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Original Article
Utility of INSCYD athletic performance software to determine
Maximal Lactate Steady State and Maximal Oxygen Uptake in
cyclists
Tim Podlogar 1,2,3, Simon Cirnski 3, Špela Bokal 2,3 and Tina Kogoj 2
1 School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom
2 Faculty of Health Sciences, University of Primorska, Izola, Slovenia
3 Human Performance Centre, Ljubljana, Slovenia
Abstract: Serious amateur and elite athletes regularly take part in structured physiological
testing sessions so that their progress gets tracked and training loads in the training plan
correctly prescribed. Commonly, athletes are tested for the maximal oxygen uptake (VO2max)
and maximal lactate steady state intensity (MLSS). While for the former expensive laboratory
equipment is required, the latter requires multiple exercise trials for accurate determination.
INSCYD athletic performance software is designed to enable continuous monitoring of these
two parameters throughout the season after undertaking a single visit exercise testing session
involving blood lactate sampling and power output measurement. The purpose of the present
study was to assess validity of the software’s estimates of VO2max and MLSS and compare them
to gold standard laboratory measures. 11 trained participants (VO2max 61.0 ± 7.9 mL ∙ kg-1 ∙ min-
1) took part in this study consisting of formal graded VO2max test, multiple MLSS trials and a
recommended test to obtain the data later fed the INSCYD athletic performance software. Both
relative VO2max (∆=0.13 ml.kg-1.min-1, p=0.885) and MLSS calculated values (∆=2 W, p=0.655)
were within expected daily variation and thus the estimations considered valid. It can be
concluded that INSCYD athletic performance software offers its users utility to accurately
predict VO2max and MLSS provided that the practitioner has a good idea of where the MLSS
lies.
Keywords: endurance, testing, performance, VO2max, maximal lactate steady state
• Correspondence: TP; tim@tpodlogar.com.
Received: 15 February 2022; Accepted: 21 April 2022; Published: 30 Juny 2022
Utility of INSCYD athletic performance software to determine Maximal Lactate Steady State and Maximal Oxygen Uptake in cyclists
Citation: Journal of Science and Cycling 2022, 11:1 – https://doi.org/10.28985/1322.jsc.06
Page 31
1. Introduction
Physiological testing has numerous benefits
when trying to optimise performance. The
information gained can be used to better
prescribe training intensity, track
longitudinal changes in performance and
determine an athlete’s strengths and
weaknesses (Jamnick, Pettitt, Granata, Pyne,
& Bishop, 2020; Leo, Spragg, Podlogar,
Lawley, & Mujika, 2021). However, a
complete physiological assessment can be
time consuming, and it usually requires
expensive laboratory equipment (e.g., a
metabolic cart). As a result, there have been
numerous attempts to create testing
protocols that would not require expensive
laboratory grade equipment; and which
could be undertaken in either a laboratory or
field setting in a time efficient manner. One
such testing battery that has gained
popularity among cyclists and is believed to
be used by some of the worlds’ best cycling
teams, is INSCYD athletic performance
software (INSCYD GmbH, Oberfelben,
Switzerland). The protocol requires access to
a power meter and a lactate analyser and
lasts approximately 3 hours. The protocol
professes to be able to provide ‘performance
diagnostics to create a granular analysis of
the physiology of an athlete’ (“INSCYD,”
2021). However, before any testing battery is
endorsed for being utilised, it should be
validated against gold standard testing
procedures and proven to be sufficiently
reliable (Halperin, Vigotsky, Foster, & Pyne,
2018).
INSCYD athletic performance software
provides its users with numerous metrics;
these include maximal oxygen uptake
(VO2max) maximal lactate steady state
(MLSS) and the intensity eliciting maximal
fat oxidation (FatMax). Whereas gold
standard measures are available for the two
former measures (Beneke, 2003; Lundby et
al., 2017), unfortunately a validation of the
latter is difficult to perform due to the large
day-to-day variability of the measure itself
(Achten, Gleeson, & Jeukendrup, 2002;
Chrzanowski-Smith et al., 2020).
