![| Average [THb], [HHb] and TSI during the 5-km time trial at pre-(open symbols), mid-(gray symbols) and post-training (black symbols) in IPC and PLA. Data were as follows: (A) Average [THb] for TT at pre-(IPC: 16.9 ± 2.9 µM; PLA: 15.5 ± 1.2 µM), mid-(IPC: 14.4 ± 2.8 µM; PLA: 13.3 ± 1.4 µM), and post-training (IPC: 17.4 ± 2.6 µM; PLA: 12.6 ± 2.1 µM). (B) Average [HHb] for TT at pre-(IPC: 19.9 ± 2.6 µM; PLA: 16.1 ± 2.0 µM), mid-(IPC: 20.6 ± 2.5 µM; PLA: 16.5 ± 2.0 µM), and post-training (IPC: 22.3 ± 2.8 µM; PLA: 16.3 ± 1.9 µM). (C) Average TSI for TT at pre-(IPC: −28.5 ± 3.3%; PLA: −27.5 ± 4.1%), mid-(IPC: −27.2 ± 3.4%; PLA: −31.2 ± 2.0%), and post-training (IPC: −32.4 ± 4.8%; PLA: −37.8 ± 4.3%). Within-group differences between time points are indicated in the square boxes for the first half (1/2), the second half (2/2) and the entire TT (all). ( †) and ( ‡) indicate clear differences between-groups (IPC vs. PLA) at postcompared to pre-and mid-, respectively. Values are mean ± SE.](https://www.researchgate.net/publication/340487620/figure/fig3/AS:885282622681098@1588079233590/Average-THb-HHb-and-TSI-during-the-5-km-time-trial-at-pre-open-symbols_Q320.jpg)
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ORIGINAL RESEARCH
published: 28 April 2020
doi: 10.3389/fspor.2020.00041
Frontiers in Sports and Active Living | www.frontiersin.org 1April 2020 | Volume 2 | Article 41
Edited by:
Olivier Girard,
University of Western
Australia, Australia
Reviewed by:
Danilo Iannetta,
University of Calgary, Canada
Leonardo Coelho Rabello de Lima,
Centro Universitário Herminio Ometto
de Araras, Brazil
*Correspondence:
François Billaut
francois.billaut@kin.ulaval.ca
Specialty section:
This article was submitted to
Elite Sports and Performance
Enhancement,
a section of the journal
Frontiers in Sports and Active Living
Received: 30 January 2020
Accepted: 25 March 2020
Published: 28 April 2020
Citation:
Paradis-Deschênes P, Joanisse DR,
Mauriège P and Billaut F (2020)
Ischemic Preconditioning Enhances
Aerobic Adaptations to Sprint-Interval
Training in Athletes Without Altering
Systemic Hypoxic Signaling and
Immune Function.
Front. Sports Act. Living 2:41.
doi: 10.3389/fspor.2020.00041
Ischemic Preconditioning Enhances
Aerobic Adaptations to
Sprint-Interval Training in Athletes
Without Altering Systemic Hypoxic
Signaling and Immune Function
Pénélope Paradis-Deschênes 1,2 , Denis R. Joanisse 1,2 , Pascale Mauriège 1,2 and
François Billaut 1,2
*
1Département de kinésiologie, Université Laval, Québec, QC, Canada, 2Institut Universitaire de Cardiologie et de
Pneumologie de Québec, Québec, QC, Canada
Optimizing traditional training methods to elicit greater adaptations is paramount for
athletes. Ischemic preconditioning (IPC) can improve maximal exercise capacity and
up-regulate signaling pathways involved in physiological training adaptations. However,
data on the chronic use of IPC are scarce and its impact on high-intensity training is
still unknown. We investigated the benefits of adding IPC to sprint-interval training (SIT)
on performance and physiological adaptations of endurance athletes. In a randomized
controlled trial, athletes included eight SIT sessions in their training routine for 4 weeks,
preceded by IPC (3 ×5 min ischemia/5 min reperfusion cycles at 220 mmHg, n=11)
or a placebo (20 mmHg, n=9). Athletes were tested pre-, mid-, and post-training on
a 30 s Wingate test, 5-km time trial (TT), and maximal incremental step test. Arterial O2
saturation, heart rate, rate of perceived exertion, and quadriceps muscle oxygenation
changes in total hemoglobin (1[THb]), deoxyhemoglobin (1[HHb]), and tissue saturation
index (1TSI) were measured during exercise. Blood samples were taken pre- and
post-training to determine blood markers of hypoxic response, lipid-lipoprotein profile,
and immune function. Differences within and between groups were analyzed using
Cohen’s effect size (ES). Compared to PLA, IPC improved time to complete the TT
(Mid vs. Post: −1.6%, Cohen’s ES ±90% confidence limits −0.24, −0.40;−0.07) and
increased power output (Mid vs. Post: 4.0%, ES 0.20, 0.06;0.35), 1[THb] (Mid vs. Post:
73.6%, ES 0.70, −0.15;1.54, Pre vs. Post: 68.5%, ES 0.69, −0.05;1.43), 1[HHb] (Pre
vs. Post: 12.7%, ES 0.24, −0.11;0.59) and heart rate (Pre vs. Post: 1.4%, ES 0.21,
−0.13;0.55, Mid vs. Post: 1.6%, ES 0.25, −0.09;0.60). IPC also attenuated the fatigue
index in the Wingate test (Mid vs. Post: −8.4%, ES −0.37, −0.79;0.05). VO2peak and
maximal aerobic power remained unchanged in both groups. Changes in blood markers
of the hypoxic response, vasodilation, and angiogenesis remained within the normal
clinical range in both groups. We concluded that IPC combined with SIT induces greater
adaptations in cycling endurance performance that may be related to muscle perfusion
and metabolic changes. The absence of elevated markers of immune function suggests
that chronic IPC is devoid of deleterious effects in athletes, and is thus a safe and potent
ergogenic tool.
Keywords: angiogenesis, blood-flow restriction, HIIT, hypoxia, NIRS, peripheral adaptation
Paradis-Deschênes et al. IPC Combined With SIT
INTRODUCTION
One of the great challenges for coaches and sports scientists is
to identify ergogenic strategies to optimize training adaptations
and performance in athletes for whom adaptations are harder
to elicit (Laursen and Jenkins, 2002; Taylor et al., 2016a).
Indeed, there is a scope to find new approaches to enhance
traditional training methods, and ischemic preconditioning
(IPC) seems promising to achieve this goal. This non-invasive
technique, involving repeated episodes of muscle ischemia
followed by reperfusion at rest, induces transient peripheral
hypoxia and can acutely improve maximal exercise capacity
(Cruz et al., 2016; Salvador et al., 2016). For example, IPC
improved mean power output during a 60 s cycling sprint, with
a greater increase at exercise onset (Cruz et al., 2016), and
time-trial (TT) performance in cyclists (Paradis-Deschênes et al.,
2018; Wiggins et al., 2018). However, the precise physiological
responses and mechanisms associated with these enhancements
are still equivocal. Among the possibilities, IPC could impact
performance by improving local vasodilation, blood flow, and
ultimately O2uptake kinetics during maximal efforts (Enko
et al., 2011; Bailey et al., 2012a; Paradis-Deschênes et al.,
2016; Kilding et al., 2018). Ergogenic molecular and vascular
adaptations within conduit arteries and capillary beds have
also been suggested. Shear stress and local tissue hypoxia
induced by the maneuver increased nitric oxide (NO) levels,
a potent vasodilator (Lochner et al., 2002), activated vascular
endothelial growth-factor (VEGF-α) gene expression and up-
regulated hypoxia inducible factor-1α(HIF-1α) (Fukumura et al.,
2001; Albrecht et al., 2013; Heusch et al., 2015). Thus, IPC could
readily increase exercise tolerance, thereby allowing a greater
training load and subsequent physiological adaptations, notably
by enhancing tissue hypoxia-mediated cell signaling.
The literature on the chronic effects of IPC on performance
is scarce. Repeated exposure to IPC for 7 to 9 days did not
change (Banks et al., 2016) or increase maximal O2consumption
(VO2max) (Lindsay et al., 2017). Improvements in maximal
aerobic power (MAP) and anaerobic capacity (i.e. increase in
peak power output, mean power output, and fatigue index)
during repeated Wingate tests (Lindsay et al., 2017) have also
been reported. However, in athletes, the application of IPC alone
would likely be insufficient to induce such improvements and,
in fact, IPC applied once or twice a day for 7 consecutive days
failed to improve 4-km TT performance in endurance cyclists
(Lindsay et al., 2018). To date, only one study used IPC prior to
high-intensity training sessions, but authors reported that neither
training alone nor training preceded by IPC improved VO2max
and 1-km TT running performance in distance runners after
8 weeks (Slysz and Burr, 2019). This is surprising considering
the previously mentioned acute effects of IPC, and may partly
be explained by: (1) the absence of effects from the 8 weeks
of intensified training per se (comprising a majority of low
intensity running interspersed with tempo and 1-km pace runs),
and (2) the use of unilateral occlusions, which are suspected to
be an insufficient stimulus to derive benefits from IPC (Kraus
et al., 2014; Cocking et al., 2018). Moreover, recent studies on
blood-flow restriction, another modality that targets metabolic
functions by impacting blood flow, also highlight the potency
of such hypoxic strategies to augment metabolic stimulus and
induce greater adaptive responses (Taylor et al., 2016a; Mitchell
et al., 2019). For example, Taylor et al. combined blood-flow
restriction and sprint-interval training (SIT) and reported an
increase in VO2max and a greater expression of the hypoxic
growth factor HIF-1α3 h after a single session, which was not
the case after SIT alone (Taylor et al., 2016a).
