Nomogram Models to Predict Postoperative Hyperlactatemia in Patients Undergoing Elective Cardiac Surgery

Dashuai Wang; Su Wang; Jia Wu; Sheng Le; Fei Xie; Ximei Li; Hongfei Wang; Xiaofan Huang; Xinling Du; Anchen Zhang

doi:10.3389/fmed.2021.763931

Nomogram Models to Predict Postoperative Hyperlactatemia in Patients Undergoing Elective Cardiac Surgery

Front Med (Lausanne). 2021 Dec 2:8:763931. doi: 10.3389/fmed.2021.763931. eCollection 2021.

Authors

Dashuai Wang¹, Su Wang², Jia Wu³, Sheng Le¹, Fei Xie⁴, Ximei Li⁵, Hongfei Wang¹, Xiaofan Huang¹, Xinling Du¹, Anchen Zhang⁶

Affiliations

¹ Department of Cardiovascular Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
² Department of Emergency Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
³ Key Laboratory for Molecular Diagnosis of Hubei Province, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
⁴ Department of Cardiovascular Surgery, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
⁵ Department of Nursing, Huaihe Hospital of Henan University, Kaifeng, China.
⁶ Department of Cardiology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Abstract

Objectives: Postoperative hyperlactatemia (POHL) is common in patients undergoing cardiac surgery and is associated with poor outcomes. The purpose of this study was to develop and validate two predictive models for POHL in patients undergoing elective cardiac surgery (ECS). Methods: We conducted a multicenter retrospective study enrolling 13,454 adult patients who underwent ECS. All patients involved in the analysis were randomly assigned to a training set and a validation set. Univariate and multivariate analyses were performed to identify risk factors for POHL in the training cohort. Based on these independent predictors, the nomograms were constructed to predict the probability of POHL and were validated in the validation cohort. Results: A total of 1,430 patients (10.6%) developed POHL after ECS. Age, preoperative left ventricular ejection fraction, renal insufficiency, cardiac surgery history, intraoperative red blood cell transfusion, and cardiopulmonary bypass time were independent predictors and were used to construct a full nomogram. The second nomogram was constructed comprising only the preoperative factors. Both models showed good predictive ability, calibration, and clinical utility. According to the predicted probabilities, four risk groups were defined as very low risk (<0.05), low risk (0.05-0.1), medium risk (0.1-0.3), and high risk groups (>0.3), corresponding to scores of ≤ 180 points, 181-202 points, 203-239 points, and >239 points on the full nomogram, respectively. Conclusions: We developed and validated two nomogram models to predict POHL in patients undergoing ECS. The nomograms may have clinical utility in risk estimation, risk stratification, and targeted interventions.

Keywords: cardiac surgery; nomogram; postoperative hyperlactatemia; prediction model; risk factor.