ABSTRACT
Objective To explore the risk factors affecting prognosis of critically ill patients following cardiac surgery, furthermore, to assess severity and keep alarm earlier. Methods A retrospective study was conducted. The clinical data of critically ill patients following cardiac surgery admitted to intensive care unit (ICU) of the Affiliated Hospital of Guizhou Medical University from January 1st 2014 to December 31st 2018 were enrolled. The clinical characteristics, acute physiology and chronic health evaluation Ⅱ (APACHEⅡ) and the worst laboratory examination within 24 hours after ICU admission, and the duration of mechanical ventilation, length of ICU stay, using continuous renal replacement therapy (CRRT), accepting vasoactive agents such as norepinephrine, dopamine or dobutamine and blood products such as red blood cells, plasma or platelets were recorded. The patients were divided into survival group and dead group based on discharge prognosis, and the difference in clinical data between the two groups was compared. Binary multivariate Logistic regression analysis was used to screen the risk factors affecting the prognosis of critically ill patients following cardiac surgery, and the receiver operating characteristic (ROC) curve was plotted to analyze the predictive value of these risk factors. Results In total, 97 patients after cardiac operation were admitted to ICU during the five years. Thirty-two patients were excluded owing to age less than 16 years old, no more than 24 hours of the length of ICU stay, without the outcomes of myocardium enzymes or myocardium markers within the first 24 hours or admitted only for pacemaker. Finally, 65 patients met the criteria, with 40 survived and 25 died. Compared with survival group, APACHEⅡ scores, the level of serum uric acid, serum creatinine (SCr), cardiac troponin T (cTnT), brain natriuretic peptide (BNP), procalcitonin (PCT) and the rate of patients accepting CRRT, vasoactive agents and blood products in dead group were significantly increased with significant differences; however, there was no statistically difference in gender, age, body weight index (BMI), distribution of types of cardiac surgery, ratio of patients suffered from hypertension and diabetes, mean arterial pressure (MAP), white blood cell (WBC), coagulation, length of ICU stay, or duration of mechanical ventilation between the two groups. Binary multivariate Logistic regression analysis showed that APACHEⅡ scores [odds ratio (OR) = 1.123, 95% confidence interval (95%CI) = 1.004-1.257, P = 0.043] and cTnT (OR = 1.496, 95%CI = 1.038-2.158, P = 0.031) were the independent risk factors for prognosis of critical ill patients following cardiac surgery. ROC curve analysis showed that APACHEⅡ score and cTnT had predictive value for prognosis of critical ill patients following cardiac surgery, the best was exerted when APACHEⅡ score combined with cTnT, the area under the ROC curve (AUC) was 0.839, the joint prediction probability was 0.42, the sensitivity was 80.0%, and the specificity was 64.0%. Conclusion APACHEⅡscore and cTnT may be one of independent risk factors for prognosis of critical ill patients following cardiac surgery, and there will be far more greater predictive value when APACHEⅡ score combined with cTnT.