The INSCYD athletic performance software
also provides some metrics which on their
own lack scientific validity and could
therefore not be validated as part of a
validation study of the software itself. These
include the maximum glycolytic power
(VLamax) and maximum carbohydrate
metabolism (CarbMax). VLamax is thought
to represent maximal lactate production rate
and is usually determined by assessing blood
lactate responses after a 15-second maximal
sprint (Thomas Hauser, Adam, & Schulz,
2014; Mader & Heck, 1986). While an
attractive metric, VLamax is, to our
knowledge, impossible to assess in vivo for
various reasons. Firstly, lactate could be used
within a muscle cell that produced it and
hence part of the lactate produced would
never appear the bloodstream (Brooks, 2018).
Secondly, blood and muscle lactate
concentrations differ (Tesch, Daniels, &
Sharp, 1982). Thirdly, blood lactate
concentrations merely represent the
relationship between blood lactate removal
and appearance, a concept also known as
lactate shuttle theory (Brooks, 2018).
CarbMax intensity is thought to represent an
intensity at which carbohydrate utilisation
rates exceeds the possible rate of oxidation of
exogenous carbohydrates. Again, as there are
numerous factors affecting maximal
exogenous carbohydrate oxidation rates
(Rowlands et al., 2015) it is unfortunately
impossible to validate this concept.
The aim of the present study was to assess
how valid are the estimates of VO2max and
MLSS (i.e., the metrics that can be validated)
produced by the INSCYD athletic
performance software when crudely
estimating the MLSS intensity (e.g., from a
ramp test) by comparing these values to
those obtained using gold standard
measures.
2. Materials and Methods
Participants
Eleven healthy, endurance-trained males
(age 35 ± 7 years, height 176 ± 4 cm, VO2max
61.0 ± 7.9 mL ∙ kg-1 ∙ min-1 (4.41 ± 0.46 L ∙ min-
Utility of INSCYD athletic performance software to determine Maximal Lactate Steady State and Maximal Oxygen Uptake in cyclists
Citation: Journal of Science and Cycling 2022, 11:1 – https://doi.org/10.28985/1322.jsc.06
Page 32
1, MLSS 268 ± 35 W (3.7 ± 0.6 W ∙ kg-1), body
mass 73.0 ± 10.5 kg and body fat 13 ± 3 %)
provided written informed consent and
completed the study that was approved by
the Committee of Republic of Slovenia for
Medical Ethics (0120-3/2021/3) and
conducted in accordance with the
Declaration of Helsinki. The main inclusion
criteria for enrolment in the study was
regular endurance training (i.e., at least 3
times a week), being accustomed to indoor
training on a stationary bicycle and having
VO2max higher than 50 ml.kg-1.min-1. Only
male athletes were recruited to avoid
menstrual cycle affecting the results due to
multiple laboratory visits.
Experimental design
The study consisted of 3-8 laboratory visits.
On the first occasion, the participants were
tested for VO2max and the exercise intensity
corresponding to the respiratory
compensation point (RCP). These metrics
were determined in line with a previously
described protocol (Iannetta, Inglis,
Pogliaghi, Murias, & Keir, 2020). The power
output corresponding to RCP was
subsequently employed when setting the
initial exercise intensities to determine
maximal lactate steady state intensity (MLSS)
and during an INSCYD test. As INSCYD
athletic performance software is meant to be
primarily used to continuously track athletes
throughout the season, a training history and
thus a crude estimate of MLSS known – hence
RCP was used as a starting point. All other
laboratory visits were conducted in a
randomised order and were separated by 2-4
days. Participants visited the laboratory on
each occasion at the same time of day (± 2
hrs). During all testing participants used
their own bicycles mounted onto an
electrically braked cycle ergometer (Kickr V5,
Wahoo, Atlanta, Georgia, USA). Blood lactate
concentrations were measured throughout
from the earlobe via a handheld blood lactate
monitor (Lactate Plus, Nova Biomedical,
USA) that has been previously validated
(Hart, Drevets, Alford, Salacinski, & Hunt,
2013).
Formal VO2max testing
The formal VO2max test consisted of a
graded intensity cycling protocol that aimed
to elicit maximal oxygen uptake in 8-12
minutes; as per recommendations for such a
test (Iannetta et al., 2020; Jamnick, Botella,
Pyne, & Bishop, 2018; Yoon, Kravitz, &
Robergs, 2007). The testing protocol also
allowed the determination of RCP.
