Measurement of central venous pressure and pulse pressure variations in off-pump CABG surgeries and its correlation with lactate levels - an observational study

Background: Hemodynamic instability in patients undergoing off-pump coronary artery bypass grafting (OPCABG) may predispose them to inadequate perfusion and poor outcomes. Central venous pressure (CVP), pulse pressure variation (PPV), and lactate are all valuable hemodynamic parameters, but the predictive nature of each of these parameters remains unclear.

Aim: To assess the relationship between intraoperative hemodynamic parameters and serial lactate levels; and the association with postoperative outcomes.

Methods: This prospective observational study was conducted in 88 patients undergoing elective OPCABG at SRM Medical College Hospital, India. Intraoperative cardiovascular parameters CVP, PPV, mean arterial pressure (MAP), vasoactive-inotropic score (VIS) and serial lactate levels were recorded. Postoperative outcomes included duration of ventilator support, duration of ICU stay, morbidity and mortality. Correlations were calculated using multiple linear regression analysis, with a significance level set at p < 0.001 to account for multiple comparisons.

Results: Lactate increased from 0.93 ± 0.38 mmol/L at baseline to 3.09 ± 0.65 mmol/L at 5 hours. Multiple linear regression analysis revealed that PPV (β = 0.046, p < 0.001) and VIS (β = 0.069, p < 0.001) were significant but weak independent predictors of lactate levels. CVP (β = 0.003, p = 0.098) and MAP (β = -0.0001, p = 0.889) demonstrated no clinically relevant correlation. Mean ventilation time was 12.4 ± 4.9 hours. Morbidity occurred in four patients with no mortality reported. Data regarding ICU stay was incomplete and could not be analyzed.

Conclusion: PPV and VIS correlated weakly but significantly with lactate, whereas CVP, MAP, and blood loss were not clinically meaningful predictors. While dynamic monitoring may contribute additional information during OPCABG surgery, the very small effect sizes indicate these variables are not strong standalone predictors in this context. Larger cohorts are needed to identify more robust associations.