SIT is typically characterized by fewer than 12 repeated
supra-maximal or “all-out” efforts lasting 10 to 30 s that are
interspersed by ∼2 to 5 min of passive recovery, and is commonly
used to induce aerobic and anaerobic adaptations (Sloth et al.,
2013). However, although 2 to 8 weeks of SIT can increase
VO2max and performance during TT and Wingate anaerobic
tests (Burgomaster et al., 2006; Hazell et al., 2010; Sloth et al.,
2013), its efficacy on trained individuals is still equivocal.
Interestingly, some characteristics ascribed to this type of training
could benefit from IPC. Indeed, SIT intensity, particularly the
peak power generated during the first seconds of exercise and the
subsequent repeated metabolic stress, has been suggested to be of
particular relevance to adaptations (Hazell et al., 2010; Skelly and
Gillen, 2018). The increase in motor unit recruitment with all-
out efforts is likely responsible for the enhancement of oxidative
capacity and metabolic profile of type II fibers (Bailey et al., 2009),
while metabolic perturbations promote the increase of signaling
processes of different transcription factors for angiogenesis and
mitochondrial biogenesis (Daussin et al., 2008; Psilander et al.,
2010; Cocks et al., 2013), including HIF-1αand VEGF-α(Lee
et al., 2004; Taylor et al., 2016b). Thus, the addition of IPC could
enhance adaptations to SIT by increasing early exercise power
output, further stimulating adaptive signaling pathways.
Therefore, the aim of the current project was to determine
the effect of the combination of IPC and SIT on performance
and physiological adaptations. We hypothesized that IPC and
SIT, compared to SIT alone, would induce greater improvement
in VO2peak, 30 s Wingate test, and 5-km TT performance, and
that the TT enhancement would be concomitant to muscle
oxygenation adaptations. We also hypothesized that blood
markers of angiogenesis and vasodilation would be elevated after
4 weeks of training in the IPC group.
MATERIALS AND METHODS
Ethics Approval
The study was approved by the Ethics Committee of University
Laval, and adhered to the principles established in the
Declaration of Helsinki. Participants provided written informed
consent after being informed of experimental procedures,
associated risks, and potential benefits.
Participants
Twenty seven participants were recruited, seven dropped out
due to external commitments or injuries unrelated to the study
protocol, and 20 completed the study. Subjects trained on average
6.5 ±0.5 h/week in an endurance sport (e.g., cycling, running,
swimming, etc.) at the time of the study, had a training history
longer than 2 years in their respective sport, and a minimal
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Paradis-Deschênes et al. IPC Combined With SIT
cycling experience. All participants were non-smokers, free of
health problems, and did not use any medication or any other
tobacco/nicotine products.
Study Design
Participants visited the laboratory for a total of 16 sessions,
including eight training sessions spread over 4 weeks and
8 testing days for pre- (4), mid- (1), and post-training (3)
evaluations. Pre-training evaluations were divided as follows
and described below (see experimental protocol): (1) maximal
incremental step test, (2) familiarization, (3) body fat and fasted
blood samples, and 4) 30 s Wingate and 5-km TT tests. Using
a between-groups design, participants were pair-matched based
on age, VO2peak, MAP, and TT performance, as well as on
their relative peak power (PPO) and mean power output (MPO)
obtained during the Wingate test, and then randomly assigned
to IPC or PLA (dice roll) to obtain equivalent groups for
every pre-testing variable. Both groups had an identical training
intervention (see training intervention). Mid-training evaluation
included a Wingate Test and a 5-km TT and was executed 2
to 4 days after the fourth training session. Finally, all testing
procedures were repeated post-training, but in a different order:
(1) body fat and fasted blood samples, (2) 30 s Wingate and 5-km
TT tests, and (3) maximal incremental step test.
All sessions were performed at the same time of the day to
avoid potentially confounding circadian rhythm effects and were
separated by a minimum of 2 days to avoid fatigue. Temperature
(21.5 ±0.1◦C, mean ±SE) and humidity (29.9 ±1.0%) were
kept constant. Prior to each testing and training day, vigorous
exercise was avoided for 48 h and alcohol and caffeine were
refrained from for 24 h. During all exercise protocols and training
sessions, participants were instructed to remain seated and were
strongly verbally encouraged. The handlebars and seat settings
of each device (Lode, Velotron, Keiser) were individualized and
replicated throughout the study. Participants were also asked to
replicate non-prescribed training throughout the entire study
and record perceived exertion and duration of every physical
activity in a training log book (Haddad et al., 2017).
Experimental Protocol
Maximal Incremental Step Test
This session was preceded by measurement of resting heart
rate (HR) and blood pressure (inclusion criteria <100 beats
per minute and <140/90 mmHg) in a seated position and
baseline characteristics: body height, body mass, thigh skinfold
thicknesses (IPC: 5.3 ±0.7 mm; PLA: 6.7 ±0.6 mm), and
thigh circumference (IPC: 55.6 ±1.2 cm; PLA: 54.9 ±1.2 cm).
The participant was then positioned on an electromagnetically-
braked cycle ergometer (Excalibur Sport, Lode, the Netherlands)
for a 2 min baseline in a seated position and a 5 min warm-
up at 100 W before the maximal step test (30 W per minute
until volitional exhaustion). Expired gases were analyzed breath-
by-breath throughout the test (Breezesuite, MedGraphics Corp.,
Minnesota, Saint Paul, USA) to assess the VO2, carbon dioxide
production (VCO2), and respiratory exchange ratio. VO2peak
was taken as the highest 20 s average recorded during the test,
and VCO2peak, peak respiratory exchange ratio, peak respiratory
rate, and MAP were also averaged at the time. The respiratory
compensation point was determined by two researchers by
identifying an increase in ventilatory equivalents for O2and
CO2concomitant to a decrease in end-tidal partial pressure of
CO2(Wasserman et al., 1999) plotted against VO2. Values at
the respiratory compensation point are reported in absolute and
relative values (i.e., compared to those at maximal exercise such
as %MAP, %VO2peak, %VCO2peak). Participants were asked
to replicate the same diet at least 2 h before each maximal
incremental step test.
Familiarization
This session was similar to testing procedures described below,
but with a shorter rest between the 30 s Wingate Test and the
5-km TT (15 vs. 30 min), and without any analysis devices.
Body Fat and Fasted Blood Samples
Participants fasted for 12 h before these sessions which occurred
2 days after the familiarization and the last SIT session, for pre-
and post-training assessment, respectively. During this session,
the body fat percentage was measured by bioelectrical impedance
(Tanita TBF-310; Tanita Corp. of America Inc., Arlington
Heights, IL) and blood samples (∼24 mL) were collected from
the antecubital vein in a semi-recumbent position by a registered
nurse (see blood measurements below).
30 s Wingate and 5-km TT Tests
For pre-, mid-, and post-training evaluations, the steps were
always as follows: 5 min rest in a supine position (NIRS baseline
recording), 10 min standardized warm-up, 2 min rest in a seated
position, 30 s Wingate test, 5 min cool down, 30 min rest in a
semi-recumbent position, 10 min standardized self-paced warm-
up, 2 min rest in a seated position, 5-km TT, and 5min cool down.
For the standardized warm-up preceding the Wingate test,
participants were instructed to choose their preferred cadence at
a low resistance for 6 min. This was followed by three 5 s sprints
at a greater resistance (85–95–100%), interspersed by 15 s active
recovery. After these sprints, participants completed the warm-
up at their chosen pace and resistance. For the standardized and
self-paced warm-up (preceding TT), power output, speed, and
gear were continuously noted by the experimenter and strictly
reproduced thereafter.
