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Sex-specific physiological responses to ultramarathon
Nicholas B. Tiller1, Courtney M. Wheatley-Guy2, Caitlin C. Fermoyle3,4, Paul Robach5, Briana Ziegler3,
Alice Gavet5, Jesse C. Schwartz2, Bryan J. Taylor6, Keren Constantini7, Robert Murdock8, Bruce D.
Johnson3, Glenn M. Stewart3,9.
1Institute of Respiratory Medicine and Exercise Physiology, Lundquist Institute for Biomedical
Innovation at Harbor-UCLA Medical Center, Torrance CA, USA.
2Department of Cardiovascular Diseases, Mayo Clinic, Scottsdale, AZ, USA
3Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
4Division of Geriatrics, Department of Internal Medicine, University of Utah, Salt Lake City, UT, USA
5Ecole Nationale des Sports de Montagne, Chamonix, FR.
6Department of Cardiovascular Diseases, Mayo Clinic, Jacksonville, FL, USA
7School of public health, Sackler Faculty of Medicine, and Sylvan Adams Sports Institute, Tel-Aviv
University, IL.
8Mercy Medical Center, Mason City, IA, USA.
9Menzies Health Institute Queensland, Griffith University, Brisbane, AUS
Correspondence: Nicholas B. Tiller, Ph.D. | 1124 W. Carson Street, CDCRC Building, Torrance, CA
90502 | Email: nicholas.tiller@lundquist.org | Tel: (+1) 310-980-8163 | Orchid: https://orcid.org/0000-
0001-8429-658X
ABSTRACT
1
Purpose. Despite a growing body of literature on the physiological responses to ultramarathon, there is a
2
paucity of data in females. This study assessed the female physiological response to ultramarathon and
3
compared the frequency of perturbations to a group of race- and time-matched males. Methods. Data were
4
collected from 53 contestants of an ultramarathon trail race at 2018/19 Ultra Trail du Mont-Blanc
5
(UTMB®). Before and within 2-h of the finish, participants underwent physiological assessments including
6
blood sampling for biomarkers (creatine kinase-MB isoenzyme, CK-MB; cardiac troponin I, cTnI; brain
7
natriuretic peptide, BNP, creatinine, Cr); pulmonary function testing (spirometry, exhaled NO, diffusing
8
capacities, mouth pressures); and transthoracic ultrasound (lung comet tails, cardiac function). Data from
9
eight female finishers (age=36.6±6.9 y; finish time=30:57±11:36 hh:mm) were compared to a group of
10
eight time-matched males (age=40.3±8.3 y; finish time=30:46±10:32 hh:mm). Results. Females exhibited
11
significant pre- to post-race increases in BNP (25.8±14.6 vs. 140.9±102.7 pg/mL; p=0.007) and CK-MB
12
(3.3±2.4 vs. 74.6±49.6 IU/L; p=0.005), whereas males exhibited significant pre- to post-race increases in
13
BNP (26.6±17.5 vs. 96.4±51.9 pg/mL; p=0.002), CK-MB (7.2±3.9 vs. 108.8±37.4 IU/L; p=0.002), and Cr
14
(1.06±0.19 vs. 1.23±0.24 mg/dL; p=0.028). Lung function declined in both groups, but males exhibited
15
additional reductions in lung diffusing capacities (DLCO=34.4±5.7 vs. 29.2±6.9 mL/min/mmHg, p=0.004;
16
DLNO=179.1±26.2 vs. 152.8±33.4 mL/min/mmHg, p=0.002) and pulmonary capillary blood volumes
17
(77.4±16.7 vs. 57.3±16.1 mL; p=0.002). Males, but not females, exhibited evidence of mild post-race
18
pulmonary edema. Pooled effect sizes for within-group pre- to post-race changes, for all variables, were
19
generally larger in males versus females (d = 0.86 vs. 0.63). Conclusions. Ultramarathon negatively
20
impacts a range of physiological functions but generally evokes more frequent perturbations, with larger
21
effect sizes, in males compared to females with similar race performances.
22
23
Key words: cardiovascular; female; male; pulmonary; respiratory; sex-differences; ultra-endurance
24
INTRODUCTION
25
Ultramarathons are footraces that typically range from ~30 miles (~50 km) to ~150 miles (~240 km) in a
26
single stage and considerably further in multi-stage events. Participation evokes extreme physiological
27
strain on multiple body systems (1), particularly the cardiovascular and respiratory systems (2). For
28
instance, studies show decreased left ventricular function and increased cardiac biomarkers following
29
ultramarathon (3, 4), in addition to lung function derangements of 10–15% with or without evidence of
30
airway obstruction (5). Moreover, while most physiological perturbations are transient and generally
31
recover to baseline within a week, there is the potential for long-term maladaptations and associated health
32
issues (6). For these reasons, there is now a greater emphasis on understanding the acute and chronic
33
physiological and pathophysiological responses to ultramarathon running (1, 2, 6, 7).
34
Despite the growing body of work, there is a paucity of data in female athletes. A recent review on
35
pulmonary responses to marathon and ultramarathon running collated 15 studies with a cumulative 232
36
participants of which only 19 (8%) were female (5). This number is considerably below the estimated ~20%
37
of female ultramarathon contestants (8–10) and supports the notion that females may be underrepresented
38
in exercise science research (11). Potential explanations may be a researcher bias that favours males as
39
recruitment participants (12), but also a possible volunteer bias which has males more willing to participate
40
in exercise-related research (13). Nevertheless, anatomical and physiological differences between males
41
and females can influence the exercise response (14–17), and failure to consider these differences may limit
42
the specificity of training programs and negatively impact efforts at promoting competitive longevity.
43
The issue of sex-based physiological predisposition to ultramarathon has also been a topic of recent
44
discussion (10). Indeed, a number of exceptional, record-breaking performances by female athletes in
45
ultramarathon in recent years has roused speculation that they might be predisposed to success in such
46
events. The male-to-female performance gap in regular endurance sports like marathon is ~10% (18), but
47
studies have calculated the performance gap in ultramarathon to be as low as 4% (19). In some instances,
48
female performances may surpass those of their male counterparts (20). Additionally, in ultramarathon,
49
there are distinct performance predictors for males (e.g., age, BMI, years of running) and females (e.g.,
50
weekly running mileage and half-marathon record) (9). Thus, while the question of whether females are
51
physiologically predisposed to ultramarathon has not been directly explored, an ability to better tolerate the
52
physiological stress of racing is likely ergogenic in ultramarathon and may also lead to better long-term
53
health management.
