Construction and Application of a Model for Predicting the Risk of Delirium in Postoperative Patients With Type a Aortic Dissection

Background: Postoperative delirium (POD), an alteration in a patient's consciousness pattern, can affect the treatment and prognosis of a disease.Objective: To construct a prediction model for delirium in patients with type A aortic dissection after surgery and to validate its effectiveness.Met...

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Autores principales:	Junfeng He, Qing Ling, Yuhong Chen
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	type A aortic dissection postoperative delirium predictive model nursing factor Surgery RD1-811
Acceso en línea:	https://doaj.org/article/51947d064ff0403794cb0d61137d7958
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spelling	oai:doaj.org-article:51947d064ff0403794cb0d61137d79582021-11-18T06:27:04ZConstruction and Application of a Model for Predicting the Risk of Delirium in Postoperative Patients With Type a Aortic Dissection2296-875X10.3389/fsurg.2021.772675https://doaj.org/article/51947d064ff0403794cb0d61137d79582021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fsurg.2021.772675/fullhttps://doaj.org/toc/2296-875XBackground: Postoperative delirium (POD), an alteration in a patient's consciousness pattern, can affect the treatment and prognosis of a disease.Objective: To construct a prediction model for delirium in patients with type A aortic dissection after surgery and to validate its effectiveness.Methods: A retrospective cohort design was used to study 438 patients undergoing surgical treatment for type A aortic dissection from April 2019 to June 2020 in tertiary care hospitals. POD (n = 78) and non-delirium groups (n = 360) were compared and analyzed for each index in the perioperative period. A prediction model was established using multifactorial logistic regression, and 30 patients' perioperative data were collected for model validation.Results: Eight predictors were included in this study: smoking, diabetes, previous cardiovascular surgery, ejection fraction (EF), time to aortic block, acute kidney injury, low cardiac output syndrome, and pulmonary complications. The area under the receiver operating characteristic (ROC) curve of the constructed prediction model was 0.98 ± 0.005, and the Youden index was 0.91. The validation results showed 97% sensitivity, 100% specificity, and 93% accuracy. The expression of the model was Z = Smoking assignment* – 2.807 – 6.009Diabetes assignment – 2.994Previous cardiovascular surgery assignment – 0.129Ejection fraction assignment + 0.071Brain perfusion time assignment – 2.583Acute kidney injury assignment – 2.916Low cardiac output syndrome assignment – 3.461*Pulmonary related complications assignment + 20.576.Conclusion: The construction of an effective prediction model for the risk of delirium in patients after type A aortic stratification can help identify patients at high risk of POD early. It also provides a reference for healthcare professionals in the prevention and care of these patients.Junfeng HeQing LingYuhong ChenFrontiers Media S.A.articletype A aortic dissectionpostoperative deliriumpredictive modelnursingfactorSurgeryRD1-811ENFrontiers in Surgery, Vol 8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	type A aortic dissection postoperative delirium predictive model nursing factor Surgery RD1-811
spellingShingle	type A aortic dissection postoperative delirium predictive model nursing factor Surgery RD1-811 Junfeng He Qing Ling Yuhong Chen Construction and Application of a Model for Predicting the Risk of Delirium in Postoperative Patients With Type a Aortic Dissection
description	Background: Postoperative delirium (POD), an alteration in a patient's consciousness pattern, can affect the treatment and prognosis of a disease.Objective: To construct a prediction model for delirium in patients with type A aortic dissection after surgery and to validate its effectiveness.Methods: A retrospective cohort design was used to study 438 patients undergoing surgical treatment for type A aortic dissection from April 2019 to June 2020 in tertiary care hospitals. POD (n = 78) and non-delirium groups (n = 360) were compared and analyzed for each index in the perioperative period. A prediction model was established using multifactorial logistic regression, and 30 patients' perioperative data were collected for model validation.Results: Eight predictors were included in this study: smoking, diabetes, previous cardiovascular surgery, ejection fraction (EF), time to aortic block, acute kidney injury, low cardiac output syndrome, and pulmonary complications. The area under the receiver operating characteristic (ROC) curve of the constructed prediction model was 0.98 ± 0.005, and the Youden index was 0.91. The validation results showed 97% sensitivity, 100% specificity, and 93% accuracy. The expression of the model was Z = Smoking assignment* – 2.807 – 6.009Diabetes assignment – 2.994Previous cardiovascular surgery assignment – 0.129Ejection fraction assignment + 0.071Brain perfusion time assignment – 2.583Acute kidney injury assignment – 2.916Low cardiac output syndrome assignment – 3.461*Pulmonary related complications assignment + 20.576.Conclusion: The construction of an effective prediction model for the risk of delirium in patients after type A aortic stratification can help identify patients at high risk of POD early. It also provides a reference for healthcare professionals in the prevention and care of these patients.
format	article
author	Junfeng He Qing Ling Yuhong Chen
author_facet	Junfeng He Qing Ling Yuhong Chen
author_sort	Junfeng He
title	Construction and Application of a Model for Predicting the Risk of Delirium in Postoperative Patients With Type a Aortic Dissection
title_short	Construction and Application of a Model for Predicting the Risk of Delirium in Postoperative Patients With Type a Aortic Dissection
title_full	Construction and Application of a Model for Predicting the Risk of Delirium in Postoperative Patients With Type a Aortic Dissection
title_fullStr	Construction and Application of a Model for Predicting the Risk of Delirium in Postoperative Patients With Type a Aortic Dissection
title_full_unstemmed	Construction and Application of a Model for Predicting the Risk of Delirium in Postoperative Patients With Type a Aortic Dissection
title_sort	construction and application of a model for predicting the risk of delirium in postoperative patients with type a aortic dissection
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/51947d064ff0403794cb0d61137d7958
work_keys_str_mv	AT junfenghe constructionandapplicationofamodelforpredictingtheriskofdeliriuminpostoperativepatientswithtypeaaorticdissection AT qingling constructionandapplicationofamodelforpredictingtheriskofdeliriuminpostoperativepatientswithtypeaaorticdissection AT yuhongchen constructionandapplicationofamodelforpredictingtheriskofdeliriuminpostoperativepatientswithtypeaaorticdissection
_version_	1718424478219763712

Construction and Application of a Model for Predicting the Risk of Delirium in Postoperative Patients With Type a Aortic Dissection

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