, compared to the others. POD1-CASUS, M-CASUS, and Dis-CASUS were found to be statistically significantly elevated in patients with acute kidney injury (AKI) and postoperative stroke, and in those who were readmitted to the CTICU after initial discharge. Patients with POD1-CASUS ≥6.5 had a statistically significant association with mortality and postoperative morbidity (p < 0.05). Findings from multivariate logistic regression indicated that body mass index (BMI), ICU readmission, length of mechanical ventilation, and length of ICU stay remained associated significantly with POD1 CASUS ≥6.5.

CONCLUSION

This study found that CASUS on POD 1, mean values of CASUS during CTICU stay, and CASUS at death/discharge from CTICU predicted ICU mortality after cardiac surgery in this racially diverse group. The CASUS derivatives can be used to predict unfavorable outcomes after cardiac surgery. A POD1-CASUS value of 6.5 or more could signify mortality and postoperative morbidity.

Validation of Cardiac Surgery Score (CASUS) in Postoperative Cardiac Patients

Introduction. Cardiac Surgery Score (CASUS) was introduced in 2005 as the first postoperative scoring system specific for patients who had cardiac surgery. Prior to this, European System for Cardiac Operative Risk Evaluation (EuroSCORE) has been used preoperatively, while Intensive Care National Audit and Research Centre Score (ICNARC) and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, which are widely used in general intensive care unit population, have been used to score cardiac patients postoperatively. The development of CASUS by Hekmat and colleagues for use in postoperative cardiac patients aims to change this. We wanted to validate CASUS against the well-established preoperative Logistic EuroSCORE, and postoperative APACHE II and ICNARC scores. Method. Institutional approval for this study was granted by the Audit and Clinical Governance Committee. We analyzed prospectively collected data of patients who had cardiac surgery in Castle Hill Hospital between January 2016 and September 2018. All patients who underwent surgery in the unit would have had Logistic EuroSCORE, APACHE, and ICNARC scores calculated as standard. CASUS was then calculated for these patients based on their day 1 postoperative variables. The scoring systems were compared and data presented as area under the receiver operating characteristic curve. Result. Our study shows that CASUS is the best predictor of mortality followed by ICNARC, Logistic EuroSCORE, and APACHE II. ICNARC score remains the most accurate predictor of renal and pulmonary complication followed by CASUS. Conclusion. CASUS is a useful scoring system in post-cardiac surgery patients. The accuracy of CASUS and ICNARC scores in predicting mortality, pulmonary, and renal complications are comparable.

Predictive Factors of Long-Term Stay in the ICU after Cardiac Surgery: Logistic CASUS Score, Serum Bilirubin Dosage and Extracorporeal Circulation Time

Objective

To test the capacity of the Logistic CASUS Score on the second postoperative day, the total serum bilirubin dosage on the second postoperative day and the extracorporeal circulation time, as possible predictive factors of long-term stay in Intensive Care Unit after cardiac surgery.

Methods

Eight-two patients submitted to cardiac surgery with extracorporeal circulation were selected. The Logistic CASUS Score on the second postoperative day was calculated and bilirubin dosage on the second postoperative day was measured. The extracorporeal circulation time was also registered. Patients were divided into two groups: Group A, those who were discharged up to the second day of postoperative care; Group B, those who were discharged after the second day of postoperative care.

Results

In this study, 40 cases were listed in Group A and 42 cases in Group B. The mean extracorporeal circulation time was 83.9±29.4 min in Group A and 95.8±29.31 min in Group B. Extracorporeal circulation time was not significant in this study (P=0.0735). The level of P significance of bilirubin dosage on the second postoperative day was 0.0003 and an area under the ROC curve of 0.708 with a cut-off point at 0.51 mg/dl was registered. The level of P significance of Logistic CASUS Score on the second postoperative day was 0.0001 and an area under the ROC curve of 0.723 with a cut-off point at 0.40% was registered.

