Reflective Biomarker or Independent Risk Predictor? Assessing Lactate Clearance in Postoperative Cardiac Surgery Outcomes

A. A. Rizaldi¹, A. Feng¹, Z. Darby², S. Khanduja², A. Leng¹, D. Alejo³, J. Gammie⁴, G. JR. Whitman², H. Wang^2
1Johns Hopkins University School of Medicine, Baltimore, Maryland ²Division of Cardiac Surgery, Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland ³Division of Cardiac Surgery, Department of Surgery, Johns Hopkins University School of Medicine, Fallston, Maryland ⁴Division of Cardiac Surgery, Department of Surgery, Johns Hopkins University School of Medicine, Stevenson, Maryland

Purpose: Hyperlactatemia is associated with worse mortality and morbidity after cardiac surgery, driving clinical decision-making. This study aimed to evaluate whether lactate clearance trend is associated with outcomes in postoperative cardiac surgery patients, and whether it provides incremental value in the prediction of mortality and morbidity.

Methods: A retrospective analysis was conducted on adult (≥18 years) patients undergoing cardiac operations at a single institution from July 1, 2016 to December 31, 2021. The trend of postoperative lactate levels and the time to lactate clearance (first lactate measurement ≤ 3 mmol/L) were analyzed. The primary outcome was operative mortality, and secondary outcomes included postoperative renal failure, stroke, prolonged ventilation, reoperation, and deep sternal wound infection rate. A multivariable logistic regression model was used to assess the association between time to lactate clearance and the primary and secondary outcomes. Receiver operating characteristic (ROC) curve analysis was used to examine the discriminative capability of the clinical model using: 1) STS predicted risk of mortality (PROM) only, 2) STS PROM + time to lactate clearance, 3) STS PROM + vasoactive inotropic score (VIS), and 4) STS PROM + time to lactate clearance + VIS.

Results: Of 3,848 patients who underwent cardiac operations, the time to lactate clearance was: 0 hours for 39% (1,504), 0 to 6 hours for 15% (577), 6 to 12 hours for 18% (706), 12 to 24 hours for 21% (790), and >24 hours or never ≤3 mmol/L for 7.3% (271). The median number of postoperative lactate measurements was 6 (IQR 4-9), and median time to the last measurement was 18 hours (IQR 13-45.3 hours). Increased time to lactate clearance was associated with higher body mass index, longer bypass and cross-clamp times, more units of intra-operative transfusion, more urgent/emergent status, and higher STS PROM (all p< 0.05). Differences in the pattern of lactate clearance, after accounting for time to clearance, were not associated with primary or secondary outcomes (p>0.05). Patients with delayed lactate clearance (>24 hours or never ≤3 mmol/L) experienced higher rates of operative mortality and morbidity (p < 0.001, Figure). Lactate levels were positively correlated with VIS at 6 hours post-op (R=0.44, p< 0.001). The predictive power of models for operative mortality or morbidity with STS PROM-only, STS PROM + time to lactate clearance, STS PROM + VIS, and STS PROM + time to lactate clearance + VIS were not significantly different (p>0.05, Table).

Conclusion: Delayed lactate clearance is associated with increased operative mortality and morbidity; however, its inclusion does not significantly enhance predictive models beyond the STS PROM alone. These findings suggest that while lactate clearance time reflects underlying patient and operative risk, it does not provide incremental value as an independent predictive biomarker in clinical decision-making for postoperative cardiac surgery patients. Clinicians should not rely solely on lactate clearance for predicting clinical outcomes. Integrating lactate measurements with other clinical indicators will provide a more comprehensive assessment for better-informed decision-making.

Identify the source of the funding for this research project: Institutional Funding (Johns Hopkins Cardiac Surgery)