Traditional approaches to estimating a lactate threshold during a progressive exercise test have utilized visual inspection of the data. We describe a computerized approach which utilizes a log-log transformation to yield two approximately linear segments. Linear regression lines are fit to these segments and the intersection of the two lines yields an estimate of the lactate threshold. An approximate 95% confidence interval is also generated. o 1986 Academic Press. Inc.
Changes in blood lactate concentration during a progressive exercise test to exhaustion have suggested the possibility of a threshold-a point where blood lactate increases dramatically.
Attempts to estimate a lactate threshold (LT) have utilized simple visual inspection of lactate data plotted against time or 02 consumption. This subjective approach has led to LT estimates that are dependent on the particular observer (6, 20) and has contributed in part to the controversy as to whether LT exists at all (3). Clearly a more objective approach is needed.
Recently, Beaver et al. ( 2) have suggested that a log-log transformation on the data enhanced the appearance of LT. They described a method of estimating LT that utilized an observer to determine a division point such that the data to the left of this point belonged to a low slope linear segment and data to the right belonged to a high slope linear segment. Linear regression lines were determined for each of these two segments, with the intersection of the two lines being the estimate of the LT. Although this approach is less subjective than simple visual inspection of the raw data, LT estimate is directly influenced by the choice of the division point.
The purpose of this paper is to describe a computerized approach for estimation of LT using the log-log transformation proposed by Beaver et al. ( 2). This computer method does not use an observer and is thus compktely objective.