54
Accordingly, there were two aims of this exploratory study. The first was to provide novel data on
55
the physiological responses of females to an ultramarathon trail race, with specific emphasis on respiratory
56
and cardiopulmonary function. The second was to explore sex differences in the frequency of pre- to post-
57
race physiological perturbations in males and females matched for ultramarathon finish time.
58
59
METHODS
60
Race Characteristics
61
Data were collected from runners competing in one-of-two races at the annual Ultra Trail du Mont-Blanc
62
(UTMB®) trail running series in 2018 or 2019. The UTMB® (106 miles/171 km, ~10,000 m ascent) and
63
the CCC® (63 miles/101 km, ~6,000 m ascent) are single-stage, mountainous trail races commencing in
64
Chamonix, France and Courmayeur, Italy, respectively. Both races require intermittent bouts of traversal
65
at altitudes ≥ 2,500 m (Fig. 1) and, in the years during which data collection took place, temperature and
66
humidity ranged from -6 to 28°C/35 to 75% (2018) and 6 to 29°C/35 to 70% (2019). Temperature extremes
67
were mediated largely by altitude.
68
69
Ethical Approval and Participants
70
Ethical approval was granted first by the Mayo Clinic Institutional Review Board (IRB# 17-003843) and
71
then by the Comité de Protection des Personnes Sud-Ouest et Outre-Mer 2 (IRB# 2-18-43-2). Thereafter,
72
runners were contacted by the UTMB® organizers who distributed details of the study via electronic
73
recruitment posters. After providing written, informed consent, data were collected from 53 runners of
74
which 10 (19%) were female. One female runner retired early from the race, and another did not return for
75
post-race assessments; thus, eight female finishers remained (CCC®, n=4; UTMB®, n=4;). A subgroup of
76
eight male runners from the same races (CCC®, n=4; UTMB®, n=4;), whose finish times most closely
77
matched the female group mean, were selected as a comparison (Table 1). Runners completed a medical
78
questionnaire and declared that they were free from known cardiorespiratory illnesses. All testing was
79
conducted in accordance with the declaration of Helsinki.
80
81
Study Design
82
Participants attended the laboratory (based near the start/finish line at 1,035 m) in the week preceding the
83
race to complete baseline testing which was organized into three phases (Fig. 2). Initial measures included
84
vital signs (heart rate, systolic and diastolic blood pressure [SBP/DBP], electrocardiogram [ECG]), basic
85
anthropometry (stature and mass), and venous blood sampling for electrolytes, biomarkers, haemoglobin
86
concentration, and haematocrit. Next, participants completed pulmonary function tests (PFTs) including
87
spirometry, forced oscillation, and exhaled nitric oxide, followed by an assessment of respiratory muscle
88
strength. Lastly, resting lung diffusing capacity was assessed followed by transthoracic ultrasound for
89
cardiac morphology and lung comet tails. All physiological measures were repeated as soon as possible
90
following race completion (mean ± SD, 1 h 41 min ± 54 min).
91
92
Blood sampling
93
Venous blood samples (~8 mL) were collected via venepuncture and analysed using a commercially
94
available, hand-held immunoassay device and cartridges (i-STAT Corporation, New Jersey, USA).
95
Measures included haemoglobin (Hb), haematocrit (Hct), electrolytes (sodium, Na2+; potassium, K+;
96
chloride, Cl-), and biochemical markers relating to cardiac (troponin I, cTnI; brain natriuretic peptide, BNP),
97
renal (creatinine, Cr), and skeletal muscle function (creatine kinase-MB, CK-MB). Plasma volume was
98
calculated from Hct and Hb using the Dill and Costill equation (21).
99
100
Pulmonary and respiratory muscle function
101
Pulmonary volumes (forced expiratory volume in 1-second, FEV1; forced inspiratory volume in 1-second,
102
FIV1), capacities (forced vital capacity, FVC; inspiratory capacity, IC), and flows (peak expiratory flow,
103
PEF; forced expiratory flow between 25 and 75% of FVC, FEF25-75) were assessed using a portable
104
spirometer (Breeze Suite 8.5 and CPFS/D USB™, Medgraphics Corporation, Minnesota, USA) during a
105
minimum of three and a maximum of eight forced expiratory manoeuvres (22). Airway resistance at 5 and
106
19 Hz (R5 and R19) were assessed via forced oscillometry (Resmon Pro V3; MGC Diagnostics, Minnesota,
107
USA) during which participants were seated, had the nose occluded, and were asked to maintain tidal
108
breathing while their cheeks were held firmly by an investigator (23). As a marker of airway inflammation,
109
fractional exhaled nitric oxide (FeNO) was measured using a handheld device (Aerocrine Nixo Vero®
110
510(k), Solna, Sweden, used in 2018; NObreath; Bedfont, Rochester, UK, used in 2019) (24). Lung
111
diffusing capacity for carbon monoxide (DLCO) and nitric oxide (DLNO) were assessed simultaneously via
112
the single-breath technique using a 4-s breath-hold (Hyp’air Compact system with Exp’air software, version
113
1.31.05, Medisoft, Dinant, Belgium). Each resting measure was separated by 4 min and performed in
114
duplicate (25). Moreover, DLCO was expressed in absolute terms, expressed relative to alveolar volume
115
(DLCO/VA), and corrected to reference hemoglobin concentrations (DLCO,HbCorr) according to the Cotes et
116
al. equation (25, 26). Following the assessment of DLCO and DLNO, alveolar-capillary membrane
117
conductance (DMCO) and pulmonary capillary blood volume (VC) were calculated using equations
118
described by Pavelescu et al. (27). Finally, maximum static inspiratory pressure (PIMAX) from residual
119
volume and maximum static expiratory pressure (PEMAX) from total lung capacity (28) were measured using
120
a handheld device (MicroRPM, CareFusion, San Diego, USA). All pulmonary and respiratory muscle
121
function tests were performed in accordance with recommended standards (22–25, 27, 28).
