Mean Platelet Volume (MPV) Predicts Middle Distance
Running Performance
Giuseppe Lippi1*, Gian Luca Salvagno2, Elisa Danese2, Spyros Skafidas3, Cantor Tarperi4,
Gian Cesare Guidi2, Federico Schena4
1 Laboratory of Clinical Chemistry and Hematology, Academic Hospital of Parma, Parma, Italy, 2 Laboratory of Clinical Biochemistry, Department of Life and Reproduction
Sciences, University of Verona, Verona, Italy, 3 CeRiSM (Centre for Mountain Sport and Health), Rovereto (TN), Italy, 4 Department of Neurological, Neuropsychological,
Morphological and Movement Sciences, University of Verona, Verona, Italy
Abstract
Background: Running economy and performance in middle distance running depend on several physiological factors,
which include anthropometric variables, functional characteristics, training volume and intensity. Since little information is
available about hematological predictors of middle distance running time, we investigated whether some hematological
parameters may be associated with middle distance running performance in a large sample of recreational runners.
Methods: The study population consisted in 43 amateur runners (15 females, 28 males; median age 47 years), who
successfully concluded a 21.1 km half-marathon at 75–85% of their maximal aerobic power (VO2max). Whole blood was
collected 10 min before the run started and immediately thereafter, and hematological testing was completed within
2 hours after sample collection.
Results: The values of lymphocytes and eosinophils exhibited a significant decrease compared to pre-run values, whereas
those of mean corpuscular volume (MCV), platelets, mean platelet volume (MPV), white blood cells (WBCs), neutrophils and
monocytes were significantly increased after the run. In univariate analysis, significant associations with running time were
found for pre-run values of hematocrit, hemoglobin, mean corpuscular hemoglobin (MCH), red blood cell distribution width
(RDW), MPV, reticulocyte hemoglobin concentration (RetCHR), and post-run values of MCH, RDW, MPV, monocytes and
RetCHR. In multivariate analysis, in which running time was entered as dependent variable whereas age, sex, blood lactate,
body mass index, VO2max, mean training regimen and the hematological parameters significantly associated with running
performance in univariate analysis were entered as independent variables, only MPV values before and after the trial
remained significantly associated with running time. After adjustment for platelet count, the MPV value before the run
(p = 0.042), but not thereafter (p = 0.247), remained significantly associated with running performance.
Conclusion: The significant association between baseline MPV and running time suggest that hyperactive platelets may
exert some pleiotropic effects on endurance performance.
Citation: Lippi G, Salvagno GL, Danese E, Skafidas S, Tarperi C, et al. (2014) Mean Platelet Volume (MPV) Predicts Middle Distance Running Performance. PLoS
ONE 9(11): e112892. doi:10.1371/journal.pone.0112892
Editor: Pedro Tauler, University of the Balearic Islands, Spain
Received August 19, 2014; Accepted October 16, 2014; Published November 11, 2014
Copyright:  2014 Lippi et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper.
Funding: The authors have no support or funding to report.
Competing Interests: The authors have declared that no competing interests exist.
* Email: glippi@ao.pr.it
Introduction
According to a recent on-line survey, recreational running is the
most popular leisure sport activity, followed by lifting weights,
biking, hiking and other outdoor activities [1]. More specifically,
75% of adults aged 24 to 44 years are engaged in outdoor running
activities at least once a week in the US [2]. The typical middle
distance runner is a ‘‘normal’’ trained adult subject, with few
previous experiences in competitive sport and without special
functional characteristics. The broad popularity of middle distance
is mostly attributable to a variety of reasons, which include no
need
of
special
talent
or
highly-specialized
and
expensive
equipment, and the remarkable benefits on health, fitness, stress
reduction and weight control [2]. It is also noteworthy that the
practice
of
habitual
running
has
been
associated
with
a
significantly reduced risk of obesity, hypertension, diabetes,
cardiovascular
disease,
cancer,
osteoporosis,
depression
and
several other chronic conditions, thus resulting in an overall
20% to 40% lower risk of mortality [3].
