Maximal Lactate Steady State Prediction Using Two DMAX Methods in Horses Subjected to Treadmill‐Graded Exercise Test - de Oliveira Littiere, Thayssa [UNESP]; da Costa, Guilherme Barbosa [UNESP]; de Sales, Nathali Adrielli Agassi [UNESP]; de Carvalho, Júlia Ribeiro Garcia [UNESP]; Rodriguez, Ivan Dario Martinez [UNESP]; Ramos, Gabriel Vieira [UNESP]; de Lacerda‐Neto, José Correa [UNESP]; Ferraz, Guilherme Camargo [UNESP] (Wiley, 2025)
Maximal lactate steady state (MLSS) and its predictive thresholds, including the lactate threshold (LT), are widely used to estimate endurance capacity, prescribe training, and assess the effects of training. The human literature identified approximately twenty-five methods to predict the MLSS. This communication compares the concordance between the two DMAX methods and the MLSS. Under laboratory conditions, ten teaching horses underwent a submaximal graded exercise test (GXT) on a treadmill to obtain their lactate-velocity curves (LVC). They performed three to five 30-min continuous running sessions to determine the MLSS. The traditional DMAX method was determined using the maximal distance from LVC to the line formed by its endpoints. A new calculated DMAX method (DMAXC) involved mathematically determining the point that results in the maximum distance from a curve connecting the start to the endpoint of the LVC. The agreement among the velocities corresponding to the DMAX (VMAX), DMAXC (VMAXC), and the MLSS (VMLSS) was established using a Bland-Altman plot and ordinary least products (OLP) analysis. The average lactatemia at VMLSS, VMAX, and VMAXC was 1.50 ± 0.36 mM, 2.02 ± 0.66 mM, and 1.92 ± 0.65 mM, with respective speeds of 5.42 ± 0.57 m/s, 6.42 ± 0.71 m/s, and 6.35 ± 0.66 m/s. The mean difference between VMAX-VMLSS and VMAXC-VMLSS was -1.01 ± 0.61 and -0.93 ± 0.67 m/s, respectively. VMAX and VMAXC did not show constant and proportional biases compared to VMLSS. In the GXT protocol used in this current study, DMAX approaches appear to be accurate and reliable methods for lactate threshold determination and estimating MLSS in teaching horses.