122
123
Transthoracic ultrasound
124
Comet tails. As a measure of extravascular lung water (pulmonary oedema), the number of
125
ultrasound lung comets was determined via transthoracic sonography (Philips CX50 and S5-1 transducer,
126
Philips Healthcare, Netherlands), as previously described (29, 30). Briefly, participants lay supine while
127
the sonographer sequentially examined 28 intercostal lung fields located at the parasternal, midclavicular,
128
anterior axillary and mid-axillary lines from the second to the fourth intercostal space (left side) and from
129
the second to the fifth intercostal space (right side). A comet was defined as an echogenic, coherent, wedge-
130
shaped signal that originated from the hyperechoic pleural line and extended to the edge of the screen. The
131
presence of an ultrasound lung comet was simultaneously verified by two trained operators. In accordance
132
with Picano et al. (31), we employed a semi-quantitative classification for the presence of extravascular
133
lung water, whereby a total lung comet tail count of < 5 was considered “normal”; 5 - 15 was mild
134
extravascular lung water accumulation; 15 - 30 was moderate extravascular lung water accumulation; and
135
> 30 was severe extravascular lung water accumulation (31).
136
Echocardiography. All images were acquired while the participant was supine and orientated in
137
the left-lateral decubitus position following 10-min rest. Two-dimensional (2-D) and pulsed-wave tissue
138
Doppler echocardiography were performed using ultrasound (Philips CX50 and S5-1 transducer, Philips
139
Healthcare, Netherlands). Images were acquired by an experienced cardiac sonographer in accordance with
140
the guidelines published by the American Society of Echocardiography (32). Echocardiograph data were
141
analysed offline by the same assessor using commercially available software (Q-Lab 13, Philips Healthcare,
142
Netherlands). Measures included cardiac frequency (fC), stroke volume (SV) determined via the Doppler
143
velocity time integral (DVTI) method, and cardiac output (Q
) determined by the product of fC and SV (32).
144
145
Statistics
146
Statistical analyses were performed using IBM SPSS Statistics v24 (IBM; Illinois, USA). Normality of
147
distribution was assessed using the Shapiro Wilk test, and data that were not normally distributed were log
148
transformed. Independent samples t-tests were used to assess for sex differences in age, race time, velocity,
149
and physiological variables at baseline, with the Welch statistic applied in cases when homogeneity of
150
variance (Levine's test) was violated. Paired samples t-tests were used to assess the female (within-group,
151
n=8) pre- to post-race response, the male (within-group, n=8) pre- to post-race response, and the overall
152
pre- to post-race response (n=16). For differences testing, the Benjamini-Hochberg method was used to
153
adjust the p-value for the false discovery rate associated with multiple comparisons. The magnitude of the
154
difference between group means was assessed using Cohen's d (0.2 = small; 0.5 = medium; 0.8 = large;
155
(33)). Alpha level was 0.05, and descriptive values are reported as mean ± SD (unless stated).
156
157
RESULTS
158
Baseline variables
159
Participant demographics and race data are shown in Table 1. There was no difference in age between
160
females and males (p = 0.361), but males were taller (p = 0.003) and heavier (p = 0.004). Per study design,
161
there were no between-group differences in average finish time (p = 0.975) or running velocity (p = 0.762).
162
Baseline physiological variables are shown in Table 2. Males exhibited greater baseline values for SBP,
163
Na2+, Hct, PV, Cr, CK-MB, FVC, FEV1, PEF, FIV1, DLCO, DLCO,HbCorr, DLNO, VC, PIMAX, and PEmax. There
164
were no baseline between-group differences in fC, DBP, K+, Cl-, Hb, cTnI, BNP, FEV1/FVC, FEF25-75, IC,
165
R5, R5-R19, FeNO, DLCO/VA, DMCO, frequency of lung comet tails, SV, or Q
.
166
167
Physiological responses to ultramarathon
168
Participants returned for post-race assessments 1 h 41 min ± 54 min after finishing the event, with no
169
difference between the sexes (1 h 44 min ± 54 min vs. 1 h 38 min ± 57 min, p = 0.846, d = 0.11). All within-
170
group pre- to post-race data (means, standard deviations, p-values, and effect sizes) are shown in the
171
supplementary table.
172
Vital signs (fC, SBP, and DBP). Paired-samples t-tests revealed a significant overall effect of
173
ultramarathon on fC (p = 0.004, d = 1.26) and SBP (p = 0.010, d = 0.88). There was no overall effect on
174
DBP (p = 0.290, d = 0.45). The within-group analysis showed that females exhibited significant pre- to
175
post-race increases in fC, while males exhibited significant pre- to post-race decreases in SBP
176
(supplementary table).
177
Blood sampling. Paired-samples t-tests revealed a significant overall effect of ultramarathon on Hb
178
(p = 0.032, p = 0.77), Hct (p = 0.036, d = 0.76), PV (p = 0.020, d = 0.82), cTn1 (p = 0.016, d = 1.11), BNP
179
(p = 0.004, d = 1.57), Cr (p = 0.028, d = 0.39), and CK-MB (p = 0.004, d = 2.65). There was no overall
180
effect on Na2+ (p = 0.566, d = 0.31) - with no evidence of hyponatremia in any athlete - and no overall effect
181
on K+ (p = 0.236, d = 0.77) or Cl- (p = 0.282, d = 0.40). The within-group analysis showed that females
182
exhibited significant pre- to post-race increases in BNP and CK-MB, while males exhibited significant pre-
183
to post-race increases in BNP, CK-MB, Cr, and PV (Fig. 3; supplementary table).
184
Pulmonary and respiratory muscle function. Paired-samples t-tests revealed a significant overall
185
effect of ultramarathon on FVC (p = 0.044, d = 0.36), FEV1 (p = 0.027, d = 0.36), PEF (p = 0.016, d =
186
0.37), IC (p = 0.004, d = 0.95), FeNO (p = 0.004, d = 0.72), DLCO (p = 0.005, d = 0.51), DLNO (p = 0.004, d
187
= 0.52), VC (p = 0.004, d = 0.88), and PIMAX (p = 0.010, d = 0.56). There was no overall effect on FEV1/FVC
188
(p = 1.000, d = 0.11), FEF25-75 (p = 0.412, d = 0.32), FIV1 (p = 0.264, d = 0.38), R5 (p = 0.472, d = 0.27),
189
R5-R19 (p = 0.182, d = 0.45), DLCO,HbCorr (p = 0.061, d = 0.32), DLCO/VA (p = 1.000, d = 0.08), DMCO (p =
190
0.825, d = 0.22), or PEMAX (p = 0.096, d = 0.38). The within-group analysis showed that females exhibited
191
significant pre- to post-race decreases in FVC, PEF, IC, FeNO, and PIMAX, while males exhibited significant
192
pre- to post-race decreases in PEF, IC, FeNO, DLCO, DLNO, and VC (Fig. 4; supplementary table).