Conclusion

The Logistic CASUS Score on the second postoperative day has shown to be better than the bilirubin dosage on the second postoperative day as a predictive tool for calculating the length of stay in intensive care unit during the postoperative care period of patients. Notwithstanding, extracorporeal circulation time has failed to prove itself as an efficient tool to predict an extended length of stay in intensive care unit.

Combination of European System for Cardiac Operative Risk Evaluation (EuroSCORE) and Cardiac Surgery Score (CASUS) to Improve Outcome Prediction in Cardiac Surgery

Background

We hypothesized that the combination of a preoperative and a postoperative scoring system would improve the accuracy of mortality prediction and therefore combined the preoperative ‘additive EuroSCORE‘ (European system for cardiac operative risk evaluation) with the postoperative ‘additive CASUS’ (Cardiac Surgery Score) to form the ‘modified CASUS’.

Material/Methods

We included all consecutive adult patients after cardiac surgery during January 2007 and December 2010 in our prospective study. Our single-centre study was conducted in a German general referral university hospital. The original additive and the ‘modified CASUS’ were tested using calibration and discrimination statistics. We compared the area under the curve (AUC) of the receiver characteristic curves (ROC) by DeLong’s method and calculated overall correct classification (OCC) values.

Results

The mean age among the total of 5207 patients was 67.2±10.9 years. Whilst the ICU mortality was 5.9% we observed a mean length of ICU stay of 4.6±7.0 days. Both models demonstrated excellent discriminatory power (mean AUC of ‘modified CASUS’: ≥0.929; ‘additive CASUS’: ≥0.920), with no significant differences according to DeLong. Neither model showed a significant p-value (<0.05) in calibration. We detected the best OCC during the 2^nd day (modified: 96.5%; original: 96.6%).

Conclusions

Our ‘additive’ and ‘modified’ CASUS are reasonable overall predictors. We could not detect any improvement in the accuracy of mortality prediction in cardiac surgery by combining a preoperative and a postoperative scoring system. A separate calculation of the two individual elements is therefore recommended.

Inclusion of 'ICU-Day' in a Logistic Scoring System Improves Mortality Prediction in Cardiac Surgery

Background

Prolonged intensive care unit (ICU) stay is a predictor of mortality. The length of ICU stay has never been considered as a variable in an additive scoring system. How could this variable be integrated into a scoring system? Does this integration improve mortality prediction?

Material/Methods

The ‘modified CArdiac SUrgery Score’ (CASUS) was generated by implementing the length of stay as a new variable to the ‘additive CASUS’. The ‘logistic CASUS’ already considers this variable. We defined outcome as ICU mortality and statistically compared the three CASUS models. Discrimination, comparison of receiver operating characteristic curves (DeLong’s method), and calibration (observed/expected ratio) were analyzed on days 1–13.

Results

Between 2007 and 2010, we included 5207 cardiac surgery patients in this prospective study. The mean age was 67.2±10.9 years. The mean length of ICU stay was 4.6±7.0 days and ICU mortality was 5.9%. All scores had good discrimination, with a mean area under the curve of 0.883 for the additive and modified, and 0.895 for the ‘logistic CASUS’. DeLong analysis showed superiority in favor of the logistic model as from day 5. The calibration of the logistic model was good. We identified overestimation (days 1–5) and accurate (days 6–9) calibration for the additive and ‘modified CASUS’. The ‘modified CASUS’ remained accurate but the ‘additive CASUS’ tended to underestimate the risk of mortality (days 10–13).

Conclusions

The integration of length of ICU stay as a variable improves mortality prediction significantly. An ‘ICU-day’ variable should be included into a logistic but not an additive model.

SAPS 3 is not superior to SAPS 2 in cardiac surgery patients

OBJECTIVES

Cardiac surgery patients are excluded from SAPS2 but included in SAPS3. Neither score is evaluated for this exclusive population; however, they are used daily. We hypothesized that SAPS3 may be superior to SAPS2 in outcome prediction in cardiac surgery patients.

