Maximal Lactate Steady State Prediction Using Two DMAX Methods in Horses Subjected to Treadmill-Graded Exercise Test.

Overview

• This study investigates two methods (D and D’) for predicting the maximal lactate steady state (MLSS) in horses running on a treadmill, comparing them to directly measured MLSS during graded exercise tests.
• The research aims to determine whether these simpler predictive methods can reliably estimate endurance capacity and training thresholds in horses without the need for prolonged testing.

Introduction and Background

• Maximal Lactate Steady State (MLSS): The highest exercise intensity at which lactate production and clearance are balanced, resulting in steady lactate levels in the blood.
• Importance for Endurance: MLSS is widely used to:
  • Estimate aerobic endurance capacity.
  • Prescribe training intensities for athletes and animals.
  • Assess effects of training interventions.
• Lactate Threshold (LT): An exercise intensity where lactate begins to accumulate in the blood; acts as a proxy for MLSS.
• Predictive Methods: Over 25 techniques exist to estimate MLSS from lactate data, many used in human athletes but less explored in horses.
• This Study’s Focus: Comparison of two DMAX methods—traditional D and a newer calculated D’—in predicting MLSS from lactate-velocity curves obtained during treadmill tests in horses.

Methods

• Subjects: Ten teaching horses participated in the study.
• Exercise Protocol:
  • Submaximal graded exercise test (GXT) performed on a treadmill to create lactate-velocity curves (LVC).
  • Each horse then completed three to five 30-minute continuous running sessions at various speeds to accurately determine MLSS.
• Lactate-Velocity Curve (LVC): Represents blood lactate concentration at different running speeds.
• DMAX Methods Explained:
  • Traditional D Method: Identifies the point on the LVC where the maximal perpendicular distance from a straight line drawn between the start and endpoint of the curve is greatest. This point approximates the lactate threshold.
  • New Calculated D Method (D’): Uses a mathematical approach to find the point maximizing the distance from a curve connecting the start to endpoint of the LVC, potentially improving precision.
• Data Analysis:
  • Speeds corresponding to the traditional D method (V_D), calculated D’ method (V_D’), and the MLSS (V_MLSS) were compared.
  • Bland-Altman plots and ordinary least products (OLP) analyses assessed agreement and biases among these measurements.

Results

• Lactate Concentrations:
  • At V_D (traditional D): 1.50 ± 0.36 mM
  • At V_D’ (calculated D): 2.02 ± 0.66 mM
  • At V_MLSS (actual MLSS): 1.92 ± 0.65 mM
• Speeds:
  • V_D: 5.42 ± 0.57 m/s
  • V_D’: 6.42 ± 0.71 m/s
  • V_MLSS: 6.35 ± 0.66 m/s
• Differences:
  • Mean difference V_D – V_MLSS: -1.01 ± 0.61 m/s (traditional method underestimates speed)
  • Mean difference V_D’ – V_MLSS: -0.93 ± 0.67 m/s (new method also underestimates, but less)
• Bias and Agreement:
  • Neither V_D nor V_D’ showed constant or proportional bias compared to V_MLSS, indicating both predict MLSS speed reliably without systematic errors.
  • The new calculated D method had slightly better agreement with MLSS speeds.

Conclusions and Implications

• Both the traditional D and the new calculated D methods are accurate and reliable for estimating the lactate threshold and MLSS in horses during treadmill exercise.
• The calculated D method may provide a more precise prediction, closer to the directly measured MLSS.
• Utilizing these methods simplifies testing by reducing the need for prolonged continuous exercise sessions to determine MLSS.
• This has practical applications for:
  • Designing training programs for horses based on reliable physiological thresholds.
  • Monitoring conditioning and performance progress with simpler, quicker tests.
• This research helps to translate methods validated in human athletes to equine sports science, supporting evidence-based training and assessment protocols.