193
Transthoracic ultrasound. Paired-samples t-tests revealed a significant overall effect of
194
ultramarathon on lung comet tails (p = 0.004, d = 1.31) and Q
(p = 0.020, d = 0.75). There was no overall
195
effect on SV (p = 0.234, d = 0.36). The within-group analysis showed that females exhibited significant
196
pre- to post-race increases in lung comet tails and Q
, while males exhibited significant pre- to post-race
197
increases in lung comet tails (supplementary table).
198
199
DISCUSSION
200
The aims of this study were to provide novel data on the physiological responses of females to an
201
ultramarathon trail race, and to explore sex differences in the frequency of pre- to post-race physiological
202
perturbations in groups matched for ultramarathon finish time. The main findings were: i) ultramarathon
203
evoked significant increases in skeletal muscle, cardiac, and renal biomarkers, and significant decreases in
204
various aspects of respiratory and cardiopulmonary function; ii) both males and females exhibited
205
biomarker disturbances but with a greater number of perturbations in males; and iii) ultramarathon reduced
206
lung function and increased comet tails in both groups, with additional reductions in diffusing capacities
207
and pulmonary capillary volumes in males. Our data show that ultramarathon negatively impacts a range
208
of physiological functions but generally evokes more frequent perturbations, with larger effect sizes (pooled
209
effect size for all variables, d = 0.86 vs. 0.63) in males compared to females matched for finish time.
210
In accordance with existing literature (5), ultramarathon resulted in a significant decrease in
211
spirometric indices of lung function; specifically, forced vital capacity (FVC), forced expiratory volume in
212
1 second (FEV1), and peak expiratory flow (PEF) (Fig. 4). The overall decreases in FVC and FEV1 were
213
driven primarily by females. Wuthrich et al. published respiratory data from 23 runners (8 female) who
214
contested the UTMB® in 2012 (35). Congruent with our findings, they also reported significant post-race
215
decreases in FEV1 and PEF. Airflow during spirometry is a product of the driving pressure of the thoracic
216
muscles offset against the airway resistance (36). Given that we observed no evidence of small airway
217
obstruction post-race, in either group (i.e., no change in FEF25-75, R5, or R5-R19), the most likely explanation
218
for the decreases in expiratory flows is a diminished thoracic driving pressure. This may have been
219
attributable to a mild degree of expiratory muscle fatigue, as proposed by Wuthrich et al. (35), and/or a
220
failure to start the FVC manoeuvre from a “true” total lung capacity, as reported by Tiller et al. (37). The
221
latter scenario is especially likely given the significantly diminished post-race IC exhibited by both groups.
222
Females generally have smaller lungs and narrower conducting airways than males (16, 38) and
223
are more likely to exhibit expiratory flow limitation during exercise (39). As such, the larger magnitude of
224
reduction in peak flows in the female athletes was not unexpected. Nevertheless, despite statistically
225
significant decreases in pulmonary function in both groups, follow-up analyses using regression equations
226
from the Global Lung Function Initiative (40) showed that all post-race values of FVC and FEV1 (with the
227
exception of one male participant, see below) remained within normal limits and were unlikely to pose an
228
acute clinical concern.
229
The male cohort exhibited a large and significant pre- to post-race decrease in lung diffusing
230
capacities (DLCO = -16%; DLCO,HbCorr = -12%, DLNO = -16%), whereas post-race values in the female group
231
were not significantly different from baseline (Fig. 4). The decreases in DLCO and DLNO, which reflect a
232
reduced capacity for gas transfer from alveoli to the bloodstream, may result from a fall in pulmonary
233
capillary blood volume (VC) in males, especially given that there was no post-race change in DMCO. There
234
are reports of diminished DLCO and DMCO at altitude without changes in VC in healthy participants (41).
235
Acute high-intensity exercise has also been shown to reduce DLCO and VC (42), despite being compensated
236
for, in some cases, by increases in DMCO (43). It is unclear if the reduced capacity for gas transfer in males
237
resulted from ultra-endurance exercise, the intermittent altitude, or a combined effect of both stimuli
238
resulting in a mild post-race pulmonary vascular de-recruitment and an overall null effect on DMCO in
239
males. Further study in a larger cohort is required to explore this finding and establish whether a pulmonary
240
vascular phenotype in female runners precludes a decline in DLCO and VC following ultramarathon.
241
There was an overall increase in lung comet tails following the race, and values were significantly
242
elevated in both females and males. Nevertheless, the male group exhibited considerably larger effect sizes
243
(2.41 vs. 0.96), and all males increased comet tails by >1 versus only 4/8 females. As per Picano et al., (31),
244
post-race comet tails in the range of 5 – 15 indicate “mild” extravascular lung water accumulation, and this
245
threshold was met only by males. By contrast, values in females remained in the “normal” range (i.e., < 5).
246
Although our data somewhat contradict earlier studies showing greater prevalence of interstitial lung
247
oedema in females following marathon (44), there is evidence of pulmonary oedema triggered by both
248
maximal and submaximal (prolonged) exercise, independent of sex and the level of hypoxia (45). As such,
249
there is no reason to think that the present increases in lung comet tails were mediated exclusively by the
250
intermittent altitude experienced during the race. Instead, capillary haemorrhage, increased capillary
251
permeability, and/or pulmonary oedema may result from increased cardiac output and pulmonary vascular
252
pressure during exercise (46). It is worthy of note that the individual male and female athletes who exhibited
253
the greatest increases in lung comet tails also exhibited the largest post-race declines in pulmonary function.