The 30 s Wingate test and the 5-km TT were executed
on a computer-controlled electrically braked cycle ergometer
(Velotron Elite, RacerMate, Seattle, WA, USA). For the Wingate
test, pedaling rate was gradually increased in order to reach
100 W during 20 s and followed by a 3 s acceleration phase
to attain a peak power as fast as possible. During the 30 s
of maximal exercise phase of the Wingate test, a resistance
equivalent to 7.5% of each participant’s body mass was computer-
controlled (Wingate Software Version 1.11, Lode BV). For the
TT, participants were instructed to complete the 5 km as quickly
as possible, with the distance traveled as the only available
information. Measurements during these tests are described in
the following section. To control for diet and activity patterns
prior to these sessions, participants were asked to record and
Frontiers in Sports and Active Living | www.frontiersin.org 3April 2020 | Volume 2 | Article 41
Paradis-Deschênes et al. IPC Combined With SIT
replicate their dietary intake and physical activity respectively for
24 and 72 h before testing.
Training Intervention
All SIT sessions were performed at the training center of
Université Laval on Keiser M3+cycle ergometers (Keiser
corporation, Fresno, CA), preceded by IPC or PLA procedures,
and supervised by an investigator. Training volume was
increased progressively weekly with two sessions of four, five,
six, and seven 30 s all-out efforts separated by 4 min and 30 s
over 4 weeks. The warm-up was identical as the one performed
during the Wingate tests. All parameters (indoor cycle model,
resistance, handlebars, and seat settings) were replicated for all
training sessions, which always proceeded as follows: IPC or PLA
application, 10 min standardized warm-up, 2 min seated rest, 30 s
all-out efforts, and 5 min cool-down. The 30 s all-out effort was
preceded by an acceleration of 15 s including a 5 s countdown to
increase speed and resistance. After the all-out effort, participants
had a 15 s period of cycling without any resistance at a chosen
pace before the 4 min passive rest. During each sprint, the peak
and the minimum power were noted by the investigator and
participants gave their RPE scores to calculate session RPE (RPE
scores ×duration).
Ischemic Preconditioning
Non-elastic nylon blood pressure cuffs (WelchAllyn, Skaneateles
Falls, NY, USA, width: 21 cm) were positioned around each
upper thigh under the gluteal line and rapidly inflated to 220
mmHg (IPC) or 20 mmHg (PLA) for 5 min to prevent arterial
inflow, three times per limb, alternatively, with each compression
episode separated by 5 min of reperfusion (cuff release). This
protocol has previously been shown to alter physiological
responses and enhance performance (Bailey et al., 2012a; Paradis-
Deschênes et al., 2018), and to completely occlude vascular
arterial inflow (Sabino-Carvalho et al., 2016). To minimize any
placebo effect, participants were told that the purpose of the
study was to compare the impact of two different cuff pressures
that could both alter training positively, with venous or arterial
effects, according to the pressure used. The participants in the
IPC group were familiarized with the pressure before the first
training session.
Instrumentation and Measurements
Arterial O2Saturation (SpO2) and heart rate (HR)
SpO2and HR were recorded at the end of each step of the
maximal incremental step test and every 250 m during TTs from
a pulse oximeter (Nellcor Bedside, Nellcor Inc. Hayward, CA)
with an adhesive forehead sensor secured with a headband.
This technique has been shown to be in good agreement with
hemoglobin O2saturation based on arterial blood analysis over
the 70–100% range (Romer et al., 2007). The SpO2measured
at the forehead is also highly correlated with SaO2measured by
direct arterial blood measurements (R2=0.90, P<0.0001) and
has significantly lower bias and greater precision for SpO2(0.3 ±
1.5%) and HR (1.8 ±5.5%) than finger probes in athletes (Yamaya
et al., 2002).
Near-Infrared Spectroscopy (NIRS)
A portable spatially-resolved, dual wavelength NIRS apparatus
(PortaMon, Artinis Medical Systems BV, The Netherlands)
was installed on the distal part of the right vastus lateralis
muscle (∼15 cm above the proximal border of the patella),
parallel to muscle fibers, to quantify changes in the absorption
of near-infrared light by oxy-hemoglobin (HbO2) and deoxy-
hemoglobin (HHb). The skinfold thickness was measured at the
site of the application of the NIRS using a Harpenden skinfold
caliper (British Indicators Ltd, West Sussex, Great Britain) during
the first session, and was less than half the distance between the
emitter and the detector (i.e., 20 mm). This thickness allows for
adequate penetration of near-infrared light into muscle tissue for
valid measurements (Mccully and Hamaoka, 2000). The device
was packed in transparent plastic wrap to protect it from sweat
and fixed with tape. Black bandages were used to cover the device
from interfering background light. The position of the apparatus
on the thigh was marked with an indelible pen for repositioning
during the same block of tests and a picture was taken for a
better replacement between different blocks (i.e., from pre- to
post-training). The pressure cuff used to induce IPC or PLA
was positioned above the NIRS device and did not affect the
placement of the device.
A modified form of the Beer-Lambert law, using two
continuous wavelengths (760 and 850 nm) and a differential
optical path length factor of 4.95 was used to calculate
micromolar changes in tissue [HbO2], [HHb] and total
hemoglobin ([THb] =[HbO2]+[HHb]). Changes in tissue
saturation index (TSI =[HbO2]/[THb]) were also used as
an index of tissue oxygenation since it reflects the dynamic
balance between O2supply and consumption in the tissue
microcirculation (Van Beekvelt et al., 2001; Ferrari et al., 2004).
This parameter is independent of near-infrared photon path
length in tissue. Before each test, 1 min of baseline values was
analyzed, once the signal was stabilized, to express the magnitude
of change during exercise relative to the baseline values (1[HHb],
1[THb], 1TSI). Thus, all NIRS variables are expressed as the
differences between exercise and rest values (1). 1[HHb] was
taken as an index of muscle O2extraction (Van Beekvelt et al.,
2002), and 1[THb] as a change in regional blood volume (Van
Beekvelt et al., 2001). NIRS data were acquired continuously at
10 Hz for every testing session. A 10th order zero-lag low-pass
Butterworth filter was applied to smooth NIRS signal (Paradis-
Deschênes et al., 2018). Data were averaged over 10 s at the end
of each step of the maximal cycling test and leading up to every
250 m of the TT. For the Wingate test, data were averaged over
2 s at the end of the test and the 30s period, for the peak and the
mean values, respectively.
Power Output
The power output was continuously recorded from the Lode
(maximal incremental step test) and the Velotron ergometer (30 s
Wingate test and 5-km TT). For the 30 s Wingate test, MPO was
averaged along 30 s and PPO was the highest power output over
1 s. The fatigue index was also calculated (FI =[PPO—lowest 1 s
power output]/PPO ×100). For the 5-km TT, power output was
averaged over a period of 10 s leading up to every 250 m.
Frontiers in Sports and Active Living | www.frontiersin.org 4April 2020 | Volume 2 | Article 41
Paradis-Deschênes et al. IPC Combined With SIT
Ratings of Perceived Exertion (RPE)
The RPE scores were recorded at the end of every step of the
VO2peak test and every 500 m of the TT using the Borg 10-point
scale to assess subjective perceived exertion.
Blood Measurements
Blood was collected in four tubes from an antecubital vein in
the morning after at least a 12 h overnight fast and a 15 min rest
period. One tube of 6 mL of plasma was kept at room temperature
and three tubes of 6 mL of serum were placed on ice during
blood collection and centrifuged at 3,000 rpm for 10 min for
the following analysis. Twelve mL of serum were divided in
four aliquots and stored at −80◦C until the end of the project
for HIF-1α, VEGF, NO, and free-fatty acid analyses. HIF-1α
and VEGF-αlevels were determined by high-sensitivity enzyme-
linked immuno-absorbent assays (ELISA) (Invitrogen, Thermo
Fisher Scientific, Ontario) while total NO was assessed with
a colorimetric assay kit (Invitrogen, Thermo Fisher Scientific,
Ontario). The reproducibility of the HIF-1αkit displayed intra-
assay and inter-assay CV values lower than 10%, irrespective of
the concentration. Concerning the VEGF-αkit, CV values for
intra-assay precision were 5.5 and 4.9% while those for inter-
assay precision were 9.3 and 6.5%, for low and high VEGF-
αlevels, respectively. For the NO kit, intra-assay precision
showed CV values of 5.3 and 1.2% while inter-assay precision
presented CV values of 6.9 and 3.3%, for low and high nitrate
concentrations, respectively.
The serum sample (6 mL) and the fourth tube of plasma
of 6-mL were sent immediately after blood sampling and
analyzed within 2 h at the Quebec Heart and Lung Institute.
Plasma was analyzed using the LH 780 (Beckman Coulter) for
a complete blood profile (including blood count, hemoglobin,
hematocrit, etc.). Serum was analyzed using standardized
laboratory procedures on a Dimension Vista 1500 Intelligent
Lab System (Siemens) to determine ferritin concentration by
chemiluminescent ELISA and the lipid-lipoprotein profile.
Fasting total cholesterol, triglyceride, and high-density
lipoprotein (HDL)-cholesterol levels were determined by
colorimetry. Fasting low-density lipoprotein (LDL)-cholesterol
concentrations were estimated using the Friedewald equation
(Friedewald et al., 1972). Free-fatty acid levels were enzymatically
measured by a colorimetric method (Wako Chemicals, Ontario).
