Association of Critical Value With 28-Day Mortality After Cardiac Surgery.

Abstract

Objective: The emergence of critical values gives a warning to the medical safety of hospitalized patients, especially Cardiosurgery Intensive Care Unit (CSICU) patients. The aim of this study was to investigate the association between early postoperative critical values and the prognosis of patients after cardiac surgery.

Methods: Clinical data of the patients were obtained from the Cardiac Critical Care Clinical Database of the Cardiovascular Intensive Care Unit of Nanjing First Hospital. A total of 1,598 consecutive patients undergoing cardiac surgery were enrolled in this retrospective cohort study, during the period from July 2019 to December 2020. According to whether critical value occurred within 7 days after cardiac surgery, patients were divided into two groups: the critical value group and control group. COX regression and survival analysis were performed to analyze the clinical data of the two groups. The area under the receiver operating characteristic curve (ROC) was used to assess the critical value's predictive value and determine the optimal cutoff value.

Results: With patients in the critical value group, the 28-day mortality after cardiac surgery was 21.98%, significantly higher than that of the control group (P < 0.05). Logistic regression analysis revealed the APACHE II score (Adjusted HR-1.11, 95% CI-1.043-1.185) and critical value group (Adjusted HR-13.57, 95% CI-6.714-27.435 ) were independent predictors of 28-day mortality after cardiac surgery. The ROC curve showed that the critical value case model (AUC = 0.748 ± 0.052, P < 0.05) could effectively predict the 28-day mortality, and the optimum cutoff was 1 case (sensitivity 52.63%, specificity 95.70%).

Conclusions: One or more reported cases of critical values in the early postoperative period could be an independent risk factor for 28-day mortality in patients undergoing cardiac surgery. The predictive model based on critical value might be effective in clinical therapy and risk stratification.