A Comparison of a Machine Learning Model with EuroSCORE II in Predicting Mortality after Elective Cardiac Surgery: A Decision Curve Analysis

被引:125
作者
Allyn, Jerome [1 ,2 ]
Allou, Nicolas [1 ,2 ]
Augustin, Pascal [2 ]
Philip, Ivan [2 ,3 ]
Martinet, Olivier [1 ]
Belghiti, Myriem [1 ]
Provenchere, Sophie [2 ]
Montravers, Philippe [2 ,4 ]
Ferdynus, Cyril [5 ,6 ]
机构
[1] Ctr Hosp Univ Felix Guyon, Reanimat Polyvalente, St Denis, France
[2] CHU Bichat Claude Bernard, AP HP, Dept Anesthesie Reanimat, Paris, France
[3] Inst Mutualiste Montsouris, Dept Anesthesie Reanimat, 42 Blvd Jourdan, Paris, France
[4] Univ Paris 07, PRESS Sorbonne Cite, Paris, France
[5] CHU La Reunion, Unite Soutien Methodol, St Denis, France
[6] INSERM, CIC 1410, St Pierre, France
关键词
DIAGNOSTIC-TESTS; REGRESSION;
D O I
10.1371/journal.pone.0169772
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background The benefits of cardiac surgery are sometimes difficult to predict and the decision to operate on a given individual is complex. Machine Learning and Decision Curve Analysis (DCA) are recent methods developed to create and evaluate prediction models. Methods and finding We conducted a retrospective cohort study using a prospective collected database from December 2005 to December 2012, from a cardiac surgical center at University Hospital. The different models of prediction of mortality in-hospital after elective cardiac surgery, including EuroSCORE II, a logistic regression model and a machine learning model, were compared by ROC and DCA. Of the 6,520 patients having elective cardiac surgery with cardiopulmonary bypass, 6.3% died. Mean age was 63.4 years old (standard deviation 14.4), and mean EuroSCORE II was 3.7 (4.8) %. The area under ROC curve (IC95%) for the machine learning model (0.795 (0.755-0.834)) was significantly higher than EuroSCORE II or the logistic regression model (respectively, 0.737 (0.691-0.783) and 0.742 (0.698-0.785), p < 0.0001). Decision Curve Analysis showed that the machine learning model, in this monocentric study, has a greater benefit whatever the probability threshold. Conclusions According to ROC and DCA, machine learning model is more accurate in predicting mortality after elective cardiac surgery than EuroSCORE II. These results confirm the use of machine learning methods in the field of medical prediction.
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页数:12
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