254
In fact, the male individual was the only participant in the cohort to exhibit post-race values for FEV1 that
255
fell below the lower limit of normal. Although our data confirm earlier observations that there is little
256
relation between the change in oedema score and the change in DMCO or FVC (47), there may yet be an
257
interaction among ultra-endurance exercise, intermittent altitude, and pulmonary oedema which warrants
258
further study.
259
Relative to baseline, we observed significant overall increases in both BNP and cTnI following the
260
race (Fig. 3). The absolute values were modest and remained within normal limits, as was generally
261
observed in studies of cardiac biomarkers following the Badwater ultramarathon (216 km; (3)) and the
262
Western States Endurance Run (160 km; (4)). Increased cardiac biomarkers are considered to be a common
263
response to endurance exercise and were reported as elevated in endurance athletes without any
264
accompanying signs of persistent cardiac damage (48). Nonetheless, a recent review highlighted the
265
potential for long-term cardiovascular maladaptations with ultra-endurance running (6) such that the
266
prognostic importance of periodic acute increases in biomarkers (particularly cardiac biomarkers) should
267
not be dismissed. Specifically, more research is needed to elucidate the clinical importance of biomarkers
268
that may be repeatedly elevated as a result of frequent ultra-endurance competition.
269
The observation of smaller and less frequent biomarker disturbances in the female group was
270
unexpected. In fact, only BNP and CK-MB were significantly elevated above baseline in females, whereas
271
males exhibited significant post-race disturbances in BNP, CK-MB, and Cr. Pre-race cTnI assessments
272
were negative (≤ 0.01 ng/mL) in all participants except one male (0.02 ng/mL), and an increase of > 0.01
273
ng/mL was observed in 5/8 females and 6/8 males, with larger effect sizes in males (0.99 vs 1.18). In
274
marathon runners, Neilan et al. (49) reported that the greatest increase in post-race cardiac biomarkers
275
occurred in those athletes training less than 35 miles/wk. Although this would indicate that higher training
276
volumes and better physical condition could be protective in the release of cardiac troponins during and
277
following exercise, George et al. found no such relationship in a diverse group of recreational runners (50).
278
Accordingly, the clinical relevance of these modest post-race changes is unclear.
279
Pre- to post-race SV was 73.0 to 65.2 mL in males (-11.4%; p = 0.084, d = 0.74) and 63.2 to 61.5
280
mL in females (-1.4%; p = 0.744, d = 0.11). Although BNP and cTnI were generally elevated following the
281
race, studies have refuted the notion that these biomarkers reflect cardiomyocyte damage (51). Interestingly,
282
the magnitude of the SV reduction in males was similar to that observed by Scott et al. (4) following a 160
283
km ultramarathon (77 to 64 mL). There are several proposed causes of such post-race decreases, including
284
low-frequency fatigue, the downregulation of cardiac beta-receptors, and decreases in plasma volume (2),
285
although our data exclude this latter mechanism. We can also speculate that the relative post-exercise
286
hypotension observed in males may have influenced cardiac afterload and/or preload.
287
Following the race, CK-MB concentrations were elevated above normal in both males and females
288
(Fig. 3) and this is considered an indirect marker of muscle damage. Indeed, several ultramarathon studies
289
report significant post-race increases in total creatine kinase (CK) concentrations with values increasing
290
congruent with race distance (52, 53). Some authors consider the muscle damage and metabolic stress
291
associated with ultramarathons to represent a danger to human health (54), causing possible hepatic damage
292
(55), and it may be that there are protective effects of smaller and less frequent CK isoenzyme perturbations
293
following ultra-endurance exercise. We initially speculated that CK-MB concentrations may be associated
294
with peripheral muscle fatigue during ultramarathon; however, previous studies reporting sex differences
295
in peripheral muscle fatigability following short (<60 km) and long (>100 km) distance ultramarathons also
296
showed show no sex differences in post-race CK isoenzyme concentrations when males and females were
297
matched by percent of winning time by sex (56, 57). Accordingly, any sex differences in peripheral muscle
298
fatigability (14) are likely independent of skeletal muscle damage and/or biomarker levels.
299
Changes in haematocrit and haemoglobin were used to calculate relative changes in plasma volume.
300
There was a large and significant post-race increase in plasma volume in the male group (21%; p = 0.043,
301
d = 1.36), whereas the post-race change in females was not significant (7%; p =0.143, d = 0.61). The
302
magnitude of the change was almost identical (21 vs. 20%) to that observed by Robach et al. in 22 male
303
runners following the UTMB® (58). In that study, the authors speculated that the increase in PV may have
304
resulted from inflammation and an associated interlukin-6-mediated effect on plasma volume expansion.
305
Sex differences in inflammation following ultramarathon have not been comprehensively assessed, but our
306
findings provide some interesting preliminary data that warrant exploration.
307
308
Methodological and physiological considerations
309
The female and male runners in this study were matched for ultramarathon finish time and running velocity
310
(Table 1) because it was deemed that matching the duration of exercise exposure and absolute work rate
311
would be important for comparing the frequency of physiological perturbations. As a result, other aspects
312
of physiological function were unable to be standardized. For example, there will be inherent differences
313
in cardiorespiratory fitness between time-matched females and males, discrepancies that we were unable to
314
quantify. During the race, this may have resulted in the two groups operating at different relative exercise
315
intensities. Other studies comparing physiological functions between male and female ultramarathon
316
runners opted to match groups by relative performance to the first male and the first female of their specific
317
race (57). While this approach has the advantage that male and female participants would be matched for
318
relative running ability, it does not overcome the problem of participants operating at different relative
319
exercise intensities and/or metabolic rates. Physiological profiling athletes in future studies would provide
320
clarity in this respect, aid in the interpretation of data, and improve our understanding of the respective male
321
and female ultramarathon performance predictors.
322
Another consideration is that the remote location of the race necessitated that our extensive
323
laboratory measures were limited to those that could be made using portable/point-of-care devices. More
324
detailed measures of physiological responses (e.g., inflammation, body composition, etc.) would require
325
expensive and fragile equipment to be transported into the field, and this is often impractical. The execution
326
of simulated, lab-based ultramarathon research may be one way of deriving more mechanistic insights in
327
the future. The nature of ‘field testing’ also made it difficult to perform post-race measurements in a timely
328
fashion because, for instance, the measuring devices could not be situated at the finish line. This required
329
athletes to travel a short distance for their post-race assessments and is a common problem with such studies.
