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Mortality after cardiac surgery ranges from 2.94 to 32.5% depending on type
of surgery and different populations (Mehta et al. 2002, Serigar et al.
2013, Chang et al. 2016). numerous risk scores were developed for mortality
prediction after cardiac surgery but still there are some major differences among
these scores with regard to score design and the initial population on which the
score was developed (Geissler et al. 2000). Postoperative risk scoring gives information of the postoperative
situation, In addition to the preoperative patient condition (Pätilä et al.
2006). Postoperative risk scoring systems such as the Cardiac Surgery Score
(CASUS), the Acute Physiology and Chronic Health Evaluation (APACHE II) and the
Sequential Organ Failure Assessment (SOFA) score are used to predict mortality after
cardiac surgery but they were not tested on our patient population so we
compared the accuracy of CASUS, APACHE II and SOFA scores in predicting mortality
after cardiac surgery in our centre

Our prospective study comprised 103 adult
patients who underwent open heart surgery in the  Cardiothoracic Surgery Department – Tanta
University Hospitals from October  2015 to December 2017. Data on the
preoperative, intraoperative and postoperative status was recorded for each
patient. the postoperative patient data was recorded every hour and the worst
data was taken every 24 hours to calculate the postoperative scores. the APACHE
2 score was calculated once in the first postoperative 24 hours, SOFA score was
calculated every 24 hours for maximum of 4 postoperative days, CASUS score was
calculated in the 2nd and 4th postoperative days. Clinical outcome was defined
as postoperative morbidity and 30-day mortality. Morbidity was expressed by:
duration of ventilatory support, length of stay in the postoperative
ICU and ward. For patients readmitted to the ICU, we considered only the
initial stay in the ICU. In cases of re intubation, we considered only the
initial period of mechanical ventilation.

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The collected data were organized, tabulated and statistically analyzed
using SPSS version 19 (Statistical Package for Social Studies) created by IBM,
Illinois, Chicago, USA. For numerical values the range mean and standard
deviations were calculated. The differences between two mean values were used
using Mann-Whitney test as data were not found to follow the normal
distribution. For categorical variable the number and percentage were
calculated and differences between subcategories were tested by Monte Carlo
exact test. The correlation between two variables was calculated using
Pearson’s correlation coefficient. Linear regression was used for multivariate
analysis of numerical variables affecting survival. The ROC curve was found to
test predictability of survival by SOFA, CACUS and APACHE 2. The level of
significant was adopted at p<0.05. our study was conducted on 103 adult patients with 30-day mortality 10.3%, all patients preoperative characteristics are shown in table (1) showing that EF, platelets count, PO2 and bilirubin level are predictors of  mortality after cardiac surgery. As shown in table (2) there is statistically significant difference between survivors and non-survivors regarding the value of SOFA (p: 0.001) and APACHE II (p: 0.001) scores. ROC curves were plotted showing that both APACHE II score(0.878) and SOFA score (0.878) have a good predictive power of 30-day mortality after cardiac surgery compared with the poor predictive power of the CASUS score (0.673) as shown in table (4). However, multivariate analysis identified APACHE II score and preoperative platelets count as the independent predictors of mortality after cardiac surgery in as shown in table (3) Regarding prediction of morbidity, all scores showed significant results in predicting length of ICU stay and postoperative hours of ventilation, on the contrary none of the scores showed correlation with the length of hospital stay as shown in table (5). The observed 30-day mortality was 10.3 % which is considered to be  higher than the average mortality reported in previous studies 9.3%, 9.6% and 6% (Curiel-Balsera et al. 2013, Junior et al. 2015, Exarchopoulos et al. 2015) respectively. this may be due to The higher rate of postoperative cardiac and respiratory complications. twenty seven/103 (26.2%) of the study group had cardiac complications while 16/103 patients (15.5%) had respiratory complications. A factor that was identified in this study as an independent predictor of mortality after cardiac surgery, was the preoperative platelet count. We found that the preoperative platelet count was higher in non survivors {285.40+67.42 (103)} compared to survivors {232.32+64.41 (103)}. Unal et al. 2013 reported that the mean platelet volume (MPV) reflecting platelet production rate and activation and the platelet count were moderately correlated with adverse events after CABG including ischemic vascular events, recurrent MI or death. The reported platelet count in their patients with adverse events was 262 ± 66(103). The  APACHE II score, calculated in the first day of ICU admission, was identified as another independent predictor of postoperative mortality. It has a good predictive power for the 30-day mortality after cardiac surgery (AUC: 0.868, p value <0.001). Supporting our results Chang et al. 2017 studied 483 patients after CABG and found that APACHE II score in the first ICU day was effective in prediction of mortality (AUC: 0.86, P value <0.001).  Other authors demonstrated that APACHE II score at ICU admission successfully predicted 30-day mortality in 150 cardiac surgery patients (AUC: 0.82, P value 0.001) (Exarchopoulos et al. 2015). The most important difference between APACHE II score and other scores is that it is estimated during the first 24 hours of ICU admission so it gives a snapshot of risk using data in the early time of admission but it still cannot guide clinical decision making reliably after the initial ICU period and prediction could be inaccurate as postoperative events have not occurred yet (Howitt et al. 2016). This can be solved if APACHE II score have the ability to predict the risk daily. In our study the maximum SOFA score in the first four days well predicted the 30-day mortality after cardiac surgery (AUC: 0.878, P value 0.001). The daily SOFA score showed significant results in all days with the 3rd day being the best (AUC: 0.918, P value: 0.001) in prediction of mortality. this is in accordance with Patila et al. 2006 who calculated the SOFA for 857 cardiac surgery patients, the SOFA score in the first three days showed good discrimination for mortality with the overall maximum SOFA score being slightly better(AUC: 0.76) and Ceriani et al. 2003 who calculated SOFA score for the first 10 postoperative days in cardiac surgery patients, the worst score, the maximum score, the difference between the two values and the first day SOFA score.  All the four derivatives showed good discrimination with the worst daily score demonstrating the best performance. A word of caution about SOFA score is that the cardiovascular component of the SOFA score is based on the administration of vasoactive medication using specific protocols such as dopamine being administered before noradrenaline to treat hypotension. In many centers, clinicians know that these patterns of drug administration are not followed and this may lead to diminished confidence in the SOFA score despite reports of good performance in multiple studies ( Badreldin et al. 2012, Patila et al. 2006, Doerr et al. 2011, Exarchopoulos et al.2015). Regarding CASUS score, the statistical analysis showed that the maximum CASUS score was  not significant as a predictor  of  30-day mortality after cardiac surgery (AUC: 0.673, P value: 0.105). On the contrary to our results, the  mean and maximum CASUS score were validated for prediction of 30-day mortality by Doerr at al. 2011 and performed well in the first 6 postoperative days after cardiac surgery with maximum CASUS score (AUC: >90) and Exarchopoulos et al. 2015 who found that CASUS score showed good
discrimination and calibration in the first postoperative day after cardiac
surgery with AUC 0.89. The poor results of CASUS score in our study
in comparison to other studies  may be
attributed to  the difference in  patient populations as  it lacks its 
application  in different  countries 
and  it has not been tested in
multicenter studies and accordingly has not gained much popularity. Another reason is that CASUS score has some volatile
variables that may change from one hour to another such as lactate and pressure
adjusted heart rate (PAR).

Comparing the three scoring systems regarding their
predictive power of the 30-days mortality after cardiac surgery in this study,
showed that  APACHE II score and SOFA
score (AUC: 0.878) has a better ability to predict 30-day mortality than CASUS
score (AUC: 0.673)

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