Heart Rate and Blood Lactate Responses to Submaximal Treadmill Exercise in the Normally Performing Standardbred Trotter — Age and Sex Variations and Predictability from the Total Red Blood Cell Volume

Abstract

The purposes of this study were to elucidate the influences of age and sex on the heart rate (HR, bpm) and blood lactate (LA, mmol/l) related exercise tolerance parameters V2000 (tread ill velocity at HR 200), VLA4 (velocity at LA 4), W200 (power output at V2000), and WLA4 (power output at VLA4), and to establish reference values for these in normally performing Standardbred trotting race horses. A further aim was to improve the predictability of individual normal values by correlating them with the total red blood cell volume (CV) alone or in combination with the blood lactate response at V200 (LA200). In total 205 horses were included in the study. According to their owners and/or trainers they were all performing satisfactorily (in racing or training) for shortly impending racing. The exercise test was performed on an inclined (3.5 degrees) high speed treadmill and consisted of four sequentially increasing speeds, each of 2 min duration, aiming at a final HR at or exceeding 200 bpm. HR was monitored continuously and recorded in parallel with blood sampling during the last 15 s of each speed. Blood volume determination was done with the Evans blue dye dilution technique immediately after the exercise test to ensure complete emptying of the splenic red cell reservoir. Both age and sex influenced significantly on all parameters. These were also all strongly dependent on the total red cell volume. Consequently, it was concluded that markers for work tolerance based on heart rate and blood lactate responses to submaximal treadmill exercise reliably reflect circulatory and muscle metabolic capacities. Further, individual normal values are predictable from the red cell volume alone with variation coefficients between 5 and 9.1%, or, in combination with LA200, between 4.4 and 62%. Disregarding the regression with CV, predictability of normal values is improved by considering age and sex variations.