Fasting glucose was analyzed using a Dimension Vista 1500
Intelligent Lab System (Siemens) by photometry and the
insulin levels using ADVIA Centaur XPT (Siemens) by
immunoassay. All measurements were performed in duplicate,
and then averaged.
Statistical Analysis
We evaluated the magnitudes of difference within groups from
pre- and mid-training to post-training for all variables as well as
the percentage difference between change in IPC and PLA during
the first (0 to 2.5 km) and the second (2.6 to 5 km) half of the
TT and the entire TT. Practical significance was evaluated using
Cohen’s effect sizes (ES) ±90% confidence limits, and compared
to the smallest worthwhile change that was calculated as the
standardized mean difference of 0.2 between-subject standard
deviations (Batterham and Hopkins, 2006; Hopkins et al., 2009).
All variables were log-transformed before analysis (Hopkins
et al., 2009), except for 1[THb] and HIF-1αconcentration,
and raw data are reported as mean ±standard error (SE) for
clarity. Standardized effects were classified as small (0.2–0.49),
moderate (0.5–0.79), or large (≥0.8) (Hopkins et al., 2009).
Using mechanistic inferences, qualitative probabilistic terms for
benefit were assigned to each effect for mechanical, NIRS,
cardiorespiratory, blood markers, and perceptual variables using
the following scale: 50 to 75%, possibly; 75 to 95%, likely; 95 to
99.5%, very likely; >99.5%, almost certainly. The effect of IPC
was deemed “unclear” if chances of having better/greater and
poorer/lower changes in performance and physiological variables
were both >5% (Batterham and Hopkins, 2006; Hopkins et al.,
2009). Pearson correlations were calculated to assess associations
between physiological changes and performance improvements.
Correlation coefficients of >0.1, >0.3, >0.5, and >0.7 were
considered small, moderate, large, and very large (Hopkins et al.,
2009).
RESULTS
All participants completed all assigned sessions and tolerated
the IPC procedure without complications. The values of two
participants in the IPC group for the mid-training sessions (two
Wingate tests and one TT) were not included because of food
indigestion and technical problems with the Velotron ergometer.
Baseline characteristics between IPC (age 31.5 ±3.0 yr; body
mass 76.3 ±2.9 kg; height 1.80 ±0.02 m; body fat 12.0 ±2.0 %,
n=11) and PLA (28.1 ±2.5 yr; 74.3 ±3.4 kg; 1.76 ±0.03 m;
10.2 ±1.6 %, n=9) groups were not significantly different
and were not altered by the intervention. Prior to training,
there was no difference in any physiological and performance
variables between groups (VO2peak, MAP, TT cycling time, PPO,
and MPO).
30 s Wingate test
Performance Parameters
Table 1 displays mechanical and muscle oxygenation variables
during the Wingate tests. Both groups increased power output
over the course of the training. The only between-group
differences were that the increase in PPO relative to body mass
from mid- to post-training was possibly lower in IPC. However,
IPC likely decreased the fatigue index from mid- to post-training
compared to PLA.
Muscle Oxygenation Variables
From pre- to post-training, IPC maintained the index of muscle
blood volume (1[THb]mean and 1[THb]peak) whereas it clearly
declined in PLA (Table 1). Similar modifications were observed
from mid- to post-training, which yielded a clear between-group
difference in these parameters. These changes were concomitant
to those in the Wingate fatigue index in favor of IPC. There were
also possible differences between IPC and PLA from pre- to post-
training in 1[HHb]mean,1[HHb]peak ,1TSImean, and 1TSIpeak .
Moreover, from pre- to post-training, the change in PPO was
correlated with 1[HHb]mean (r=0.83) and 1[HHb]peak (r=
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Paradis-Deschênes et al. IPC Combined With SIT
TABLE 1 | Mechanical and near-infrared spectroscopy variables during the 30 s Wingate test after IPC and PLA at pre-, mid- and pos t-training.
IPC PLA 1IPC vs. 1PLA
PRE MID POST PRE MID POST MID vs. POST PRE vs. POST
Mean ±SE Mean ±SE %D (ES) CL
MPO (W) 751 ±35 752 ±34 759 ±32 705 ±34 709 ±36 718 ±32 −0.4% (−0.02)
−0.22;0.17
−0.6% (−0.04)
−0.23;0.16
MPO (W/kg) 9.9 ±0.4 9.9 ±0.4 10.0 ±0.3 9.5 ±0.3 9.5 ±0.3 9.7 ±0.3 −0.4% (−0.03)
−0.29;0.23
−0.6% (−0.05)
−0.30;0.21
PPO (W) 1078 ±63 1126 ±75 1131 ±83 1008 ±28 1053 ±46 1094 ±62a,b−3.3% (−0.19)
−0.53;0.16
−3.3% (−0.19)
−0.66;0.29
PPO (W/kg) 14.1 ±0.6 14.7 ±0.7a14.8 ±0.8a13.7 ±0.6 14.2 ±0.5 14.8 ±0.6a,b−3.3% (−0.23)
−0.64;0.19
−3.3% (−0.23)
−0.80;0.35
Fatigue index (%) 51.7 ±2.6 54.9 ±4.4 52.3 ±5.2b53.5 ±3.7 54.4 ±3.5 56.0 ±3.8 −8.4% (−0.37)
−0.79;0.05
−6.9% (−0.30)
−1.01;0.40
1[HHb]mean (µM) 18.0 ±2.4 18.6 ±2.5 20.4 ±3.1 14.5 ±1.4 14.7 ±1.6 14.6 ±1.5 7.1% (0.13)
−0.18;0.44
13.9% (0.25)
−0.12;0.62
1[HHb]peak (µM) 19.6 ±2.5 20.8 ±2.7 22.5 ±3.1a15.7 ±1.8 16.2 ±1.9 15.8 ±1.7 8.9% (0.17)
−0.14;0.47
15.3% (0.28)
−0.09;0.64
1[THb]mean (µM) 8.13 ±2.6 6.73 ±2.6 9.33 ±2.7 6.46 ±0.9 5.14 ±1.1 4.03 ±2.4a43.3% (0.42)
−0.06;0.91
36.2% (0.38)
−0.21;0.97
1[THb]peak (µM) 11.6 ±2.9 10.4 ±2.8 11.5 ±2.9 9.82 ±1.2 7.66 ±1.6 7.05 ±2.5a20.8% (0.28)
−0.10;0.66
28.4% (0.40)
−0.16;0.96
1TSI mean (%) −32.7 ±2.5 −30.7 ±2.8 −35.6 ±5.5 −32.1 ±3.3 −33.2 ±3.8 −39.1 ±4.0a−11.6% (−0.33)
−1.41;0.76
−17.4% (−0.51)
−1.21;0.20
1TSI peak (%) −31.2 ±2.4 −29.6 ±2.5 −35.7 ±5.1 −29.4 ±3.2 −30.2 ±3.8 −37.5 ±3.6a−17.7% (−0.42)
−1.52;0.69
−16.4% (−0.38)
−0.97;0.20
CL, confidence limits; %D, percentage difference between changes in IPC and PLA; ES, effect size; 1[HHb], change in deoxy-hemoglobin; MPO, mean power output; PPO, peak power
output; 1[THb], change in total hemoglobin; 1TSI, change in tissue saturation index.
a,bclear changes within each group in post- compared to pre- and mid-training, respectively.
Differences between changes in IPC and PLA are indicated in bold.
FIGURE 1 | Average and individual completion times of the 5-km time trial at pre-, mid-, and post-training in IPC and PLA. IPC improved TT performance post-
compared to pre- (↑2.1%, ES 0.32, 0.14;0.51) and mid- (↑1.8%, ES 0.28, 0.12; 0.44). (‡), clear post- compared to mid- between-group (IPC –PLA) differences
(↑1.6%, ES 0.24, −0.07; 0.40). Values are mean ±SE.
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Paradis-Deschênes et al. IPC Combined With SIT
0.75) in IPC group, and with 1TSImean (r=0.79) and 1TSIpeak
(r=0.78) in PLA group.
5-km Time Trial
Performance Parameters
Average and individual completion times of the TT are displayed
in Figure 1. The calculated smallest worthwhile change for TT
time in IPC and PLA group, respectively, equated to 5.94 s and
7.29 s from pre- to post-training, and to 5.74 and 6.80 s from mid-
to post-training. The completion time in post- was likely faster in
IPC compared to both pre- (−10.6 s, −2.1%, ES 0.32) and mid-
training (−9.1 s, −1.8%, ES 0.28). Changes in PLA were trivial
with improvements of 4.4 s from pre- to post-training. When
comparing groups, IPC produced possible faster times from mid-
to post-training (−8.0 s, −1.6%, ES 0.24) compared to PLA.