330
Presently, we aimed to retrieve participants for their post-race assessments as soon as possible, with the
331
actual time being 1 h 41 min ± 54 min after finishing the race. Although radiographic findings of mild
332
interstitial oedema have been observed to persist for at least 98 min after endurance exercise (marathon
333
running) (44), comet tails and several of our other measures, including aspects of pulmonary and respiratory
334
muscle function, will have started to recover within a few hours (5). As such, it is possible that there may
335
have been an underestimation of the number and/or magnitude of pre- to post-race physiological changes.
336
Nonetheless, the time in which females and males returned for post-race assessments was similar, thereby
337
not invalidating a direct comparison of the frequency of between-group perturbations.
338
Finally, in the present study, we examined sex-specific physiological responses to ultramarathon
339
by comparing the frequency of physiological perturbations between males and females. However, although
340
our original data set represents one of the larger samples of its kind among the literature, comprising all
341
female participants from an initial mixed-sex cohort of 53 athletes who contested the event over two years,
342
the relatively small sample size (and the large within-group variance) precluded any direct male-to-female
343
comparisons on the magnitude of the response. Based on the data reported herein, a power analysis was
344
performed (G*Power version 3.1.9.6) to determine the sample size that would be required to observe a
345
statistically significant between-group interaction (should one exist) in future studies using a repeated-
346
measures design. Based on an alpha level of 0.05 and a statistical power of 0.8, a total of 32 participants
347
(16 per group) would likely be required where moderate between-group effect sizes are observed (e.g., most
348
biomarker comparisons), although slightly smaller samples sizes would likely be acceptable in the case of
349
larger between-group effects (e.g., diffusing capacity and comet tails). We hope this will inform future
350
research on sex differences in physiological variables in response to ultramarathon.
351
352
Conclusions
353
Ultramarathon evokes considerable physical stress on multiple body systems, as evidenced by significant
354
pre- to post-race disturbances in numerous aspects of physiological function. In males and females matched
355
for ultramarathon finish time, it was male athletes who exhibited more frequent perturbations, and with
356
larger effect sizes, most notably in lung diffusing capacities and in biomarkers of skeletal muscle, cardiac,
357
and renal function. These data may inform training prescription and future research on long-term health
358
and injury management in ultramarathon.
359
360
Acknowledgments
361
The authors would like to thank the athletes who volunteered their time while contesting one of the world’s
362
most arduous footraces. Individual thanks are reserved for Catherine Poletti and Michel Poletti of UTMB®,
363
Patrick Basset and Volker Scheer of the Ultra Sports Science Foundation, and Loïc Chabridon for clinical
364
expertise he provided during data collection. Thanks are also extended to personnel at Grenoble University
365
Hospital for their help preparing the ethics application in France, and The institute Ecole Nationale des
366
Sports de Montagne for hosting the research team throughout data collection. This research was funded by
367
a grant that the Mayo Clinic received from Biomobie Regenerative Medicine Co. (Shanghai, China).
368
Finally, the authors would like to thank MGC Diagnostics Corporation (Minnesota, USA), Medisoft
369
(Sorinnes, Belgium), and Philips Healthcare (Eindhoven, Netherlands) for equipment and technical support.
370
371
Conflict of Interest
372
The authors declare no conflict of interest. The results of the present study do not constitute endorsement
373
by ACSM. The results of the study are presented clearly, honestly, and without fabrication, falsification, or
374
inappropriate data manipulation. NBT is supported by a postdoctoral fellowship from the Tobacco-Related
375
Disease Research Program (TRDRP; award no. T31FT1692). GMS is supported by the American Heart
376
Association (AHA#19POST34450022) and a Career Development Award in Cardiovascular Disease
377
Research Honouring Dr. Earl H. Wood from Mayo Clinic.
378
379
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515
TABLES AND FIGURES
516
Table 1. Participant demographics and race data.
517
518
Table 2. Baseline physiological comparisons.
519
520
Supplementary table. Pre- and post-race physiological responses in males and females.
521
522
Figure 1. Course profiles for the Ultra-Trail du Mont-Blanc (UTMB®; panel A) and the CCC® (panel B).
523
The CCC® begins at 78 km into the UTMB® course (at Courmayeur) and the two races follow a similar,
524
although not identical, route thereafter.
525
526
Figure 2. Illustration of testing procedures.
527
528
Figure 3. Pre- to post-race changes in haemoglobin (panel A), haematocrit (panel B), troponin I (panel C),
529
brain neuropeptide (panel D), creatinine (panel E), and creatine kinase-MB (panel F) in females (□) and
530
males (■). † = statistically significant overall (n=16) change from baseline; p = p-value from independent-
531
or paired-samples t-test; d = Cohen’s d effect size; *statistically significant within-group (n=8) difference
532
(Benjamini-Hochberg-adjusted p-value). For clarity of presentation, data are presented as mean and
533
standard error of the mean.
534
535
Figure 4. Pre- to post-race changes in forced expiratory volume in 1-second (panel A), peak expiratory
536
flow (panel B), inspiratory capacity (panel C), maximum inspiratory pressure (panel D), exhaled NO (panel
537
E), diffusing capacity for CO (panel F), diffusing capacity for NO (panel G), and alveolar capillary volume
538
(panel H) in females (□) and males (■). † = statistically significant overall (n=16) change from baseline; p
539
= p-value from independent- or paired-samples t-test; d = Cohen’s d effect size; *statistically significant
540
within-group (n=8) difference (Benjamini-Hochberg-adjusted p-value). For clarity of presentation, data are
541
presented as mean and standard error of the mean.
542
543
Table 1. Participant demographics and race data.