Both running economy and overall performance in middle
distance running depend on a number of physiological factors,
which are partially different from those required for short and long
distance running [4,5]. The published research on half-marathon
runners has mainly focused on a number of specific anthropo-
metric variables (i.e., midaxillary skinfold, body mass index,
percent body fat), functional characteristics (i.e., maximal aerobic
power [VO2max)], body core temperature), volume and intensity
in training [6–8]. Despite the well-established relationship existing
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between packed cell volume, VO2max, aerobic performance and
maximal exercise capacity [9–11], a fact that has also contributed
to the increase use of blood doping in sports during the past
decades [12], there is little information about the association
between hematological variables and middle distance running
performance. As such, the aim of this study was to investigate
whether some hematological parameters may predict half-mara-
thon running time in a large sample of recreational runners.
Materials and Methods
The study was performed during a specific event called ‘‘Run
For Science’’, held in Verona (Italy) in April 2014, with the
purpose of analyzing the normal response of adult person to
middle distance running. Forty three amateur runners were
recruited (15 females and 28 males; median age 47 years and IQR
42–50 years; median body mass index 23 kg/m2 and IQR, 22–
25 kg/m2), who successfully concluded a 21.1 km half-marathon
at 75–85% of their VO2max. All athletes were members of a non
professional
team,
were habitually
involved
in recreational
running (mean training regimen 222 min/week and IQR 191–
253 min/week; maximal oxygen uptake 50 mL/kg/min and IQR
46–55 mL/kg/min), and had rested for not less than 36 hours
before the trial. Maximal aerobic capacity was individually
measured in the last two weeks before the event by a running
test on a treadmill using a breath by breath ergospirometric system
(Quark B2, Cosmed Italy). After appropriate familiarization, each
runner underwent a progressive incremental test, starting from
habitual running pace and increasing speed of 0.5 km/h every
min till reaching the volitional exhaustion. None of the subjects
were taking medications known to alter erythrocyte or platelet
metabolism, including antiplatelet or antihypertensive drugs and
erythropoiesis stimulating substances. The trial started at 9.30 AM
and the 21.1 km distance was covered on a relatively flat route
near Verona (35 m vertical gain, with maximal slope of 1.8%), in a
partially sunny day with temperatures between 12–19uC and
humidity between 55–75%. Participants were free to drink ad
libitum during the run. Blood was drawn in primary blood tubes
containing K2EDTA (Terumo Europe N.V., Leuven, Belgium)
10 min before the start of the run and immediately thereafter (i.e.,
within 15 min after conclusion). The whole blood samples were
immediately transported to the local laboratory under controlled
conditions of temperature and humidity, where a complete blood
cell count (CBC) was performed on Advia 2120 (Siemens
Healthcare Diagnostics, Tarrytown NY, USA), which included
measurement of hematocrit, hemoglobin, red blood cell (RBC)
count, mean corpuscular volume (MCV), mean corpuscular
hemoglobin (MCH), mean corpuscular hemoglobin concentration
(MCHC), RBC distribution width (RDW), platelet count, mean
platelet volume (MPV), white blood cell (WBC) count and
differential,
reticulocyte
count
and
reticulocyte
hemoglobin
concentration (RetCHR). The analysis of blood specimens was
concluded within 2 hours after sample collection and all results
were finally expressed as median and interquartile range (IQR).
Differences of pre-run and post-run values were analyzed with
Wilcoxon’s test for paired samples. Univariate (i.e., Spearman’s
correlation) and multivariate analysis (with adjustment for age, sex,
blood lactate, body mass index, VO2max, mean training regimen
and CBC parameters significantly associated with running time in
univariate correlation) were performed, in order to identify
potential predictors of running performance. The statistical
analysis was performed with Analyse-it (Analyse-it Software Ltd,
Leeds, UK) for Microsoft Excel (Microsoft Corporation, Red-
mond, WA, USA). All subjects gave a written consent for being
enrolled in this investigation. The study was approved by the local
ethical committee (Department of Neurological, Neuropsycholog-
ical, Morphological and Movement Sciences, University of
Verona) and performed in accord with the Helsinki Declaration
of 1975 (additional information can be downloaded from the
institutional Website: http://www.dsnm.univr.it/?ent=iniziativa&
id=5382, Last accessed, 10 October 2014).
Results
The 43 amateur runners completed the run in a median time of
113 min (IQR, 105–121 min). As predictable, the median running
performance of the 28 male athletes (100 min and IQR 101–
118 min) was significantly better than that of the 15 females
athletes (120 min and IQR 113–123 min; p,0.001). The median
body weight decreased by 2.2% after the run (from 73.1 to
71.5 kg; p,0.001). The median lactate value measured in
capillary blood at the end of the run was 4.0 mmol/L (IQR,
3.0–4.9 mmol/L). The variation of the CBC parameters after the
run is shown in table 1. The values of lymphocytes and eosinophils
exhibited a significant decrease compared to pre-run values,
whereas those of MCV, platelets, MPV, WBC, neutrophils and
monocytes were found to be significantly increased after the run.