The power output profiles during the TT are displayed
in Figure 2. IPC likely increased overall power output in
post- compared with pre- (5.5%, ES 0.31, confidence limits
0.12;0.50) and mid-training (4.7%, ES 0.27, 0.12;0.43). Changes
in PLA remained trivial. Thus, compared with PLA, IPC clearly
increased power output in the first half in post- compared with
pre- (6.1%, ES 0.30, −0.02;0.62) and mid-training (7.1%, ES
0.36, 0.06;0.65) and during the entire TT compared with mid-
training (4.0%, ES 0.20, 0.06;0.35). As there was no change in
any performance variables from pre- to mid-training, we focused
our analysis of the physiological changes from pre- and mid-
to post-training.
Physiological and Perceptual Responses
Muscle oxygenation variables are displayed in Figure 3. Overall,
PLA did not alter 1[HHb], but increased 1TSI in post-
compared with pre- (ES 0.78, 0.26;1.31) and mid-training (ES
0.52, −0.08;1.13). PLA also lowered 1[THb] in the second half
of the TT from pre- to post-training (ES −0.56, −1.37;0.25).
On the other hand, IPC produced clear changes in all NIRS
parameters. It increased 1[THb] from mid- to post-training (ES
0.34, −0.02;0.69) which yielded clear differences with PLA in
the first and second halves and the entire TT (post- vs. pre-:
73.6%, ES 0.70, −0.15;1.54, Figure 3A). From mid- to post-
training, the increase in 1[THb] was very largely correlated with
the improvement in chronometric performance in IPC only (r
=0.77).
IPC also clearly increased 1[HHb] in the first half of (ES
0.25, 0.18;0.32) and during the entire TT (ES 0.21, 0.14;0.27).
Compared with PLA, IPC increased 1[HHb] from pre- to post-
training in the first (13.9%, ES 0.26, −0.07;0.59) and second half
(11.7%, ES 0.22, −0.15;0.59), and during the entire TT (12.7%, ES
0.24, −0.11;0.59, Figure 3B). The increase in power output in the
second half of the TT from pre- to post-training in IPC was very
largely correlated with both 1[HHb] (r=0.71) and 1[THb] (r
=0.71).
IPC increased 1TSI (i.e., lowered absolute TSI) in the second
half of the TT from mid- to post-training (ES 0.27, −0.21;0.74).
Compared with PLA, IPC maintained 1TSI during the entire
TT from pre- to post-training (−24.2%, ES −0.57, −1.32;0.17,
Figure 3C).
FIGURE 2 | Power output profile during the 5-km time trial at pre- (open
symbols), mid- (gray symbols) and post-training (black symbols) in IPC and
PLA. Power outputs were as follows: pre- (IPC: 271 ±13 W; PLA: 276 ±
18 W), mid- (IPC: 273 ±13 W; PLA: 279 ±17 W), and post-training (IPC: 285
±13 W; PLA: 281 ±17 W). W ithin-group difference between time points are
indicated in the square box for the first half (1/2) and the entire TT (all). (†) and
(‡) indicate clear differences between-groups (IPC vs. PLA) at post- compared
to pre- and mid-, respectively. Values are mean ±SE.
HR and SpO2are displayed in Table 2. PLA did not alter
SpO2, but increased HR from pre- to post-training. IPC decreased
SpO2in the second half and increased HR in post-, compared
with pre- and mid-training during the entire TT. The increase
in power output in the second half of the TT from pre- to post-
training in IPC was correlated with HR (r=0.73). Compared
with PLA, IPC increased SpO2and HR in post-, compared with
pre- and mid-training.
RPE increased in both groups during the entire TT in
post-, compared with pre- (PLA: 10.4%, ES 0.63, 0.26;1.00, IPC:
19.8%, ES 0.87, 0.39;1.34) and mid-training (PLA: 5.7%, ES 0.39,
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Paradis-Deschênes et al. IPC Combined With SIT
FIGURE 3 | Average 1[THb], 1[HHb] and 1TSI during the 5-km time trial at pre- (open symbols), mid- (gray symbols) and post-training (black symbols) in IPC and
PLA. Data were as follows: (A) Average 1[THb] for TT at pre- (IPC: 16.9 ±2.9 µM; PLA: 15.5 ±1.2 µM), mid- (IPC: 14.4 ±2.8 µM; PLA: 13.3 ±1.4 µM), and
post-training (IPC: 17.4 ±2.6 µM; PLA: 12.6 ±2.1 µM). (B) Average 1[HHb] for TT at pre- (IPC: 19.9 ±2.6 µM; PLA: 16.1 ±2.0 µM), mid- (IPC: 20.6 ±2.5 µM;
PLA: 16.5 ±2.0 µM), and post-training (IPC: 22.3 ±2.8 µM; PLA: 16.3 ±1.9 µM). (C) Average 1TSI for TT at pre- (IPC: −28.5 ±3.3%; PLA: −27.5 ±4.1%), mid-
(IPC: −27.2 ±3.4%; PLA: −31.2 ±2.0%), and post-training (IPC: −32.4 ±4.8%; PLA: −37.8 ±4.3%). Within-group differences between time points are indicated
in the square boxes for the first half (1/2), the second half (2/2) and the entire TT (all). (†) and (‡) indicate clear differences between-groups (IPC vs. PLA) at post-
compared to pre- and mid-, respectively. Values are mean ±SE.
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Paradis-Deschênes et al. IPC Combined With SIT
TABLE 2 | Average HR and SpO2during the 5-km cycling time trial after IPC and PLA at pre-, mid-, and post-training.
IPC PLA 1IPC vs. 1PLA
PRE MID POST PRE MID POST MID vs. POST PRE vs. POST
Mean ±SE Mean ±SE %D (ES) CL
Heart rate (beats per minute)
0.5 km 159 ±4 160 ±4 165 ±4ab 158 ±3 153 ±5 160 ±2ab −2.4% (−0.17)
−0.62;0.29
2.6% (0.17)
−0.02;0.36
1.0 km 164 ±4 164 ±4 169 ±4ab 163 ±3 163 ±3 165 ±2 1.9% (0.13)
−0.10;0.36
2.6% (0.17)
−0.05;0.39
2.0 km 170 ±3 169 ±4 170 ±4 168 ±2 166 ±2 169 ±2b−0.5% (−0.03)
−0.17;0.11
0.3% (0.02)
−0.17;0.21
3.0 km 173 ±4 172 ±4 174 ±4 170 ±2 169 ±2 171 ±2 1.1% (0.18)
−0.22;0.59
0.6% (0.10)
−0.38;0.57
4.0 km 175 ±4 174 ±4 178 ±4ab 172 ±2 172 ±2 174 ±2 1.6% (0.26)
−0.09;0.61
1.4% (0.23)
−0.12;0.58
5.0 km 180 ±3 185 ±4 188 ±2ab 178 ±2 180 ±2 180 ±22.5% (0.42)
−0.14;0.99
3.5% (0.59)
0.08;1.10
Arterial O2saturation (%)
0.5 km 96.8 ±0.5 97.0 ±0.6 97.5 ±0.5 96.7 ±1.4 98.4 ±0.7 96.0 ±1.5b1.4% (0.46)
−0.10;1.02
1.4% (0.38)
−0.03;0.79
1.0 km 97.5 ±0.4 97.1 ±0.5 97.4 ±0.6 96.6 ±1.4 97.9 ±0.6 96.6 ±1.3 0.4% (0.12)
−0.37;0.61
−0.2% (−0.06)
−0.47;0.35
2.0 km 97.0 ±0.3 96.2 ±0.5 96.5 ±0.5 96.3 ±0.7 96.4 ±0.6 96.4 ±0.5 0.2% (0.06)
−0.23;0.36
−0.7% (−0.19)
−0.48;0.09
3.0 km 96.3 ±0.3 95.7 ±0.3 95.7 ±0.4 95.8 ±0.7 96.1 ±0.7 95.8 ±0.6 0.3% (0.20)
−0.47;0.88
−0.6% (−0.33)
−0.83;0.17
4.0 km 95.8 ±0.4 95.3 ±0.4 95.1 ±0.5 95.8 ±0.4 95.8 ±0.5 95.6 ±0.4 0.3% (0.21)
−0.37;0.78
−0.1% (−0.05)
−0.50;0.40
5.0 km 95.4 ±0.4 94.8 ±0.8 93.8 ±0.8a95.8 ±0.7 94.8 ±0.7 94.8 ±0.5 −0.4% (−0.24)
−1.04;0.55
0.1% (0.06)
−0.80;0.93
CL, confidence limits; %D, percentage difference between changes in IPC and PLA; ES, effect size.
a,bclear changes within each group in post- compared to pre- and mid-training, respectively.
Differences between changes in IPC and PLA are indicated in bold.
0.10;0.67, IPC: 11.1%, ES 0.39, 0.10;0.67), and scores were higher
in IPC –PLA (ES 0.31, −0.11;0.74).
