Establishment of Nomogram model for individualized prediction of the risk of severe hyperlactatemia after cardiopulmonary bypass heart surgery

Yang Jie; Lu Zhen; Sun Haoliang; Guan Yuzhen

doi:10.3969/j.issn.1002-1949.2023.12.008

Abstract：Objective To establish a Nomogram model for personalized prediction of the risk of severe hyperlactatemia after cardiopulmonary bypass heart surgery.Methods Patients who underwent cardiopulmonary bypass cardiac surgery in Jiangsu Provincial People's Hospital from January 2020 to December 2022 were selected as the training set,and patients from January 2023 to June 2023 were selected as the validation set according to the same criteria.Clinical data of the patients in the training set were collected,and they were divided into a severe hyperlactatemia group and a non-severe hyperlactatemia group based on the occurrence of severe hyperlactatemia.Univariate and multivariate Logistic regression were used to analyze the risk factors for severe hyperlactatemia after cardiopulmonary bypass heart surgery,and relevant Nomogram prediction models were established.The concordance index(C-index),the calibration curve,the receiver operating characteristic(ROC)curve and decision curve analysis(DCA)were used to evaluate the prediction efficiency of the model.Results Among the 469 patients with cardiopulmonary bypass cardiac surgery enrolled in the training set,61 patients were in the severe hyperlactatemia group and 408 patients were in the non-severe hyperlactatemia group.There was a statistically significant difference in American Society of Anesthesiologists(ASA)grading,New York Heart Association(NYHA)cardiac function grading,cardiopulmonary bypass time,surgery time,acute kidney injury,and ventilator usage time between the two group(P＜0.05).Multivariate Logistic regression analysis showed that ASA grading of Ⅳ-Ⅴ,NYHA cardiac function grading of Ⅲ-Ⅳ,cadiopulmonary bypass time≥120 min,surgery time≥5 h,acute kidney injury,and ventilator usage time≥24 h were independent risk factors for severe hyperlactatemia after cardiopulmonary bypass heart surgery(P＜0.05).The C-index for the training set and the validation set was0.807(95%CI 0.779-0.835)and 0.792(95%CI 0.768-0.816),respectively.The Hosmer-Lemeshoe goodness-of-fit test showed the results of the training set and the validation set were χ2 =6.418,P =0.506 and χ2 =5.767,P =0.457.The AUC of the ROC curve for the training set and the validation set was 0.801(95%CI 0.772-0.831)and0.787(95%CI 0.761-0.813),respectively.Within the predictable range of 1%to 80%of the column chart,the model has a net benefit.Conclusions ASA grading ofⅣ-Ⅴ,NYHA cardiac function grading of Ⅲ-Ⅳ,cardiopulmonary bypass time≥120 min,surgery time≥5 h,acute kidney injury,and ventilator usage time≥24 h are risk factors for severe hyperlactatemia after cardiopulmonary bypass heart surgery.The Nomogram model constructed based on the above factors has certain predictive value for the occurrence of severe hyperlactatemia after cardiopulmonary bypass heart surgery.