In univariate analysis, significant predictors of finishing time were
the pre-run values of hematocrit, hemoglobin, MCH, RDW,
MPV, RetCHR, whereas the post-run values of MCH, RDW,
MPV, monocytes and RetCHR were also associated with running
performance (Table 2). The VO2max was the best overall
predictor of running time (r = 20.601; p,0.001), whereas neither
body mass index or blood lactate at the end of the half-marathon
were significantly associated with running performance (Table 2).
In multivariate analysis, in which running time was entered as
dependent variable whereas age, sex, blood lactate, body mass
index, VO2max, mean training regimen and the CBC parameters
significantly associated with running performance in univariate
analysis were entered as independent variables, only MPV values
before and after the trial remained significantly associated with
running time (Table 3). After adjustment for the platelet count, the
MPV value before the run (p = 0.042), but not thereafter
(p = 0.247), remained significantly associated with running perfor-
mance (Fig. 1). Neither the platelet count (r = 20.210; p = 0.303)
or the MPV (r = 0.039; p = 0.851) were significantly associated
with VO2max in univariate analysis.
Discussion
Due to the increasing popularity of recreational running as a
form of leisure activity and health-promoting behavior, a large
number of studies have been performed over the past decades to
identify the most reliable predictors of running economy and
performance. The large majority of these investigations focused on
anthropometric variables, functional characteristics, as well as
volume and intensity of training [13]. With the notable exception
of hemoglobin and packed cell volume, little information is
available on other hematological parameters that may predict
middle distance running performance [14]. This investigation was
hence specifically planned to establish whether some hematolog-
ical parameters comprised within the CBC may be significantly
associated with half-marathon running time.
The leukocytes variations recorded in this study are not new,
since an increase of total leukocyte, neutrophil and monocyte
counts along with a decrease of lymphocyte and eosinophils values
have already been reported in a number of previous investigations,
and are prevalently attributable to the well-documented release of
catecholamines and cortisol during exercise [8,15,16].
Mean Platelet Volume Predicts Running Performance
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The significant increase of both platelet count (median increase,
17%; IQR, 10–34%) and MPV (median increase, 6%; IQR, 1–
9%) recorded immediately after the half-marathon run substan-
tially exceeded the inter-individual biological variation of these
parameters (platelet count, 9.1%; MPV, 4.3%) [17], and is also
consistent with the well established evidence that aerobic physical
activity is effective to enhance circulating activated platelets, as
well as platelet-platelet and platelet-leukocyte aggregates [18–22].
More specifically, it has been recently demonstrated that the
hyperactive platelets generated during exercise are rapidly cleared
by the spleen, which is also a dynamic reservoir of younger and
larger platelets (i.e., the human spleen retains one-third of total
body platelets, with MPV approximately 20% greater than that of
circulating platelets) [23]. The younger platelets are then released
into the circulation, thus explaining the significant increase of
platelet count and MPV observed after endurance exercise in this
and other previous studies [18–22]. Another putative mechanism
that may contribute to increase the MPV has been reported by
Hilberg et al. [24], who observed that moderate exercise increased
both platelet reactivity and platelet-leukocyte conjugate formation,
which both contribute to increase the measured value of MPV.
Regardless of the underlying mechanism(s), the significant increase
of MPV recorded after exercise in this and other studies [18–22]
has meaningful clinical implications, suggesting that the enhanced
risk of cardiovascular events that is occasionally observed in
athletes may be at least in part mediated by platelet hyper-
reactivity [20]. Indeed, further studies are advisable to define
whether an improvement of physical fitness is also accompanied
with an increased MPV.
Interestingly, although the pre-run values of hematocrit,
hemoglobin, MCH, RDW, MPV, RetCHR, along with the
post-run values of MCH, RDW, MPV, monocytes and RetCHR
were significantly associated with running time in univariate
analysis, only the MPV values before and after the half-marathon
remained significantly correlated with running performance in the
fully-adjusted model. As predictable, both hemoglobin and
hematocrit values were found to be positively correlated with
running performance in univariate analysis, but the significance of
these associations was lost in the fully adjusted model, especially
when VO2max was entered as covariate. This is plausible, since
VO2max and both hemoglobin and hematocrit clearly interplay in
increasing sport performance, and VO2max is in fact enhanced by
approximately 1% for each 3 g/L increase of hemoglobin [25].