Maximal Incremental Step Test
Peak values at the end of exercise during maximal incremental
step test and percentage differences between groups, from pre-
to post-training, are displayed in Table 3. At maximal exercise,
there was no change within and between groups for MAP, VO2,
respiratory rate, SpO2, RPE, 1[HHb], and 1[THb]. However,
IPC decreased respiratory exchange ratio and VCO2at maximal
exercise compared to PLA.
Mechanical and physiological variables at the respiratory
compensation point during maximal incremental step test and
percentage differences between groups, from pre- to post-
training, are displayed in Table 4. Compared to PLA, IPC
increased power output, VO2and VCO2.
Blood Markers of Hypoxic Response and
Blood Profile
Both IPC and PLA led to similar decreases in VEGF-αover time,
but did not modify NO and HIF-1α. There was no difference
between groups for all these markers (Table 5).
The blood profile is summarized in Table 5. IPC increased
platelets concentration and the distribute index of erythrocytes,
and decreased mean corpuscular hemoglobin level and average
hemoglobin concentration. PLA decreased hematocrit, ferritin,
and platelets concentration post-training. There was a clear
difference between groups for platelets, the distribute index of
erythrocytes, hematocrit, and ferritin concentrations. Regarding
the immune function, IPC increased total leucocytes and
neutrophils, and decreased eosinophils, lymphocytes, and
monocytes, while PLA decreased total leucocytes. Compared to
PLA, IPC induced greater changes in leucocytes, neutrophils,
monocytes, and eosinophils from pre- to post-training. However,
all values and changes within and between groups remained
within the normal clinical range of all variables for a
healthy population.
The lipid-lipoprotein profile and glucose-insulin homeostasis
are summarized in Table 6. IPC increased TG levels, whereas
PLA increased TG and decreased free-fatty acid levels. There was
a clear difference between-groups for LDL-cholesterol and free-
fatty acid concentrations. Finally, IPC increased insulin levels,
while PLA increased fasting glucose levels, and this yielded a clear
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Paradis-Deschênes et al. IPC Combined With SIT
TABLE 3 | Mechanical and physiological variables at the end of exercise during the maximal incremental step test after IPC and PLA at pre- and post-training.
IPC PLA 1IPC VS. 1PLA
PRE POST %d (ES) PRE POST %d (ES) %D (ES) CL
MAP (W) 359 ±16 367 ±15
2.3% (0.15)
360 ±21 363 ±19
1.3% (0.07)
1.0% (0.06)
−0.19;0.32
VO2peak (mL/min/kg) 57.6 ±3.0 58.6 ±2.7
2.1% (0.11)
58.1 ±2.8 58.5 ±2.4
1.0% (0.07)
1.1% (0.07)
−0.29;0.43
VO2peak (mL/min) 4341 ±207 4427 ±196
2.1% (0.13)
4308 ±252 4351±260
1.0% (0.05)
1.1% (0.07)
−0.27;0.40
VCO2peak (mL/min) 4922 ±138 4873 ±153
−1.1% (0.10)
4691 ±300 4832 ±284
3.3% (0.16)
−4.2% (−0.30)
−0.61;0.02
RERpeak 1.15 ±0.04 1.11 ±0.04
−3.2% (−0.27)
1.09 ±0.04 1.12 ±0.04
2.2% (0.19)
−5.3% (−0.48)
−1.08;0.11
RRpeak (L/min) 163 ±7 160 ±6
−1.5% (−0.11)
165 ±10 164 ±7
0.1% (0.00)
−1.5% (−0.10)
−0.78;0.58
HRpeak (bpm) 180 ±3.7 179 ±4.4
−0.5% (−0.07)
178 ±3.6 175 ±3.4a
−1.4% (−0.20)
0.8% (0.11)
−0.21;0.43
SpO2peak (%) 96.6 ±0.3 96.1 ±0.4
−0.6% (−0.43)
96.7 ±0.6 96.6 ±0.7
−0.1% (−0.06)
−0.4% (−0.27)
−1.11;0.57
1[HHb]peak (µM) 21.2 ±2.8 21.9 ±2.0
8.0% (0.16)
15.3 ±2.0 15.7 ±1.9
2.1% (0.05)
5.8% (0.12)
−0.42;0.67
1[THb]peak (µM) 12.7 ±2.8 10.2 ±1.2
−19.8% (−0.35)
8.3 ±1.7 7.0 ±1.7
−15.5% (−0.23)
−4.3% (−0.20)
−1.10;0.71
1TSIpeak (%) 37.2 ±4.3 34.6 ±3.4
−1.4% (−0.03)
26.6 ±2.1 33.1 ±3.1a
21.3% (0.57)
−18.8% (−0.49)
−1.33;0.35
CL, confidence limits; %d, in-group percentage difference between pre- and post-training; %D, percentage difference between changes in IPC and PLA; ES, effect size; 1[HHb],
change in deoxy-hemoglobin; HR, heart rate; MAP, maximal aerobic power; RER, respiratory exchange ratio; RR, respiratory rate; SpO2, arterial O2saturation; 1[THb], change in total
hemoglobin; 1TSI, change in tissue saturation index; VO2, O2consumption; VCO2, carbon dioxide production.
aclear change within each group in post- compared to pre-training.
Differences between changes in IPC and PLA are indicated in bold. Values are mean ±SE.
difference between groups for fasting glucose levels. Importantly,
all values and changes within and between groups were within
the normal clinical range of all variables for a healthy population.
DISCUSSION
This study investigated the potential of IPC to enhance
performance adaptations following SIT and attempted to
elucidate some potential physiological underpins. The main
findings were that in endurance athletes, when compared to
SIT alone, eight sessions of SIT immediately preceded by three
cycles of bilateral occlusions led to greater improvements in mean
power output (∼5%) and completion time (∼2%) during a 5-km
maximal cycling time trial, as well as increased fatigue resistance
(∼8.5%) during a Wingate test. Peak power output during the
Wingate test was increased similarly in both groups. Although the
adaptive responses to both aerobic and anaerobic performances
are complex, the current study presents some evidence to suggest
that increased muscle perfusion and peripheral O2extraction
occurred after IPC.
Few studies have investigated performance changes after
chronic IPC, and only one applied this manoeuver before a
training stimulus. Four cycles of upper-limb occlusion repeated
over a period of 7 to 9 days, without any training, had no effect
(Banks et al., 2016) or increased VO2max (Lindsay et al., 2017).
Lindsay et al. also reported an increase in MAP and Wingate
performance in recreationally-active participants (Lindsay et al.,
2017). In athletes, application of IPC alone would likely be
insufficient to induce such improvements (Marocolo et al., 2018).
Indeed, IPC applied once or twice a day for 7 consecutive days
failed to improve 4-km TT in trained cyclists (Lindsay et al.,
2018), but combining IPC with high-intensity training could
trigger larger adaptations. Surprisingly, trained middle-distance
runners did not improve VO2max or 1-km TT performance
after 8 weeks of training alone or when preceded by IPC (Slysz
and Burr, 2019). The absence of effect on VO2peak and MAP is
confirmed in the present study, but we observed an improvement
in TT performance. Two possibilities might explain the lack of
impact of IPC in this earlier study. First, the use of unilateral
occlusions may not have provided a sufficient stimulus to derive
benefits from IPC (Kraus et al., 2014; Cocking et al., 2018).
Second, the training was mostly composed of low intensity
sessions and a few faster-pace runs, which was likely not sufficient
to trigger adaptations in trained athletes. SIT, however, has been
shown to improve endurance performance in trained cyclists
(Laursen et al., 2002) and runners (Esfarjani and Laursen, 2007).
Although time spent at >90% VO2max during SIT sessions is
low (typically 0–60 s in trained cyclists for an entire training
session), it has been suggested that muscle O2demand is high,
especially as the number of sprints increases, as suggested by low
muscle oxygenation levels (Buchheit et al., 2012; Paquette et al.,
2019). In the present study, both groups increased the peak power
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Paradis-Deschênes et al. IPC Combined With SIT
TABLE 4 | Mechanical and physiological variables at the respiratory compensation point during the maximal incremental step test after IPC and PLA at pre- and
post-training.
