共 42 条
Development of a prognostic nomogram for patients underwent extracorporeal circulation auxiliary to open cardiac surgery on hospital mortality: a retrospective cohort study
被引:0
作者:
Wang, Peihe
[1
,2
]
Lu, Meiling
[1
]
Huang, Yu
[1
]
Sun, Lu
[1
]
Han, Zhen
[1
]
机构:
[1] Peking Univ Shenzhen Hosp, Dept Cardiovasc Surg, 1120 Lianhua St, Shenzhen 518000, Peoples R China
[2] Shantou Univ, Med Coll, Shantou, Peoples R China
关键词:
Extracorporeal circulation;
cardiac surgery;
intensive care;
nomogram;
prediction model;
ACUTE KIDNEY INJURY;
PERIPHERAL ARTERIAL-DISEASE;
EUROSCORE II;
RISK;
SOCIETY;
EPIDEMIOLOGY;
ACCURACY;
CORONARY;
OUTCOMES;
MODELS;
D O I:
10.21037/jtd-24-24
中图分类号:
R56 [呼吸系及胸部疾病];
学科分类号:
摘要:
Background: Extracorporeal circulation auxiliary to open cardiac surgery (ECAOCS) is one of the most complex surgical procedures and carries a very high risk of death. We developed a nomogram from a retrospective study to predict the risk of death during patient hospitalization. Methods: All clinical data were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. We extracted clinical variables for the first 24 hours after admission to the intensive care unit (ICU) in a total of 880 patients who underwent ECAOCS. All patients were randomly divided into training and validation cohort in a ratio of 7:3. All variables included in the study were subjected to univariate logistic regression analysis. In order to prevent overfitting and to address the problem of severe covariance, all factors with P<0.05 in the univariate logistic regression analysis were analyzed using the least absolute shrinkage and selection operator (LASSO) regression. A multivariate logistic regression model was developed based on the factors output from the LASSO regression and a nomogram was plotted. The receiver operating characteristic (ROC) curve was constructed and the area under the curve (AUC) was calculated in training and validation cohort. Finally, the evaluation of the model was performed by calibration curves and Hosmer-Lemeshow goodness-of-fit test (HL test) and decision curve analysis (DCA) was performed. Results: Indicators included in the nomogram were anion gap (AG), central venous pressure (CVP), glucose, creatinine (Cr), prothrombin time (PT), activated partial thromboplastin time (APTT), bicarbonate ion (HCO3-), cerebrovascular disease (CVD), peripheral vascular disease (PVD), and acute myocardial infarction (AMI). Conclusions: Our study developed a model for predicting postoperative hospital mortality in patients underwent ECAOCS by incorporating AG, CVP, glucose, Cr, APTT, HCO3-, CVD, AMI, and PVD from the first 24 hours after admission to the ICU.
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页码:4174 / 4185
页数:12
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