Three Logistic Predictive Models for the Prediction of Mortality and Major Pulmonary Complications after Cardiac Surgery

Abstract

Background and Objectives: Pulmonary complications are a leading cause of morbidity after cardiac surgery. The aim of this study was to develop models to predict postoperative lung dysfunction and mortality. Materials and Methods: This was a single-center, observational, retrospective study. We retrospectively analyzed the data of 11,285 adult patients who underwent all types of cardiac surgery from 2003 to 2015. We developed logistic predictive models for in-hospital mortality, postoperative pulmonary complications occurring in the intensive care unit, and postoperative non-invasive mechanical ventilation when clinically indicated. Results: In the “preoperative model” predictors for mortality were advanced age (p p p = 0.036); predictors for non-invasive mechanical ventilation were advanced age (p p = 0.023), higher body mass index (p p = 0.043); predictors for postoperative pulmonary complications were preoperative chronic obstructive pulmonary disease (p = 0.007), preoperative kidney injury (p p = 0.033). In the “surgery model” predictors for mortality were intraoperative inotropes (p = 0.003) and intraoperative intra-aortic balloon pump (p p p p = 0.029) and PaO2/FiO2 ratio at discharge (p = 0.028); predictors for non-invasive mechanical ventilation were kidney injury (p p p 2/FiO2 ratio at the discharge (p Conclusions: In this retrospective study, we identified the preoperative, intraoperative and postoperative characteristics associated with mortality and complications following cardiac surgery.

Keywords

• cardiac anesthesia
• mortality
• postoperative pulmonary complications