Finds the maximal lactate steady state (MLSS) from two or more constant-load bouts of at least 30 min on separate
days: a bout is steady when blood lactate rises by no more than 1.0 mmol/L from minute 10 to minute 30, and the MLSS
is the highest steady bout. Heck et al. (1985), who introduced the test and the term, allowed a rise of 1 mmol/L over
the last 20 min of 3 + 25-min runs; the minute 10 to 30 window is that of Beneke (2003). Against
the highest steady oxygen uptake, a window from minute 15 or 20 to minute 30 was more accurate
(Iannetta et al., 2022); set it with from. With the result of lactate_threshold() for a step test of the same
athlete, it also gives how far each threshold lies from the MLSS, your own check of which threshold estimates it.
Usage
lactate_mlss(bouts, x = NULL, rise = 1, from = 10)
# S3 method for class 'lactate_mlss'
autoplot(object, ...)Arguments
- bouts
A data frame with one row per sample:
intensity(the load of the bout, in the unit of the step test),time(minutes from the start of the bout) andlactate(mmol/L).- x
The result of
lactate_threshold()for a step test of the same athlete, orNULL.- rise
The largest rise in lactate (mmol/L) from minute
fromto minute 30 of a steady bout. Defaults to1.- from
The minute the rise is measured from, to minute 30. Defaults to
10(Beneke, 2003). In 10 men cycling, the MLSS from minute 10 lay 8 W below the highest steady oxygen uptake on average, and from minute15or202 W above it, where oxygen uptake was steady in 7 of the 10 rather than 9 (Iannetta et al., 2022).- object
The result of
lactate_mlss().- ...
Not used.
Value
a lactate_mlss list with mlss (the highest steady bout, NA when none was steady), next_bout (the
lowest bout above it, which was not steady, or NA), bouts (a tibble with one row per bout: intensity,
lactate_from (at minute from), lactate_30, rise, minutes (the last sample), and steady), the samples,
rise and from, and, with x,
thresholds (a tibble with method, intensity, and the gap to the MLSS in intensity units and in %, positive
when the threshold lies above it). Plot it with autoplot(); the article Beyond the step test shows it.
Details
The lactate at minute from and at minute 30 is interpolated linearly between the samples, so sample at or around
both. A bout
that ended before minute 30 (exhaustion) is not steady. The true MLSS lies between the highest steady bout and the
next bout up, so bouts closer together pin it down better. Thresholds against a measured MLSS land from about 40 W
below to 40 W above it on average, depending on the method and the protocol (Hauser et al., 2014; Ploszczyca et al.,
2020). Whether the MLSS or the critical power marks the boundary between the heavy and severe domains is debated
(Keir et al., 2015; Mattioni Maturana et al., 2016; Jones et al., 2019).
References
Beneke R. Methodological aspects of maximal lactate steady state - implications for performance testing. European Journal of Applied Physiology. 2003;89(1):95-99. doi:10.1007/s00421-002-0783-1
Hauser T, Adam J, Schulz H. Comparison of selected lactate threshold parameters with maximal lactate steady state in cycling. International Journal of Sports Medicine. 2014;35(6):517-521.
Heck H, Mader A, Hess G, Mücke S, Müller R, Hollmann W. Justification of the 4-mmol/l lactate threshold. International Journal of Sports Medicine. 1985;6(3):117-130. doi:10.1055/s-2008-1025824
Iannetta D, Ingram CP, Keir DA, Murias JM. Methodological reconciliation of CP and MLSS and their agreement with the maximal metabolic steady state. Medicine & Science in Sports & Exercise. 2022;54(4):622-632. doi:10.1249/MSS.0000000000002831
Jones AM, Burnley M, Black MI, Poole DC, Vanhatalo A. The maximal metabolic steady state: redefining the 'gold standard'. Physiological Reports. 2019;7(10):e14098.
Keir DA, Fontana FY, Robertson TC, Murias JM, Paterson DH, Kowalchuk JM, Pogliaghi S. Exercise intensity thresholds: identifying the boundaries of sustainable performance. Medicine & Science in Sports & Exercise. 2015;47(9):1932-1940. doi:10.1249/MSS.0000000000000613
Mattioni Maturana F, Keir DA, McLay KM, Murias JM. Can measures of critical power precisely estimate the maximal metabolic steady-state? Applied Physiology, Nutrition, and Metabolism. 2016;41(11):1197-1203. doi:10.1139/apnm-2016-0248
Ploszczyca K, Jazic D, Piotrowicz Z, Chalimoniuk M, Langfort J, Czuba M. Comparison of maximal lactate steady state with anaerobic threshold determined by various methods based on graded exercise test with 3-minute stages in elite cyclists. BMC Sports Science, Medicine and Rehabilitation. 2020;12:70.
Examples
bouts <- data.frame(
intensity = rep(c(130, 140, 150), each = 4),
time = rep(c(5, 10, 20, 30), 3),
lactate = c(2.4, 2.6, 2.7, 2.8, 3.1, 3.4, 3.8, 4.1, 3.9, 4.5, 5.4, 6.3)
)
results <- lactate_threshold(demo_data, intensity, lactate, plot = FALSE)
mlss <- lactate_mlss(bouts, results)
mlss
#> 3 constant-load bouts, steady when lactate rose by 1 mmol/L or less from minute 10 to 30.
#> MLSS at 140 W: the next bout (150 W) was not steady.
#> Closest thresholds: ModDmax (+0 W), OBLA 3.5 (-1 W), Exp-Dmax (-5 W).
mlss$thresholds
#> # A tibble: 18 × 4
#> method intensity gap gap_percent
#> <chr> <dbl> <dbl> <dbl>
#> 1 Log-log 101 -39 -28.1
#> 2 OBLA 2.0 106 -34 -24.5
#> 3 OBLA 2.5 119 -21 -14.8
#> 4 OBLA 3.0 130 -10 -7.2
#> 5 OBLA 3.5 139 -1 -1
#> 6 OBLA 4.0 146 6 4.4
#> 7 Bsln + 0.5 83 -57 -41
#> 8 Bsln + 1.0 103 -37 -26.1
#> 9 Bsln + 1.5 118 -22 -16
#> 10 Dmax 132 -8 -5.9
#> 11 ModDmax 140 0 0.1
#> 12 Exp-Dmax 135 -5 -3.7
#> 13 Log-Poly-ModDmax 149 9 6.7
#> 14 Log-Exp-ModDmax 152 12 8.2
#> 15 LTP1 111 -29 -20.7
#> 16 LTP2 160 20 14
#> 17 LTratio 77 -63 -44.8
#> 18 IAT 125 -15 -10.9
## the plot is short and wide: see it in the article Beyond the step test
if(interactive()) autoplot(mlss)