The graded intensity protocol commenced
with a 2-min warm-up at 60W followed by 6-
min of cycling at 120W (i.e., moderate
intensity exercise domain). This was
proceeded by a ramp incremental protocol
increasing the exercise intensity by 30 W ∙
min-1 until task failure. A plateau in VO2 was
confirmed in all participants. Breath by
breath gas exchange measurements were
performed using an automated online gas
analysis system (MetaLyzer 3B-R3, Cortex,
Lepizig, Germany. VO2max was considered
to represent the highest 30-s average of O2
uptake. 30-minutes following the task failure
during the first part of the test, the second
part commenced, and it involved cycling for
2-min at 120W followed by 10-min of cycling
~55-65% of maximal intensity achieved
during the first part of the test (i.e., heavy
intensity exercise domain). RCP (i.e.,
boundary between heavy and severe exercise
intensity domain) was determined as
previously described (Iannetta et al., 2020). In
brief, ramp test respiratory data was
analysed by two experienced researchers that
independently determined oxygen uptake
associated with RCP (VO2 at which end-tidal
PCO2 began to fall after a period of
isocapnia). Subsequently a spreadsheet
supplementing the original article describing
the protocol
(http://links.lww.com/MSS/B957) was used
to determine exercise intensities relating to
RCP.
Prior to each trial gas analysers were
calibrated with a known gas mixture (15.10%
O2, 5.06% CO2; Linde Gas, Prague, Czech
Republic) and the volume transducer was
calibrated with a 3-litre calibration syringe
(Cortex, Leipzig, Germany). During this and
Utility of INSCYD athletic performance software to determine Maximal Lactate Steady State and Maximal Oxygen Uptake in cyclists
Citation: Journal of Science and Cycling 2022, 11:1 – https://doi.org/10.28985/1322.jsc.06
Page 33
all the subsequent tests, laboratory
conditions were comparable at 20 ± 3 °C and
30 ± 5 % relative humidity and two fans were
pointing towards the participants (Vacmaster
Air Mover, Cleva, Newcastle upon Tyne, UK)
to improve air circulation.
Maximal Lactate Steady State Testing
MLSS intensity was determined using
multiple constant-workload tests as per prior
recommendations (Beneke, 2003). The test
started with a 5 min long warm at 100-150W
(individually determined based on the RCP)
followed by 30 minutes of cycling at the
intensity corresponding to the RCP intensity
determined during the first laboratory visit.
Blood lactate was determined at 10th and 30th
minute and the MLSS was accepted if the
difference between both values was not
higher than 1 mmol.L-1. Had this occurred,
the next MLSS testing trial was conducted at
a 5 W higher intensity and the trials were
repeated until the blood lactate concentration
rose by more than 1 mmol.L-1 from 10th to the
30th minute. Conversely, if the first trial
elicited a higher blood lactate change than 1
mmol.L-1, the exercise intensity on the
subsequent trial was reduced by 5 W. Thus,
MLSS intensity was accurately determined to
a value of ±2.5W. Up-to 5 trials per
participant were required to establish a MLSS
in all 11 participants.
INSCYD test
The INSCYD test followed the requirements
obtained from the INSCYD athletic
performance software developer (INSCYD
GmbH, Switzerland; personal
communication). Upon arrival at the
laboratory, body composition of the
participants was estimated using the
bioelectrical impedance methodology (Tanita
BC-601, Tanita Europe BV, The Netherlands).
Then, an exercise bout was started. After an
initial warm up there were 6 intervals
performed at various intensities for various
durations. The first interval lasted 2 minutes
and was performed at the intensity
corresponding to RCP. Upon its completion,
blood lactate concentration was determined
and had the concentration been higher than 4
mmol.L-1, the intensity of the subsequent
interval was reduced and increased if the
concentration was below 2 mmol.L-1.