As such, this is the first study demonstrating a direct correlation
between platelet size and endurance performance to the best of
our knowledge. It is noteworthy that the inverse association
between pre-run MPV value and half-marathon running time
remained significant after adjustment for a number of factors such
as age, sex, blood lactate, body mass index, VO2max, mean
training regimen and platelet count, thus confirming the existence
of an effective interplay between platelet metabolism and aerobic
performance. In univariate analysis, the correlation between
running time and pre-run MPV value was the second highest
overall, only preceded by that between running time and VO2max
(Table 2). In agreement with a previous study [26], neither the
platelet count or the MPV at baseline were significantly associated
with VO2max, thus confirming that the influence of MPV on
running performance may be virtually independent from the
baseline cardiorespiratory fitness level.
An increased platelet volume is a well established surrogate
marker of platelet activation, wherein large platelets are reportedly
more active than small platelets [27–29]. The association of this
evidence with our data would imply that platelet hyperactivity may
be a significant determinant of performance in medium distance
running. The use of platelets in sports medicine has risen sharply
in recent times. The platelet-rich plasma (PRP), an autologous
blood fraction rich in platelets and associated cytokines and
growth factors, is mainly used for treatment of sports related
Table 1. Variation of the complete blood cell count after a 21.1 km half-marathon run in 43 amateur runners.
Pre-run
Post-run
P
Hematocrit
0.45 (0.44–0.47)
0.45 (0.43–0.47)
0.420
Hemoglobin (g/L)
148 (140–155)
148 (138–155)
0.137
RBC (1012/L)
4.8 (4.6–5.0)
4.8 (4.5–5.1)
0.162
MCV (fL)
94 (91–96)
95 (92–97)
0.004
MCH (pg)
31 (30–32)
31 (30–32)
0.400
MCHC (g/dL)
32.7 (32.4–33.2)
32.5 (3.19–3.32)
0.068
RDW (%)
13.4 (13.1–13.5)
13.5 (13.1–13.6)
0.001
Platelets (109/L)
260 (218–299)
321 (287–361)
,0.001
MPV (fL)
9.2 (8.6–9.8)
9.5 (8.9–10.1)
,0.001
WBC (109/L)
5.6 (4.9–6.4)
12.4 (9.8–13.9)
,0.001
Neutrophils (109/L)
3.1 (2.5–3.6)
9.3 (7.4–11.5)
,0.001
Lymphocytes (109/L)
2.0 (1.7–2.3)
1.8 (1.5–2.2)
0.037
Monocytes (109/L)
0.3 (0.2–0.4)
0.5 (0.4–0.6)
,0.001
Eosinophils (109/L)
0.2 (0.1–0.2)
0.1 (0.0–0.01)
,0.001
Basophils (109/L)
0.1 (0.1–0.1)
0.1 (0.0–0.1)
0.052
LUC (109/L)
0.01 (0.1–0.1)
0.01 (0.1–0.1)
0.063
Reticulocytes (109/L)
62 (54–74)
60 (52–73)
0.138
RetCHR (pg)
31 (31–32)
31 (31–32)
0.243
RBC, red blood cell; MCV, mean corpuscular volume; MCH, mean corpuscular hemoglobin (MCH); MCHC, mean corpuscular hemoglobin concentration; (MCHC); RDW,
red blood cell distribution width; MPV, mean platelet volume (MPV); WBC, white blood cell; LUC, large unstained cells; RetCHR, reticulocyte hemoglobin concentration.
doi:10.1371/journal.pone.0112892.t001
Mean Platelet Volume Predicts Running Performance
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injuries [30–32]. It was recently proven that injection of PRP may
also exert some ergogenic effects. In particular, Wasterlain et al.
studied the effect of PRP injection on variation of performance-
enhancing systemic growth factors in 25 patients [33], and
observed that the administration of PRP increased the concentra-
tion of insulin-like growth factor-1 (IGF-1), basic fibroblast growth
factor (bFGF) and VEGF. Interestingly, Kasuya et al. also showed
that a symptom-limited treadmill exercise test was effective to
enhance the platelet release of nitric oxide (NO) [34], which would
then contribute to raise exercise tolerance and performance [35].
