Development and Internal Validation of Predictive Formula for Arterial Lactate Using Peripheral Venous Sampling in Early Septic Shock

Background: Lactate is a key biomarker for diagnosis, risk stratification, and therapeutic monitoring in septic shock. Arterial sampling is the gold standard, but it is invasive, painful, and not always feasible, especially in early resuscitation. Peripheral venous sampling is less invasive and more widely accessible. This study aimed to develop and internally validate a predictive equation to estimate arterial lactate from peripheral venous lactate in patients with septic shock. Methods: A prospective observational study was conducted in the intensive care unit of a tertiary hospital from April 2023 to April 2025. Adult patients meeting Sepsis-3 criteria for septic shock within the first 6 hours of resuscitation were enrolled. Arterial, central venous, and peripheral venous lactate were measured simultaneously or within 15 minutes. Predictive modeling was performed using multivariable regression with backward elimination. Model performance was assessed using R², mean absolute error (MAE), root mean square error (RMSE), and correlation coefficient (r). Results: Among 120 patients included, the median (IQR) arterial, central venous, and peripheral venous lactate were 2.3 (1.3–4.3), 2.7 (1.7–4.5), and 3.7 (2.1–5.9) mmol/L, respectively. The final model was: arterial lactate = 0.7414 × (peripheral venous lactate) – 0.1315 . Internal validation demonstrated strong predictive accuracy (R² = 0.8514, MAE = 0.8899, RMSE = 1.2314). The correlation coefficient showed strong agreement between arterial and central venous lactate (r = 0.97) and arterial and peripheral venous lactate (r = 0.91), across both low and high lactate ranges. Conclusions: A simple predictive equation using only peripheral venous lactate provides reliable estimation of arterial lactate in early septic shock. This approach is clinically feasible, less invasive, and may support timely decision-making in critical care, particularly in emergency departments and resource-limited settings.