Modification of the intensity was based on
the subjective assessment made by the
experienced physiologist. The next interval
was 8 minutes long and was performed at the
intensity agreed by the researcher after
conducting the initial 2-minute-long interval
and was followed by 8 minutes and 4
minutes at 110% of this intensity. Lastly, 2-
min all-out and 3-min all out efforts were
carried out. Intervals at the constant load
were interspersed with at least 12 minutes
(ended up being approximately 15 minutes)
of easy cycling (i.e., 50-120W) and the next
interval was initiated once blood lactate
concentration dropped to <2 mmol.L-1,
whereas during both all-out intervals
participants rested and/or cycled at a very
low intensity until blood lactate dropped to
<2 mmol.L-1or 60 minutes had passed which
should suffice for complete reconstitution of
anaerobic capacity (W’) (Skiba, Chidnok,
Vanhatalo, & Jones, 2012). During this time
participants were allowed to consume
carbohydrates in the form of gummy figures
(Haribo, Bonn, Germany) in an ad libitum
quantity. At the end of each interval a blood
sample was obtained from the earlobe and
analysed for blood lactate. This procedure
was repeated each minute to obtain the
highest blood lactate concentration as per the
requirement of the INSCYD athletic
performance software until the blood lactate
concentration started to decline. The cycle
ergometer was set into ERG mode during
constant load cycling and to a simulated
incline of 6% when doing all-out efforts and
participants were free to choose the preferred
cadence and gearing ratio (Wahoo App,
Wahoo, US).
Data analysis
Power data was analysed using WKO5
software (TrainingPeaks, LLC; Colorado,
United States). Study participants’
characteristics (i.e., body mass, body height,
age, and body composition) together with
Utility of INSCYD athletic performance software to determine Maximal Lactate Steady State and Maximal Oxygen Uptake in cyclists
Citation: Journal of Science and Cycling 2022, 11:1 – https://doi.org/10.28985/1322.jsc.06
Page 34
power data and blood lactate values were
analysed via the INSCYD athletic
performance software by an independent
person not familiar with values from the
formal MLSS or VO2max tests.
Statistical Analysis
All data are descriptively represented as
mean ± standard deviation (SD), mean
difference (∆) and 95% confidence intervals
(∆95% CI). Normality of all data was assessed
using Shapiro-Wilk test.
Absolute and relative VO2max values as well
as power output at MLSS were compared
between the laboratory and INSCYD athletic
performance software output using paired
samples t-tests. Reliability was assessed
using Pearson product correlation coefficient
(r), coefficient of variation (CV), typical error,
intraclass correlation coefficient (ICC) and
Bland Altman plots with 95% limits of
agreement (LoA). Level of statistical
significance was set at alpha ≤ 0.05 - two
tailed. Statistical analyses and graphical
representation were processed with a
commercially available software package
(Prism 8, Graphpad Software Inc, San Diego,
USA) and Microsoft Excel (Microsoft 365,
Microsoft Corporation, Redmond, USA).
3. Results
Maximal Oxygen Uptake
No significant differences were found
between laboratory and INSCYD athletic
performance software derived VO2max
values for absolute (∆=5.1 ml.min-1, ∆95% CI
= -145.5 to 155.9 ml.min-1, p=0.940) and
relative (∆=0.13 ml.kg-1.min-1, ∆95% CI = -1.91
to 2.18 ml.kg-1.min-1, p=0.885). Reliability
measures for absolute and relative VO2max
are represented in Table 1 and Table 2.
Correlation between laboratory and INSCYD
athletic performance software derived
VO2max was very strong for both absolute
(r=0.945 p<0.001) and relative (r=0.954 p<0.01)
values (Figure 1A and 1B). Bland Altman
plots between laboratory and INSCYD
athletic performance software derived
VO2max are presented in Figure 1C and
Figure 1D.
Table 1. Reliability measures
between absolute VO2max
estimates.
Absolute VO2max
Laboratory
INSCYD
Mean Difference
(ml.min-1)
5.18
95% CI Mean
Difference (ml.min-1)
-155 to 146
CV (%)
11.1
14.6
Typical Error (ml.min-1)
159
95% CI Typical Error
(ml.min-1)
110 to 278
ICC (p ≤ 0,001)
0.945
CV – Coefficient of variation. CI – Confidence
interval. ICC - intraclass correlation coefficient
Table 2. Reliability measures between
relative VO2max estimates.