DESIGN

All consecutive patients undergoing cardiac surgery between January 2007 and December 2010 were included in our prospective study. Both models were tested with calibration and discrimination statistics. We compared the AUC of the ROC curves by DeLong's method and calculated OCC values.

RESULTS

A total of 5207 patients with mean age of 67.2 ± 10.9 years were admitted to the ICU. The mean length of ICU stay was 4.6 ± 7.0 days and the ICU mortality was 5.9%. The two tested models had acceptable discriminatory power (AUC: SAPS2: 0.777-0.875; SAPS3: 0.757-893). SAPS3 had a low AUC and poor calibration on admission day. SAPS2 had poor calibration on Days 1-6 and 8.

CONCLUSIONS

Despite including cardiac surgery patients, SAPS3 was not superior to SAPS2 in our analysis. In this large cohort of ICU cardiac surgery patients, performance of both SAPS models was generally poor. In this subset of patients, neither scoring system is recommended.

Rapid clinical evaluation: an early warning cardiac surgical scoring system for hand-held digital devices

OBJECTIVES

The purpose of this study was to develop a new scoring system for the prompt recognition of clinical deterioration and early treatment in postoperative cardiac surgical patients.

METHODS

All consecutive adult patients undergoing cardiac surgery between 1st January 2007 and 31st December 2010 were included. The new score was calculated daily until intensive care unit (ICU) discharge. The score consists of 11 variables representing six different organ systems. Performance was assessed using receiver-operating characteristic (ROC) curves and calibration tests.

RESULTS

A total of 5207 patients with a mean age of 67.2 ± 10.9 years were admitted to the ICU after cardiac surgery. The operations performed covered the whole spectrum of cardiac surgery. ICU mortality was 5.9%. The mean length of ICU stay was 4.6 ± 7.0 days. The new score had an excellent discrimination with areas under the ROC curves between 0.91 and 0.96. Calibration was also excellent reflected by observed/expected mortality ratios ranging between 1.0 and 1.26.

CONCLUSIONS

The new score is a simple and reliable scoring system to assess organ dysfunction in cardiac intensive care patients. It is designed especially for personal digital assistants to simplify and accelerate the process of risk stratification in cardiac surgical ICUs.

A comparative study of four intensive care outcome prediction models in cardiac surgery patients

Background

Outcome prediction scoring systems are increasingly used in intensive care medicine, but most were not developed for use in cardiac surgery patients. We compared the performance of four intensive care outcome prediction scoring systems (Acute Physiology and Chronic Health Evaluation II [APACHE II], Simplified Acute Physiology Score II [SAPS II], Sequential Organ Failure Assessment [SOFA], and Cardiac Surgery Score [CASUS]) in patients after open heart surgery.

Methods

We prospectively included all consecutive adult patients who underwent open heart surgery and were admitted to the intensive care unit (ICU) between January 1^st 2007 and December 31^st 2008. Scores were calculated daily from ICU admission until discharge. The outcome measure was ICU mortality. The performance of the four scores was assessed by calibration and discrimination statistics. Derived variables (Mean- and Max- scores) were also evaluated.

Results

During the study period, 2801 patients (29.6% female) were included. Mean age was 66.9 ± 10.7 years and the ICU mortality rate was 5.2%. Calibration tests for SOFA and CASUS were reliable throughout (p-value not < 0.05), but there were significant differences between predicted and observed outcome for SAPS II (days 1, 2, 3 and 5) and APACHE II (days 2 and 3). CASUS, and its mean- and maximum-derivatives, discriminated better between survivors and non-survivors than the other scores throughout the study (area under curve ≥ 0.90). In order of best discrimination, CASUS was followed by SOFA, then SAPS II, and finally APACHE II. SAPS II and APACHE II derivatives had discrimination results that were superior to those of the SOFA derivatives.

Conclusions

CASUS and SOFA are reliable ICU mortality risk stratification models for cardiac surgery patients. SAPS II and APACHE II did not perform well in terms of calibration and discrimination statistics.