Postoperative hyperlactatemia (POHL) is a common metabolic disorder in patients undergoing cardiac surgery and is associated with adverse clinical outcomes, such as severe acute kidney injury, acute respiratory distress syndrome, and mortality (1–3). Given that elevated lactate levels have important implications for poor prognosis, lactate levels could represent a useful goal of initial resuscitation (4). Nonetheless, studies on lactate-directed therapy performed in post-cardiac surgery patients are limited (5). The reported incidence of POHL in different studies varied greatly, from 11.1 to 45.6% (6, 7).

Globally, numerous studies have been conducted to explore predictors for POHL after cardiac surgery due to its high prevalence and poor outcomes (8–10). Some significant risk factors have been reported in the literature, such as non-elective surgery and diabetes mellitus (8, 11). However, the baseline characteristics of the surgical patients have changed substantially these years due to great advances in anesthesia and surgical techniques. Many studies were published decades ago, and some conclusions may have been obsolete because of the very limited samples and narrow patient selection (3, 12). In addition, the majority of the published studies were conducted in patients undergoing mixed surgeries or single valvular heart surgery (13, 14), but none were conducted specifically for patients undergoing elective cardiac surgery (ECS). To our knowledge, a large-scale persuasive study on this topic is still lacking, and the establishment of a convincing prediction model is still an urgent need.

The aim of this study was to identify independent risk factors for the development of POHL in adult patients who underwent ECS and to develop and validate two easy-to-use clinical prediction models that may help clinicians evaluate the risk of POHL and implement appropriate interventions early.

The elevated level of postoperative lactate has been well-recognized to be associated with poor outcomes (1, 10, 14), which was confirmed again by the results of this study. The incidence of POHL after ECS was 10.6%, close to previous reports (6, 7). The overall mortality was 2.3%, similar to previous studies (14). Nonetheless, the mortality was significantly higher in patients with POHL compared with patients without that. Moreover, significantly higher probabilities of other poor clinical outcomes such as readmission to ICU and the length of hospital stay were also observed in those with POHL. However, the optimal management of patients with POHL is little known (17), emphasizing the importance of early management of high risk populations that may develop POHL.

To our knowledge, our study represents the first large-scale study that focuses on the risk factors for POHL after ECS and the establishment of nomogram models globally. In this study, we developed and validated two nomogram models for POHL after ECS using data from 13,454 patients in four institutions. By univariate and multivariate analysis, we identified four preoperative and two intraoperative independent risk factors for POHL. A full nomogram model based on all the six predictors and a preoperative nomogram model based on the four preoperative predictors were then established. Both models indicated good calibration, discrimination, and clinical usefulness. Finally, on the basis of the full nomogram model and clinical practice, we defined four risk intervals to facilitate clinical application.

It is well-known that lactate is produced by pyruvate during glycolysis, and its increase comes from an increase in production and a decrease in clearance. However, the parts that contribute more to the development of hyperlactatemia vary greatly from person to person (15, 18). In this study population, age, renal insufficiency, LVEF, cardiac surgery history, CPB time, and RBC transfusion were identified as independent predictors for POHL. Indeed, these factors were also found to be independently associated with renal impairment and pulmonary dysfunction after cardiac operations (19, 20). Thus, we speculate that POHL may act as an abnormal intermediate product and a causal link between clinical features and outcomes.

The history of previous cardiac surgery was identified as the most significant predictor for POHL after ECS in our analysis. Reentry procedures in redo cardiac surgery are technically demanding and carry elevated operative risk due to anatomical planes loss, injuries to numerous structures, and hemorrhage (21–23). Bianco et al. found that more blood product transfusion was required in reoperative patients, and speculated that transfusion requirements might be related to injuries upon reentry and prolonged operative and CPB time (24). In addition, patients undergoing reoperation often had older age and more comorbidities (24, 25). In this study, age was positively correlated to the peak lactate value. However, the results with regard to the correlation between age and elevated lactate were mixed in the literature, which may be caused by different measurement time points of lactate (10, 11).

Our results showed that the lower the preoperative LVEF, the higher risk of developing POHL, which was consistent with previous studies (8). It is well-known that low LVEF can affect tissue perfusion. Myocardial stunning caused by ischemia-reperfusion states, as a frequent consequence following CPB, may lead to decreased left ventricular function and thus can further aggravate the accumulation of lactate (26). In this study, renal insufficiency was another independent preoperative risk factor. This may be due to the fact that the kidney mostly relies on lactate as the gluconeogenic substrate, and renal insufficiency could affect the systemic clearance of lactate, giving rise to hyperlactatemia (27). In addition, patients undergoing chronic hemodialysis are more likely to be deficient in thiamine due to strict dietary control, which may cause pyruvate to shift to anaerobic metabolism (28).

The preoperative nomogram model comprising four preoperative factors mentioned above was moderately accurate in predicting POHL after ECS. These factors are simple and easily accessible in clinical practice. This nomogram allows patients to intuitively and easily understand their conditions. For clinicians, this may help to evaluate the risk of patients and formulate feasible plans.

