Analysis of prognostic factors for in-hospital mortality in patients with unplanned re-exploration after cardiovascular surgery

OBJECTIVE: To explore the prognostic factors for in-hospital mortality in patients with unplanned re-exploration after cardiovascular surgery. METHODS: We retrospectively analyzed the data of 100 patients who underwent unplanned re-exploration after cardiovascular surgery in our hospital between May 2010 and May 2020. There were 77 males and 23 females, aged (55.1 ± 15.2) years. Demographic characteristics, surgical information, perioperative complications were collected to establish a database. These patients were divided into surviving and non-surviving groups according to in-hospital mortality. Logistic regression was used for multivariable analysis to explore the prognostic factors of in-hospital mortality. These statistically significant indicators were selected for drawing the receiver operating characteristic curve of the evaluation model, calculating the area under the curve (AUC) and evaluating the effectiveness of the new model with Hosmer–Lemeshow C-statistic. RESULTS: In-hospital mortality in patients with unplanned re-exploration after cardiovascular surgery was 26.0% (26/100). Multivariate logistics regression revealed that the operation time of unplanned re-exploration, the worst blood creatinine value within 48 h before the re-exploration, the worst lactate value within 24 h after the re-exploration, cardiac insufficiency, respiratory insufficiency, and acute kidney injury were independent prognostic factors (P < 0.05). The AUC of the new assessment model constituted by these prognostic factors was 0.910, and the Hosmer–Lemeshow C-statistic was 4.153 (P = 0.762). CONCLUSIONS: Operation time of unplanned re-exploration, worst serum creatinine value within 48 h before re-exploration, worst lactate value within 24 h after re-exploration, cardiac insufficiency, respiratory insufficiency, and acute kidney injury are the main prognostic factors for in-hospital mortality in patients with unplanned re-exploration after cardiovascular surgery. Identifying these prognostic factors can effectively facilitate preventive measures and improve patient outcomes.