IPC PLA 1IPC VS. 1PLA
PRE POST %d (ES) PRE POST %d (ES) %D (ES) CL
Power (W) 291 ±13 305 ±13a
4.7% (0.30)
303 ±20 303 ±17
0.6% (0.03)
4.1% (0.24)
−0.12;0.61
%MAP 81.1 ±1.4 83.7 ±1.7a
3.1% (0.44)
84.1 ±1.7 83.6 ±2.3
−0.8% (−0.09)
3.9% (0.54)
−0.42;1.49
VO2(mL/min) 3443 ±187 3669 ±178a
6.8% (0.37)
3581 ±256 3571 ±219
0.3% (0.01)
6.5% (0.33)
0.00;0.67
%VO2peak 79.22 ±1.5 82.9 ±1.5a
4.6% (0.66)
82.6 ±1.3 82.1 ±1.5
−0.7% (−0.12)
5.3% (0.85)
−0.07;1.76
VCO2(mL/min) 3562 ±120 3808 ±143a
6.8% (0.52)
3622 ±241 3755 ±221a
4.1% (0.20)
2.6% (0.16)
−0.35;0.67
%VCO2peak 72.5 ±1.9 78.3 ±2.3a
8.0% (0.75)
77.2 ±1.6 78.0 ±2.5
0.9% (0.10)
7.1% (0.73)
−0.11;1.58
RER 1.05 ±0.03 1.05 ±0.03
0.1% (0.01)
1.02 ±0.03 1.06 ±0.03a
3.8% (0.42)
−3.6% (−0.39)
−1.04;0.26
CL, confidence limits; %d, in-group percentage difference between pre- and post-training; %D, percentage difference between changes in IPC and PLA; ES, effect size; MAP, maximal
aerobic power; RER, respiratory exchange ratio; VO2, O2consumption; VCO2, carbon dioxide production.
aclear change within each group in post- compared to pre-training.
Differences between changes in IPC and PLA are indicated in bold. Values are mean ±SE.
output during the Wingate test, but only the chronic application
of bilateral IPC prior to SIT sessions improved TT performance
in endurance athletes in just 4 weeks.
Of all performance tests realized in this study, the 5-km self-
paced time trial would be the most relevant to athletes wishing
to enhance their sport performances. Endurance performance is
mainly determined by maximal cardiorespiratory fitness, exercise
economy, and anaerobic capacity (Hawley et al., 1997). In our
study, the maximal cardiorespiratory fitness and the anaerobic
capacity do not seems to be involved. Indeed, the end variables in
the incremental step test (VO2max and MAP), which is mainly
determined by central components, were not improved and the
Wingate test was increased similarly in both groups. On the
other hand, the changes in muscle hemodynamics, visible only
after 4 weeks and accompanying the endurance performance
enhancement in both tests following IPC, seem to be a key factor.
More precisely, local blood volume tended to decrease in both
groups at mid- compared to pre-training, with no clear changes
in muscle O2extraction and, thus, on performance. However,
after 2 more weeks with IPC, participants clearly improved their
TT performance and the reduction of the local blood volume
during exercise was reversed and returned to initial values despite
the increase in power output. Coincident with this increase in
1[THb] was an increase in 1[HHb] and a better maintenance
of 1TSI, which likely reflects a matching between O2extraction
and delivery. The likely positive effect of muscle hemodynamics
changes on performance after IPC is also confirmed by the
correlation between 1[THb] and chronometric performance, as
well as 1[HHb] and TT power output. In the PLA group, the
1[THb] decreased throughout the 4 weeks and so did the 1TSI,
without any clear change in TT performance. It could be argued
that the increase in HR could partly explain the increase in
local blood volume and the performance considering the positive
correlation between HR and power output. However, because
the participants were free to adjust their workload, we cannot
ascertain if the changes in cardiovascular hemodynamics are
associated with IPC or to a higher work rate, the latter being the
more plausible hypothesis. Indeed, acute IPC is mostly reported
to have no effect on HR during maximal exercise (Bailey et al.,
2012b; Kido et al., 2015; Salvador et al., 2016; Kilding et al.,
2018). In addition, a difference in HR of ∼1% can hardly explain
alone the difference in local blood volume, especially since HR
and 1[THb] displayed different patterns. Therefore, we conclude
from these results that IPC combined with SIT induces additional
adaptations at the peripheral level by increasing muscle perfusion
and O2uptake during exercise which could, in turn, increase
endurance performance.
The present results also indicated that endurance performance
enhancement could be due to an improvement in ventilatory
threshold. The observation of a greater respiratory compensation
point, which is predominantly determined by peripheral
mechanisms (Joyner and Coyle, 2008), and the decrease in
VCO2and respiratory exchange ratio at maximal exercise,
suggest an improved oxidative capacity, visible only after
IPC. These results, combined with the observed peripheral
adaptations on muscle perfusion and O2uptake, could suggest
a speeding of the VO2kinetics, which could reduce the O2
deficit and the reliance on substrate level phosphorylation.
As mentioned earlier, very few studies have investigated the
effects of chronic IPC on training, but studies on acute IPC
confirmed this possibility. Indeed, acute IPC has been reported
to speed HHb kinetics (Kido et al., 2015) and, without changing
first ventilatory threshold, VO2peak and MAP, and to have a
beneficial priming effect (i.e., a decrease in VO2slow component
amplitude in the heavy-intensity domain) on well-trained male
cyclists (Kilding et al., 2018). Authors of this study suggested
Frontiers in Sports and Active Living | www.frontiersin.org 11 April 2020 | Volume 2 | Article 41
Paradis-Deschênes et al. IPC Combined With SIT
TABLE 5 | Blood markers of the hypoxic response and blood profile after IPC and PLA at pre- and post-training.
IPC PLA 1IPC VS. 1PLA
PRE POST %d (ES) PRE POST %d (ES) %D (ES) CL
Hypoxic response
HIF-1α(pg/mL) 2.48 ±1.71 2.77 ±1.94
11.7% (0.04)
1.69 ±0.93 1.83 ±1.09
7.8% (0.04)
3.9% (0.03)
−0.09;0.16
VEGF-α(pg/mL) 23.2 ±3.3 19.8 ±3.8a
−19.5% (−0.37)
24.2 ±4.6 19.2 ±4.0a
−21.9% (−0.38)
3.1% (0.05)
−0.47;0.58
NO (pg/mL) 40.1 ±3.6 36.2 ±2.1
−7.4% (−0.26)
43.2 ±5.9 39.4 ±3.4
−5.3% (−0.15)
−2.2% (−0.07)
−0.87;0.73
Blood profile
Erythrocytes (1012/L) 4.89 ±0.10 4.92 ±0.10
0.7% (0.10)
4.71 ±0.11 4.70 ±0.12
−0.2% (−0.02)
0.9% (0.12)
−0.20;0.43
MCV (fL) 89.3 ±0.9 89.2 ±0.9
−0.2% (−0.06)
90.0 ±0.8 89.2 ±1.3
−1.0% (−0.25)
0.8% (0.22)
−0.35;0.79
DIE (%) 13.2 ±0.1 13.3 ±0.2a
1.0% (0.28)
13.3 ±0.1 13.2 ±0.1
−0.7% (−0.25)
1.8% (1.05)
−0.07;2.16
Hemoglobin (g/L) 147 ±2 148 ±2
0.1% (0.01)
143 ±2 141 ±2
−0.9% (−0.18)
1.0% (0.19)
−0.25;0.63
MCHC (pg) 30.2 ±0.4 30.0 ±0.4a
−0.9% (−0.20)
30.3 ±0.3 30.1 ±0.5
−0.9% (−0.19)
0.0% (0.00)
−0.71;0.70
AHC (g/L) 338 ±2 336 ±2a
−0.7% (−0.42)
337 ±2 338 ±2
0.2% (0.09)
−0.9% (−0.52)
−1.47;0.43
Ferritin (µg/L) 121 ±21 128 ±27
1.2% (0.02)
92 ±18 82 ±20a
−19.4% (−0.29)
25.6% (0.32)
−0.14;0.79
Platelets (109/L) 190 ±11 200 ±11a
5.2% (0.24)
200 ±10 194 ±9
−2.7% (−0.17)
8.1% (0.44)
−0.02;0.89
APV (fL) 9.69 ±0.48 9.65 ±0.43
−0.2% (−0.01)
8.58 ±0.27 8.39 ±0.24
−2.1% (−0.21)
1.9% (0.14)
−0.19;0.47
Leucocytes (109/L) 4.99 ±0.36 5.40 ±0.33a
8.6% (0.37)
5.66 ±0.61 4.91 ±0.33a
−11.1% (−0.41)
22.1% (0.84)
0.06;1.62
Neutrophils (%) 48.4 ±1.7 51.0 ±1.9a
5.1% (0.39)
54.5 ±1.8 53.7 ±2.1
−1.8% (−0.15)
7.0% (0.54)
−0.01;1.09
Eosinophils (%) 3.15 ±0.57 2.65 ±0.50a
−18.7% (−0.26)
2.47 ±0.52 2.41 ±0.44
1.3% (0.02)
−19.7% (−0.33)
−0.63;−0.03
Basophils (%) 0.609 ±0.039 0.609 ±0.031
0.6% (0.03)
0.500 ±0.047 0.533 ±0.090
−2.6% (−0.05)
3.3% (0.09)
−0.96;1.14
Lymphocytes (%) 39.2 ±1.5 37.8 ±1.9a
−4.2% (−0.25)
35.5 ±1.6 36.3 ±2.0
1.8% (0.11)
−5.9% (−0.37)
−0.96;0.22
Monocytes (%) 8.57 ±0.64 7.98 ±0.45a
−5.8% (−0.24)
7.02 ±0.46 7.10 ±0.41
1.6% (0.08)
−7.3% (−0.33)
−0.99;0.33
AHC, average hemoglobin concentration; APV, average platelet volume; CL, confidence limits; %d, in-group percentage difference between pre- and post-training; %D, percentage
difference between changes in IPC and PLA; DIE, distribute index of erythrocytes; ES, effect size; HIF-1α, hypoxia inducible factor-1α; MCHC, mean corpuscular hemoglobin content;
MCV, mean corpuscular volume; NO, nitric oxide; VEGF-α, vascular endothelial growth-factor.
aclear change within each group in post- compared to pre-training.