Another mechanism by which platelets may contribute to
enhance sport performance is the attenuation of neuropathic pain
and/or fatigue during exercise [36]. Kennedy et al. studied platelet
activation and function in 17 patients with chronic fatigue
Table 2. Univariate correlation (r) analysis between running performance and parameters of the complete blood cell count in 43
amateur athletes who completed a 21.1 km half-marathon run.
Pre-run value
Post-run value
r
p
r
p
Hematocrit
20.329
0.031
20.298
0.052
Hemoglobin
20.388
0.010
20.291
0.059
RBC
20.074
0.635
20.086
0.584
MCV
20.234
0.131
20.257
0.097
MCH
20.306
0.046
20.341
0.025
MCHC
20.240
0.122
20.199
0.200
RDW
0.316
0.039
0.336
0.027
Platelets
0.300
0.052
0.256
0.097
MPV
20.450
0.002
20.476
0.001
WBC
20.208
0.181
0.248
0.109
Neutrophils
20.142
0.365
0.262
0.090
Lymphocytes
20.072
0.647
20.028
0.861
Monocytes
20.262
0.090
0.361
0.017
Eosinophils
20.143
0.360
20.258
0.095
Basophils
20.096
0.538
20.197
0.207
LUC
20.039
0.805
0.185
0.234
Ret
0.290
0.059
0.208
0.181
RetCHR
20.390
0.001
20.379
0.012
Blood lactate
2
2
20.069
0.663
Body mass index
0.092
0.555
-
-
VO2max (mL/min/Kg)
20.601
0.001
-
-
RBC, red blood cell; MCV, mean corpuscular volume; MCH, mean corpuscular hemoglobin (MCH); MCHC, mean corpuscular hemoglobin concentration; (MCHC); RDW,
red blood cell distribution width; MPV, mean platelet volume (MPV); WBC, white blood cell; LUC, large unstained cells; RetCHR, reticulocyte hemoglobin concentration;
VO2max, maximal aerobic power.
doi:10.1371/journal.pone.0112892.t002
Table 3. Multivariate correlation analysis between running performance and parameters of the complete blood cell count in 43
amateur athletes who completed a 21.1 km half-marathon run.
Pre-run value
Post-run value
p
p
Hematocrit
0.338
-
Hemoglobin
0.216
-
MCH
0.512
0.567
RDW
0.272
0.216
MPV
0.042
0.026
Monocytes
-
0.080
RetCHR
0.967
0.925
Results were also adjusted for age, sex, body mass index, post-run blood lactate, maximal aerobic power (VO2max) and training regimen.
MCH, mean corpuscular hemoglobin (MCH); RDW, red blood cell distribution width; MPV, mean platelet volume (MPV); RetCHR, reticulocyte hemoglobin concentration.
doi:10.1371/journal.pone.0112892.t003
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syndrome and 16 healthy controls [37], reporting that patients
displayed lower platelet aggregability and reduced MPV. This
would be consistent with the fact that smaller and less active
platelets may somehow increase the fatigue threshold, thus
conditioning exercise output. A series of studies also demonstrated
that platelet gel or autologous platelet tissue graft are effective to
lower pain after surgery and are associated with less pain
medications and broader range of motion prior to discharge
[38–40]. As specifically regards sports, the use of PRP was proven
to
be
effective
in
reducing
pain
and
promoting
function
improvement in tennis elbow [41] and other painful tendinopa-
thies [42], as well as for accelerating muscle recovery after acute
injury [43].
According to these evidences, it seems hence plausible that
hyperactive platelets may exert some pleiotropic effects on
endurance
sport
performance,
by
both
releasing
ergogenic
mediators as well as by triggering an increase in performance-
enhancing substances such as NO into the circulation. Further
studies, involving also different running distances, sports and
different categories of athletes are needed to confirm these findings
and to elucidate the potential underlining mechanisms linking
platelet volume and aerobic performance.
Author Contributions
Conceived and designed the experiments: GL CT FS. Performed the
experiments: GLS ED SS. Analyzed the data: GL GLS GCG FS. Wrote
the paper: GL GCG FS.
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Mean Platelet Volume Predicts Running Performance
PLOS ONE | www.plosone.org
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November 2014 | Volume 9 | Issue 11 | e112892

Mean platelet volume (MPV) predicts middle distance running performance.
Lippi, Giuseppe,Salvagno, Gian Luca,Danese, Elisa,Skafidas, Spyros,Tarperi, Cantor,Guidi, Gian Cesare,Schena, Federico