Overall (n=16)
Females (n=8)
Males (n=8)
p
d
Age (y)
38.4
±
7.6
36.6
±
6.9
40.3
±
8.3
0.361
0.48
Stature (cm)
171.3
±
6.3
167.1
±
5.3
175.5
±
4.0
0.003*
1.79
Mass (kg)
63.9
±
9.0
56.9
±
6.1
71.0
±
4.6
0.004*
2.58
Finish time (h:min)
30:52
±
10:42
30:57
±
11:36
30:46
±
10:32
0.975
0.02
UTMB®
39:56
±
06:42
40:24
±
06:49
39:28
±
07:34
0.860
0.12
CCC®
21:48
±
03:33
21:30
±
05:24
22:05
±
00:19
0.837
0.13
Velocity (m/s)
1.2
±
0.2
1.2
±
0.3
1.2
±
0.1
0.762
0.00
UTMB®
1.1
±
0.1
1.1
±
0.0
1.1
±
0.1
0.425
0.00
CCC®
1.3
±
0.2
1.4
±
0.4
1.3
±
0.0
0.615
0.35
Mean ± SD; p = independent-samples t-test; d = Cohen’s d effect size.
544
545
Table 2. Baseline physiological comparisons.
Females (n=8)
Males (n=8)
P
d
Vital Signs
fC (beats/min)
57
±
7
50
±
9
0.129
0.81
SBP (mmHg)
107
±
7
122
±
11
0.011*
1.69
DBP (mmHg)
73
±
8
76
±
7
0.303
0.66
Blood Sampling
Na2+ (mmol/L)
138.4
±
1.3
141.0
±
1.5
0.008*
1.87
K+ (mmol/L)
4.0
±
0.4
3.9
±
0.3
0.775
0.30
Cl- (mmol/L)
103.5
±
3.3
104.0
±
2.1
0.943
0.19
Hb (g/dL)
13.9
±
0.8
14.9
±
0.9
0.057
1.12
Hct (%)
40.9
±
2.4
43.9
±
2.7
0.045*
1.18
PV (L)
2.7
±
0.2
3.1
±
0.1
0.004*
2.53
cTnI (ng/mL)
0.001
±
0.004
0.005
±
0.008
0.233
0.68
BNP (pg/mL)
25.8
±
14.6
26.6
±
17.5
0.971
0.05
Cr (mg/dL)
0.8
±
0.1
1.1
±
0.2
0.012*
1.79
CK-MB (IU/L)
3.3
±
2.4
7.2
±
3.9
0.039*
1.25
Pulmonary Function
FVC (L)
4.3
±
0.6
5.4
±
0.7
0.010*
1.67
FEV1 (L)
3.4
±
0.6
4.2
±
0.5
0.028*
1.40
FEV1/FVC
79.9
±
7.1
78.9
±
6.4
0.801
0.14
PEF (L/s)
7.1
±
0.8
10.2
±
2.2
0.012*
2.05
FEF25-75 (L)
3.3
±
1.1
3.9
±
0.9
0.496
0.61
IC (L)
3.3
±
0.8
4.1
±
1.2
0.117
0.81
FIV1 (L)
2.5
±
0.7
4.2
±
0.8
0.004*
2.22
R5 (cmH2O/L/s)
3.2
±
1.2
2.0
±
0.4
0.128
1.43
R5-R19 (cmH2O/L/s)
-0.24
±
0.27
0.00
±
0.20
0.232
1.05
FeNO (ppb)
19.4
±
16.7
18.5
±
5.6
0.619
0.08
DLCO (mL/min/mmHg)
25.5
±
3.2
34.4
±
5.7
0.008*
2.00
DLCO,HbCorr (mL/min/mmHg/g/dL)
25.1
±
3.2
34.2
±
5.7
0.008*
1.96
DLCO/VA (mL/min/mmHg/L)
4.9
±
0.6
4.7
±
1.0
1.000
0.16
DLNO (mL/min/mmHg)
124.4
±
15.0
179.1
±
26.2
0.001*
2.66
DMCO (mL/min/mmHg)
118.4
±
18.3
338.5
±
447.5
0.108
0.94
VC (mL)
60.8
±
9.7
77.4
±
16.7
0.039*
1.26
PIMAX (cmH2O)
95.1
±
22.8
132.7
±
11.7
0.020*
2.17
PEMAX (cmH2O)
117.1
±
22.8
202.5
±
28.9
0.004*
3.31
Transthoracic Ultrasound
Lung comet Tails (n)
0.8
±
1.4
2.4
±
2.2
0.081
0.91
SV (mL)
63.2
±
14.2
73.0
±
11.9
0.209
0.75
Q
(L/min)
3.6
±
0.8
3.6
±
0.7
0.787
0.13
Mean ± SD. fC = cardiac frequency (heart rate); SBP = systolic blood pressure; DBP = diastolic blood pressure; Na2+ = sodium concentration; K+ =
potassium concentration; Cl- = chloride concentration; Hb = haemoglobin concentration; Hct = haematocrit; PV = plasma volume; cTnI = cardiac
troponin-1; BNP = brain natriuretic peptide; Cr = creatinine; CK-MB = creatine kinase; FVC = forced vital capacity; FEV1 = forced expiratory volume
in 1-second; PEF = peak expiratory flow; FEF25-75 = forced expiratory flow between 25 and 75% of FVC; IC = inspiratory capacity; FIV1 = forced
inspiratory volume in 1-second; R5 = airway resistance at 5 Hz; R5-R19 = airway resistance at 5 Hz minus resistance at 19 Hz (small airways); FeNO =
exhaled nitric oxide; DLCO = diffusing capacity of the lung for carbon monoxide; DLCO,HbCorr = diffusing capacity of the lung for carbon monoxide
corrected to reference haemoglobin concentrations; DLCO/VA = diffusing capacity of the lung for carbon monoxide relative to alveolar volume; DLNO
= diffusing capacity of the lung for nitric oxide; DMCO = diffusing capacity of the pulmonary membrane for carbon monoxide; VC = pulmonary capillary
blood volume; PIMAX = maximum inspiratory pressure; PEMAX = maximum expiratory pressure; SV = stroke volume; Q
= cardiac output. p = p-value
from independent-samples t-test; d = Cohen’s d effect size; *statistically significant between-group difference (Benjamini-Hochberg-adjusted p-value).
546
547
548
Fig 1
549
550
551
Fig 2
552
553
554
Fig 3
555
556
557
Fig 4
558
Supplementary table. Pre- and post-race physiological responses in males and females.