Differences between changes in IPC and PLA are indicated in bold. Values are mean ±SE.
that this effect on VO2kinetics could be responsible for the
observed TT performance improvement (Kilding et al., 2018).
This could also have been the case in our study considering
the increase in muscle O2extraction during the TT and the
change in the respiratory compensation point. Taken together,
these results suggested that the combination of IPC with SIT
could have enhanced exercise efficiency by improving aerobic
metabolism and could represent a perspective for subsequent
studies. Investigations on metabolism during exercise could help
answer some of the questions surrounding the effects of IPC
resulting in changes in muscle oxygenation that are visible
while exercising.
To date, most studies applying IPC chronically have reported
promising adaptations, though they have mainly been done
without exercise. Daily exposure to IPC for 7 days enhanced
artery endothelial function and cutaneous vascular conductance,
which persisted up to 1 week after the intervention (Jones
et al., 2014). One-week exposure also increased skeletal muscle
oxidative capacity (Jeffries et al., 2018). Longer application of
IPC for 8 weeks also improved endothelial function, and this
Frontiers in Sports and Active Living | www.frontiersin.org 12 April 2020 | Volume 2 | Article 41
Paradis-Deschênes et al. IPC Combined With SIT
TABLE 6 | Lipid-lipoprotein profile and glucose-insulin homeostasis after IPC and PLA at pre- and post-training.
IPC PLA 1IPC VS. 1PLA
PRE POST %d (ES) PRE POST %d (ES) %D (ES) CL
Lipid-lipoprotein profile
Total CHOL (mmol/L) 4.18 ±0.30 4.37 ±0.34
4.2% (0.15)
4.01 ±0.26 4.03 ±0.24
0.8% (0.04)
3.3% (0.14)
−0.18;0.45
Triglycerides (mmol/L) 0.900 ±0.209 0.997 ±0.200a
15.1% (0.22)
0.80 ±0.11 0.93 ±0.10a
19.3% (0.44)
−3.5% (−0.07)
−0.57;0.43
HDL-CHOL (mmol/L) 1.51 ±0.11 1.53 ±0.10
1.7% (0.07)
1.52 ±0.11 1.52 ±0.08
1.3% (0.06)
0.5% (0.02)
−0.43;0.47
LDL-CHOL (mmol/L) 2.25 ±0.28 2.38 ±0.28
7.5% (0.12)
2.12 ±0.20 2.08 ±0.19
−1.9% (0.06)
9.6% (0.20)
−0.08;0.49
FFA (mmol/L) 0.078 ±0.019 0.086 ±0.021
15.5% (0.15)
0.107 ±0.039 0.091 ±0.057a
−44.1% (−0.56)
106.5% (0.77)
0.26;1.27
Glucose-insulin homeostasis
Glucose (mmol/L) 4.98 ±0.09 5.05 ±0.09
1.3% (0.19)
4.84 ±0.12 5.13 ±0.12a
6.0% (0.74)
−4.5% (−0.31)
−0.59;−0.02
Insulin (pmol/L) 35.8 ±4.8 40.7 ±5.6a
14.3% (0.29)
30.7 ±2.7 32.7 ±1.7
9.4% (0.34)
4.5% (0.12)
−0.59;0.83
CHOL, cholesterol; CL, confidence limits; %d, in-group percentage difference between pre- and post-training; %D, percentage difference between changes in IPC and PLA; ES, effect
size; FFA, free fatty acids; HDL, high-density lipoprotein; LDL, low-density lipoprotein.
adenote clear change within each group in post- compared to pre-training.
Differences between changes in IPC and PLA are indicated in bold.
Values are mean ±SE.
enhancement lasted another 2 weeks (Jones et al., 2015). These
upregulated functions at rest might have taken place in the
present study and explained, at least in part, some of the changes
in [THb] and [HHb] during exercise. It has been suggested
that shear stress and local tissue hypoxia from IPC could up-
regulate HIF-1α, activate VEGF-αgene expression (Fukumura
et al., 2001; Albrecht et al., 2013; Heusch et al., 2015), and increase
levels of NO (Lochner et al., 2002). Our data do not reveal any
chronic changes to these markers after training with IPC. This
does not preclude their implication, as: (1) our methodology was
limited to one blood sample post-training, and (2) we may have
missed the window of transiently increased expression during
adaptation in the weeks between the start of the training program
and post-training blood sampling. For example, studies using
an identical training intervention to ours, but using blood-flow
restriction during the recovery periods after SIT, reported a
greater expression of muscle HIF-1α3 h after one session in
trained individuals (Taylor et al., 2016a), but no change in skeletal
muscle capillarity and mitochondrial protein content after a 4
week period (Mitchell et al., 2019). Another possibility is that
the frequency of the IPC procedure (2x/week) was insufficient to
induce molecular adaptations in these trained endurance athletes.
For example, Kimura et al. applied IPC six times per day for 1
month and reported an increase in NO production and VEGF
plasma concentration measured 14 h post IPC (Kimura et al.,
2007), and most of the studies on repeated IPC for cardiac surgery
applied IPC every day (Liang et al., 2015; Meng et al., 2015).
Thus, the optimal dose or protocol to maximize the hypoxic
and angiogenic signaling events following IPC remains unclear.
Taken together, these data suggest that the ergogenic effects
of IPC are mainly derived from transient functional changes
(probably related to an improved vascular control) rather than
structural modifications per se.
Finally, our results preclude a chronic role for a number
of circulating factors in contributing to improved performance
after repeated IPC application. Indeed, neither training with or
without IPC chronically modified blood markers of hypoxic and
angiogenic signaling or vasodilation, nor in factors related to
blood O2transport capacity measured 2 days post-training. The
absence of changes in lipid-lipoprotein profile, fasting glucose,
and insulin levels in athletes without dietary modification or
weight issues is not surprising. Others have suggested that the
immune system or inflammation could be of importance in
adaption following IPC (Thijssen et al., 2016). For example,
Czibik et al. reported that nuclear-factor-kappa B could be
responsible for modified gene regulation after IPC (Czibik
et al., 2008), and daily IPC for 10 days altered neutrophil
function and leukocyte inflammatory gene expression in humans
(Konstantinov et al., 2004; Shimizu et al., 2010). However, our
data show that the repetition of IPC two times per week had no
effect on immune system function, though we did not measure
markers of inflammation or transient response immediately
after training.
In conclusion, 4 weeks of bilateral IPC applied immediately
before SIT sessions elicited greater gains in time-trial
performance in endurance athletes than the same SIT
prescription without IPC. This was mainly associated with
enhanced local perfusion and muscle O2extraction, while
hematocrit, VO2max, and maximal aerobic power did not change.
Furthermore, the present intervention seems to be both safe and
sufficient to induce performance enhancements of interest to
trained individuals.
Frontiers in Sports and Active Living | www.frontiersin.org 13 April 2020 | Volume 2 | Article 41
Paradis-Deschênes et al. IPC Combined With SIT
DATA AVAILABILITY STATEMENT
All datasets generated for this study are included in the
article/supplementary material.
ETHICS STATEMENT
The studies involving human participants were
reviewed and approved by Ethic committee from
Laval University. The patients/participants provided
their written informed consent to participate in
this study.
AUTHOR CONTRIBUTIONS
PP-D, DJ, PM, and FB conceptualized and designed the research
project. PP-D acquired the data and conducted the statistical
analysis. PP-D interpreted results with assistance from DJ,
PM, and FB. PP-D wrote the manuscript with revisions from
DJ, PM, and FB. All authors reviewed and agreed upon the
final manuscript.
FUNDING
This work was supported by a research grant to FB, DJ,
and PM from the Foundation de l’Institut Universitaire
de Cardiologie et de Pneumologie de Québec and Ph.D.
scholarships from Laval University and the Foundation de
l’Institut Universitaire de Cardiologie et de Pneumologie de
Québec to PP-D.
ACKNOWLEDGMENTS
The authors thank the athletes for their participation in this
study. We also sincerely thank all graduate and undergraduate
students from our research group for their valuable help as well
as Michel Lacaille for his help in HIF-1α, VEGF- α, NO, and
FFA assays.
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Conflict of Interest: The authors declare that the research was conducted in the
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