Cargando…
Three Logistic Predictive Models for the Prediction of Mortality and Major Pulmonary Complications after Cardiac Surgery
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 retr...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10456464/ https://www.ncbi.nlm.nih.gov/pubmed/37629658 http://dx.doi.org/10.3390/medicina59081368 |
_version_ | 1785096705709965312 |
---|---|
author | Bignami, Elena Guarnieri, Marcello Giambuzzi, Ilaria Trumello, Cinzia Saglietti, Francesco Gianni, Stefano Belluschi, Igor Di Tomasso, Nora Corti, Daniele Alfieri, Ottavio Gemma, Marco |
author_facet | Bignami, Elena Guarnieri, Marcello Giambuzzi, Ilaria Trumello, Cinzia Saglietti, Francesco Gianni, Stefano Belluschi, Igor Di Tomasso, Nora Corti, Daniele Alfieri, Ottavio Gemma, Marco |
author_sort | Bignami, Elena |
collection | PubMed |
description | 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 < 0.001), New York Heart Association (NYHA) class (p < 0.001) and emergent surgery (p = 0.036); predictors for non-invasive mechanical ventilation were advanced age (p < 0.001), low ejection fraction (p = 0.023), higher body mass index (p < 0.001) and preoperative renal failure (p = 0.043); predictors for postoperative pulmonary complications were preoperative chronic obstructive pulmonary disease (p = 0.007), preoperative kidney injury (p < 0.001) and NYHA class (p = 0.033). In the “surgery model” predictors for mortality were intraoperative inotropes (p = 0.003) and intraoperative intra-aortic balloon pump (p < 0.001), which also predicted the incidence of postoperative pulmonary complications. There were no specific variables in the surgery model predicting the use of non-invasive mechanical ventilation. In the “intensive care unit model”, predictors for mortality were postoperative kidney injury (p < 0.001), tracheostomy (p < 0.001), inotropes (p = 0.029) and PaO(2)/FiO(2) ratio at discharge (p = 0.028); predictors for non-invasive mechanical ventilation were kidney injury (p < 0.001), inotropes (p < 0.001), blood transfusions (p < 0.001) and PaO(2)/FiO(2) ratio at the discharge (p < 0.001). Conclusions: In this retrospective study, we identified the preoperative, intraoperative and postoperative characteristics associated with mortality and complications following cardiac surgery. |
format | Online Article Text |
id | pubmed-10456464 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-104564642023-08-26 Three Logistic Predictive Models for the Prediction of Mortality and Major Pulmonary Complications after Cardiac Surgery Bignami, Elena Guarnieri, Marcello Giambuzzi, Ilaria Trumello, Cinzia Saglietti, Francesco Gianni, Stefano Belluschi, Igor Di Tomasso, Nora Corti, Daniele Alfieri, Ottavio Gemma, Marco Medicina (Kaunas) Article 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 < 0.001), New York Heart Association (NYHA) class (p < 0.001) and emergent surgery (p = 0.036); predictors for non-invasive mechanical ventilation were advanced age (p < 0.001), low ejection fraction (p = 0.023), higher body mass index (p < 0.001) and preoperative renal failure (p = 0.043); predictors for postoperative pulmonary complications were preoperative chronic obstructive pulmonary disease (p = 0.007), preoperative kidney injury (p < 0.001) and NYHA class (p = 0.033). In the “surgery model” predictors for mortality were intraoperative inotropes (p = 0.003) and intraoperative intra-aortic balloon pump (p < 0.001), which also predicted the incidence of postoperative pulmonary complications. There were no specific variables in the surgery model predicting the use of non-invasive mechanical ventilation. In the “intensive care unit model”, predictors for mortality were postoperative kidney injury (p < 0.001), tracheostomy (p < 0.001), inotropes (p = 0.029) and PaO(2)/FiO(2) ratio at discharge (p = 0.028); predictors for non-invasive mechanical ventilation were kidney injury (p < 0.001), inotropes (p < 0.001), blood transfusions (p < 0.001) and PaO(2)/FiO(2) ratio at the discharge (p < 0.001). Conclusions: In this retrospective study, we identified the preoperative, intraoperative and postoperative characteristics associated with mortality and complications following cardiac surgery. MDPI 2023-07-26 /pmc/articles/PMC10456464/ /pubmed/37629658 http://dx.doi.org/10.3390/medicina59081368 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Bignami, Elena Guarnieri, Marcello Giambuzzi, Ilaria Trumello, Cinzia Saglietti, Francesco Gianni, Stefano Belluschi, Igor Di Tomasso, Nora Corti, Daniele Alfieri, Ottavio Gemma, Marco Three Logistic Predictive Models for the Prediction of Mortality and Major Pulmonary Complications after Cardiac Surgery |
title | Three Logistic Predictive Models for the Prediction of Mortality and Major Pulmonary Complications after Cardiac Surgery |
title_full | Three Logistic Predictive Models for the Prediction of Mortality and Major Pulmonary Complications after Cardiac Surgery |
title_fullStr | Three Logistic Predictive Models for the Prediction of Mortality and Major Pulmonary Complications after Cardiac Surgery |
title_full_unstemmed | Three Logistic Predictive Models for the Prediction of Mortality and Major Pulmonary Complications after Cardiac Surgery |
title_short | Three Logistic Predictive Models for the Prediction of Mortality and Major Pulmonary Complications after Cardiac Surgery |
title_sort | three logistic predictive models for the prediction of mortality and major pulmonary complications after cardiac surgery |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10456464/ https://www.ncbi.nlm.nih.gov/pubmed/37629658 http://dx.doi.org/10.3390/medicina59081368 |
work_keys_str_mv | AT bignamielena threelogisticpredictivemodelsforthepredictionofmortalityandmajorpulmonarycomplicationsaftercardiacsurgery AT guarnierimarcello threelogisticpredictivemodelsforthepredictionofmortalityandmajorpulmonarycomplicationsaftercardiacsurgery AT giambuzziilaria threelogisticpredictivemodelsforthepredictionofmortalityandmajorpulmonarycomplicationsaftercardiacsurgery AT trumellocinzia threelogisticpredictivemodelsforthepredictionofmortalityandmajorpulmonarycomplicationsaftercardiacsurgery AT sagliettifrancesco threelogisticpredictivemodelsforthepredictionofmortalityandmajorpulmonarycomplicationsaftercardiacsurgery AT giannistefano threelogisticpredictivemodelsforthepredictionofmortalityandmajorpulmonarycomplicationsaftercardiacsurgery AT belluschiigor threelogisticpredictivemodelsforthepredictionofmortalityandmajorpulmonarycomplicationsaftercardiacsurgery AT ditomassonora threelogisticpredictivemodelsforthepredictionofmortalityandmajorpulmonarycomplicationsaftercardiacsurgery AT cortidaniele threelogisticpredictivemodelsforthepredictionofmortalityandmajorpulmonarycomplicationsaftercardiacsurgery AT alfieriottavio threelogisticpredictivemodelsforthepredictionofmortalityandmajorpulmonarycomplicationsaftercardiacsurgery AT gemmamarco threelogisticpredictivemodelsforthepredictionofmortalityandmajorpulmonarycomplicationsaftercardiacsurgery |