Although this study was conducted in patients undergoing ECS, as expected, the independent association between CPB duration and POHL development was still significant, in line with previous studies (3, 10). Evans et al. reported that the duration of CPB longer than 3 h was associated with 5.8-fold increased odds of POHL (13). The stress of cardiac surgery has been demonstrated to cause decreased pyruvate dehydrogenase quantity and activity and depletion of thiamine levels, resulting in hyperlactatemia (29, 30). Regrettably, Luger et al. found that the intravenous thiamine supplementation prior to cardiac surgery failed to significantly reduce postoperative blood lactate concentration (31). In addition, Mustafa et al. indicated that the CPB procedure decreased lactate clearance, which was possibly linked to the liver dysfunction in elective surgery (32). Moreover, microvascular thrombosis was found to be linked to cardiac surgery with CPB, and insufficient oxygen supply in the microcirculation area increased lactate levels (9). Without a doubt, the extension of CPB time will exacerbate this situation.

The loss of clotting factors and platelets induced by CPB leads to coagulation dysfunction, which may relate to an increased risk of bleeding (33). To some extent, more blood transfusion requirements always imply more blood loss during the operation. Moreover, hemodilution as a necessary part of the CPB process may further increase the possibility of demand for blood transfusion. In this study, the volume of RBC transfusion was also identified as an independent risk factor for POHL. It is undeniable that increasing oxygen delivery is the physiologic benefit of blood transfusion, and several studies have shown that RBC transfusion can improve tissue oxygenation and increase functional capillary density in the microcirculation (34, 35). However, increasing evidence suggested that massive transfusion of RBC increased the risk of adverse outcomes in cardiac surgical patients (36–38). Surgenor et al. indicated that RBC transfusion initiated a systemic inflammatory response, leading to local microvascular occlusion and tissue hypoxia (38). They also found that exposure to RBC transfusion during surgery was associated with low-output heart failure, which may have a relationship with hyperlactatemia (38). The results of randomized controlled trials also indicated that restrictive RBC transfusion strategy was safe in both adults and pediatric patients who underwent cardiac surgery, and it had obvious resources and economic advantages (39, 40).

In addition, limiting the effect of hemodilution on renal function was effective in reducing acute kidney injury rates (41). We speculate that it is reasonable to limit hemodilution and thus decrease transfusion requirements, which may reduce lactate levels due to the fact that renal injury may affect lactate metabolism. Of course, correction of preoperative anemia was also a feasible option for patients undergoing elective surgery to reduce intraoperative blood transfusion (42). Minimized CPB has also been reported to have beneficial effects on decreasing transfusion rate (43), which may be due to lower inflammatory response (44). Undeniably, skilled surgical operation with mature teamwork also plays an important part to reduce CPB and surgery time.

The full nomogram model involved four preoperative and two intraoperative predictors, showing a good prediction efficiency and clinical utility, and was well-validated in the independent cohort. Its character as a graphical prediction tool makes clinicians convenient to do a risk assessment and clinical intervention considerations. Moreover, the utilization of our models may help reduce the significant increase of lactate levels after ECS and, thus, may have a positive effect on reducing postoperative adverse outcomes.

Several measures have been reported to have an effect on alleviating POHL, such as minimal volume ventilation in robotically assisted cardiac surgery, continuous ultrafiltration through polyethersulfone membrane during CPB, and modified glucose–insulin–potassium regimen (45–47). There may exist a huge waste of labor and material resources if these measures are applied to all patients without selection, especially to those who are at very low risk. However, implementing these auxiliary interventions in patients who are identified as high risk by our risk models may be more effective and more cost-efficient for clinical application.

There are some limitations in this study that deserve mention. First, this was a retrospective observational study, and POHL was diagnosed on the basis of medical records. Despite having carefully reviewed all the records, we cannot ensure that all patients who developed POHL were included. Second, some possible risk factors for POHL after ECS were not available in this study, such as intraoperative hemodynamic data and the use of positive inotropic drugs. Nevertheless, the nomogram models performed well in discrimination, calibration, and clinical utility. Third, the records of POHL were limited within the first postoperative 12 h, which may underestimate the true incidence. However, this was in line with the main purpose of this study, as previous studies have indicated that early POHL was significantly associated with poorer prognosis.

In this study, we developed and validated two nomogram models to assess the probability of POHL in patients undergoing ECS. The full nomogram model incorporated both preoperative and intraoperative variables, and the preoperative nomogram model used only preoperative variables. Both nomogram models demonstrated good discrimination, calibration, and clinical utility. Based on the full nomogram model, four risk intervals were divided for better clinical practice. Risk assessment and targeted interventions based on the predictive models may be conducive to decreasing the incidence of POHL in patients undergoing ECS.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and approved by the Ethical Committee of the Union Hospital (No. 0521), Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

DW, XH, AZ, and XD conceptualized and supervised the study. DW, JW, SL, FX, XL, AZ, and HW collected the clinical data. DW, SW, JW, SL, FX, XL, HW, and XH summarized all the data. DW, SW, JW, and SL drafted the manuscript. DW, SW, XH, AZ, and XD revised the final manuscript. All authors read and approved the final manuscript.

This study was supported by the National Natural Science Foundation of China (Grant nos. 81800413 and 81801586).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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