Relative VO2max
Laboratory
INSCYD
Mean Difference
(ml.kg-1min-1)
-0.08
95% CI Mean
Difference(ml.kg-1min-1)
2.12 to 1.96
CV (%)
13.6
16.5
Typical Error (ml.kg-
1min-1)
2.15
95% CI Typical Error
(ml.kg-1min-1)
1.50 to 3.77
ICC (p ≤ 0,001)
0.954
CV – Coefficient of variation. CI – Confidence
interval. ICC - intraclass correlation
coefficient.
Maximum Lactate Steady State
While the difference between the estimate of
MLSS from the RCP intensity and laboratory
MLSS was not significant (∆= -12 W, ∆95% CI
= -24 to 1 W, p=0.051), it was greatly
improved by INSCYD athletic performance
software (∆=2 W, ∆95% CI = -6 to 9 W,
p=0.655). Reliability measures for the power
output at the MLSS are represented in Table
3.
Utility of INSCYD athletic performance software to determine Maximal Lactate Steady State and Maximal Oxygen Uptake in cyclists
Citation: Journal of Science and Cycling 2022, 11:1 – https://doi.org/10.28985/1322.jsc.06
Page 35
Correlations between power output at the
MLSS derived from laboratory and INSCYD
athletic performance software was very
strong (r=0.95 p<0.001). Correlations and
Bland Altman plots between power output at
the MLSS derived from laboratory and
INSCYD athletic performance software are
presented in Figure 2.
Table 3. Reliability measures between
MLSS estimates
MLSS
Laboratory
INSCYD
Mean Difference (W)
2
95% CI Mean Difference
(W)
-6 to 9
CV (%)
14.4
14.0
Typical Error (W)
8
95% CI Typical Error (W)
6 to 14
ICC (p ≤ 0,001)
0.976
CV – Coefficient of variation. CI – Confidence
interval. ICC - intraclass correlation
coefficient.
4. Discussion
The aim of the present study was to assess the
utility of the INSCYD athletic performance
software to accurately estimate VO2max and
MLSS after having a crude idea of where the
MLSS could be (e.g., RCP intensity) by
comparing the output values with the values
obtained during formal gold-standard
laboratory tests. The data shows that
INSCYD athletic performance software was
able to provide VO2max and MLSS estimates
that were within the typical daily variation of
these estimates when obtained from gold
standard testing protocols and can thus be
considered valid.
VO2max is considered as the gold standard
measure of aerobic fitness (Martin-Rincon &
Calbet, 2020) despite requiring special
equipment for its accurate determination. In
a standard laboratory practice, it is computed
by assessing the volume and fractional
utilisation of oxygen from the expired air in
each time frame. As is the case with most
measures, it is also prone to daily variability.
Early research showed daily variability to be
as high as ±5.6% which is a result of both
biological variability and a measurement
error (Katch, Sady, & Freedson, 1982). A
meta-analysis found that average standard
test-retest measurement error is 2.58 ml.kg-
1.min-1 (Vickers, 2003), while some individual
studies using more up-to-date measurement
equipment report an even smaller daily
variability (Blagrove, Howatson, & Hayes,
2017). The calculated typical error between
VO2max estimates in the present study was
2.15 ml.kg-1.min-1 with an ICC of 0.954 (CI
0.826-0.988). This is within acceptable and
previously reported day-to-day variability
limits (Blagrove et al., 2017). It can therefore
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in VO2max (ml.min-1)
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Figure 1. Correlations (A and B) and Bland Altman
plots (C and D) between laboratory and INSCYD
athletic performance software derived VO2max
values.
Figure 2. Correlations and Bland Altman plots
between laboratory and INSCYD athletic
performance software derived MLSS values
Utility of INSCYD athletic performance software to determine Maximal Lactate Steady State and Maximal Oxygen Uptake in cyclists
Citation: Journal of Science and Cycling 2022, 11:1 – https://doi.org/10.28985/1322.jsc.06
Page 36
be concluded that INSCYD software
provides users with a valid VO2max estimate.
Likewise, the typical error for MLSS
estimates derived by the INSCYD athletic
performance software was 8W, which is
smaller than the 3% typical day to day
variability of MLSS values (T. Hauser,
Bartsch, Baumgärtel, & Schulz, 2013). From
an applied perspective, while the typical
error might seem high, this is still within a
difference between certain estimation
methods for critical power or MLSS
(Iannetta, Ingram, Keir, & Murias, 2022)
which are both thought to represent the
boundary between heavy and severe exercise
intensity domains. Thus, this allows the
authors to conclude that INSCYD athletic
performance software can provide users with
a valid MLSS estimate.
While the data suggests that the INSCYD
athletic performance software provides its
users with valid estimates of both VO2max
and MLSS, there are some important
limitations of the INSCYD athletic
performance software. In addition to those
discussed in the introduction, notably that
some of the measures provided by the
INSCYD software cannot be validated, the
present study also highlighted some
considerations for potential users.
Furthermore, future studies are required to
assess daily variability in the values obtained
by INSCYD athletic performance software.
Firstly, to collect the data required by the
INSCYD athletic performance software to
accurately estimate VO2max and MLSS, one
needs to first estimate the MLSS intensity as
this is used to determine the intensity at
which the intervals within the protocol are
performed. In the present study the RCP
intensity obtained from the initial VO2max
test was used. While this provides the
software an idea of where the MLSS actually
lies, the INSCYD athletic performance
software improved the estimation of MLSS
intensity, which is what the software would
be primarily used in the field as well.
However, one cannot, based on the results of
the present study, say that the INSCYD
athletic performance software has an utility
to accurately predict MLSS without prior
crude estimation of MLSS. However,
provided that this condition is met, INSCYD
athletic performance software can accurately
determine the MLSS intensity. This is useful
especially for continuous tracking of athletes
rather than their initial assessment.
The gold standard protocol for MLSS
determination requires at least two exercise
trials; performed on separate days.
Therefore, its utility in an elite athlete
population may be limited due to the amount
of time out of training and or competition
that would be required. This is arguably
where the INSCYD athletic performance
software has great utility, i.e., is a relatively
time efficient way to estimate both VO2max
and MLSS, at least compared with gold
standard measures. However, in practice,
MLSS is typically estimated from graded
exercise tests during in which lactate is
sampled at the end of stage (Heck et al., 1985;
Jamnick et al., 2018), commonly these
measurements are combined with VO2max
measurement. It should be noted that when
combining both VO2max and MLSS
determination in a single graded exercise test
there is potential for
underestimation/overestimation of either of
the parameters (Jamnick et al., 2018).
However, utilising the INSYCD athletic
performance software is not the only way to
derive MLSS estimates in a time efficient
way, in fact a single session test to estimate
MLSS has been validated (Hering, Hennig,
Riehle, & Stepan, 2018), although this would
still require a separate laboratory visit for the
assessment of VO2max.
A second consideration when performing
data collection test for the INSCYD athletic
performance software is the large number of
lactate samples required (usually 20 or more
per test). This could be both cost prohibitive
and may lead to some discomfort for
participants. A final consideration is that the
INSCYD athletic performance software does
not calculate the boundary between
moderate and heavy intensity exercise
Utility of INSCYD athletic performance software to determine Maximal Lactate Steady State and Maximal Oxygen Uptake in cyclists
Citation: Journal of Science and Cycling 2022, 11:1 – https://doi.org/10.28985/1322.jsc.06
Page 37
domain. This boundary has been shown to
have utility when defining training zones for
the prescription of training intensity
(Jamnick et al., 2020).
5. Practical Applications.
The INSCYD athletic performance software
using the data collection protocol described
within the present study provides valid
VO2max and MLSS estimates and can
therefore be used as a tool for practitioners.
However, as with any testing protocol,
practitioners need to acknowledge the
potential drawbacks; namely, some provided
metrics are unvalidated, the initial intensity
for the intervals within the protocol needs to
be estimated, no estimate of the boundary
between the moderate and heavy exercise
intensity domains is provided, and finally the
large number of lactate samples required
may be cost prohibitive in some
circumstances.
Funding: This research received no external
funding.
Acknowledgments: Authors would like to
thank Sebastian Weber from INSCYD GmbH
for cooperation in blinded data analysis.
Conflicts of Interest: The authors declare no
conflict of interest.
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