Females (n=8)
Males (n=8)
Pre-race
Post-race
P
d
Pre-race
Post-race
P
d
Body mass & vital signs
Mass (kg) †
56.9 ± 6.1
55.8 ± 5.9
0.027*
0.17
71.0 ± 4.6
69.4 ± 5.2
0.027*
0.32
fC (beats/min) †
57 ± 7
73 ± 15
0.012*
1.43
50 ± 9
62 ± 7
0.053
1.43
SBP (mmHg) †
107 ± 6
105 ± 10
0.500
0.24
122 ± 11
106 ± 10
0.008*
1.53
DBP (mmHg)
72 ± 8
71 ± 12
0.781
0.12
77 ± 8
71 ± 7
0.344
0.80
Blood Sampling
Na2+ (mmol/L)
138.4 ± 1.3
137.6 ± 1.9
0.490
0.46
141.0 ± 1.5
140.2 ± 2.2
0.580
0.33
K+ (mmol/L)
4.0 ± 0.4
3.3 ± 0.8
0.122
1.20
3.9 ± 0.3
3.9 ± 0.4
0.690
0.19
Cl- (mmol/L)
103.5 ± 3.3
103.5 ± 2.5
0.984
0.00
104.0 ± 2.1
106.1 ± 2.1
0.256
1.00
Hb (g/dL) †
13.9 ± 0.8
13.4 ± 0.7
0.164
0.66
14.9 ± 0.9
13.5 ± 2.0
0.052
0.90
Hct (%) †
40.9 ± 2.4
39.5 ± 2.1
0.196
0.62
43.9 ± 2.7
39.8 ± 5.8
0.052
0.91
PV (L) †
2.7 ± 0.2
2.9 ± 0.4
0.143
0.61
3.1 ± 0.1
3.7 ± 0.6
0.043*
1.36
cTnI (ng/mL) †
0.001 ± 0.004
0.031 ± 0.043
0.117
0.99
0.005 ± 0.008
0.046 ± 0.049
0.060
1.18
BNP (pg/mL) †
25.8 ± 14.6
140.9 ± 102.7
0.007*
1.57
26.6 ± 17.5
96.4 ± 51.9
0.002*
1.80
Cr (mg/dL) †
0.8 ± 0.1
0.8 ± 0.2
0.504
0.24
1.1 ± 0.2
1.2 ± 0.2
0.028*
0.75
CK-MB (IU/L) †
3.3 ± 2.4
74.6 ± 49.6
0.005*
2.03
7.2 ± 3.9
108.8 ± 37.4
0.002*
3.82
Pulmonary Function
FVC (L) †
4.3 ± 0.6
3.8 ± 0.6
0.008*
0.79
5.4 ± 0.7
5.3 ± 0.8
0.636
0.14
FEV1 (L) †
3.4 ± 0.6
3.1 ± 0.6
0.052
0.54
4.2 ± 0.5
4.1 ± 0.9
0.337
0.24
FEV1/FVC
79.9 ± 7.1
80.8 ± 5.3
0.800
0.14
78.9 ± 6.4
76.2 ± 10.1
1.000
0.33
PEF (L/s) †
7.1 ± 0.8
6.1 ± 1.3
0.039*
0.92
10.2 ± 2.2
9.6 ± 2.6
0.048*
0.25
FEF25-75 (L)
3.3 ± 1.1
3.0 ± 1.0
0.333
0.29
3.9 ± 0.9
3.6 ± 1.2
0.292
0.31
IC (L) †
3.3 ± 0.8
2.2 ± 0.7
0.004*
1.46
4.1 ± 1.2
3.3 ± 0.9
0.005*
0.79
FIV1 (L)
2.5 ± 0.7
2.4 ± 0.5
0.607
0.19
4.2 ± 0.8
3.8 ± 0.6
0.200
0.58
R5 (cmH2O/L/s)
3.2 ± 1.2
3.6 ± 1.7
0.455
0.28
2.0 ± 0.4
2.2 ± 0.7
0.325
0.46
R5-R19 (cmH2O/L/s)
-0.24 ± 0.27
-0.08 ± 0.23
0.213
0.66
0.00 ± 0.20
0.05 ± 0.17
0.368
0.26
FeNO (ppb) †
19.4 ± 16.7
10.6 ± 8.4
0.031*
0.66
18.5 ± 5.6
13.1 ± 5.5
0.038*
0.97
DLCO (mL/min/mmHg) †
25.5 ± 3.2
24.2 ± 2.5
0.328
0.45
34.4 ± 5.7
29.2 ± 6.9
0.004*
0.83
DLCO,HbCorr (mL/min/mmHg/g/dL)
25.1 ± 3.2
24.3 ± 2.4
0.550
0.30
34.2 ± 5.7
30.5 ± 7.8
0.090
0.54
DLCO/VA (mL/min/mmHg/L)
4.9 ± 0.6
4.9 ± 0.7
0.981
0.00
4.7 ± 1.0
4.6 ± 1.4
1.000
0.11
DLNO (mL/min/mmHg) †
124.4 ± 15.0
113.2 ± 13.3
0.064
0.79
179.1 ± 26.2
152.8 ± 33.4
0.002*
0.88
DMCO (mL/min/mmHg)
118.4 ± 18.3
105.0 ± 12.6
0.106
0.86
338.5 ± 447.5
239.0 ± 87.4
0.924
0.31
VC (mL) †
60.8 ± 9.7
55.9 ± 7.3
0.179
0.57
77.4 ± 16.7
57.3 ± 16.1
0.002*
1.22
PIMAX (cmH2O) †
95.1 ± 22.8
84.4 ± 22.4
0.028*
0.47
132.7 ± 11.7
113.9 ± 23.4
0.071
1.02
PEMAX (cmH2O)
117.1 ± 22.8
105.6 ± 20.7
0.147
0.53
202.5 ± 28.9
174.1 ± 54.3
0.193
0.65
Transthoracic Ultrasound
Lung comet Tails (n) †
0.8 ± 1.4
2.9 ± 2.8
0.048*
0.96
2.4 ± 2.2
8.3 ± 2.7
0.006*
2.41
SV (mL)
63.2 ± 14.2
61.5 ± 17.4
0.744
0.11
73.0 ± 11.9
65.2 ± 9.1
0.084
0.74
Q
(L/min) †
3.6 ± 0.8
4.4 ± 1.2
0.048*
0.80
3.6 ± 0.7
4.0 ± 0.5
0.177
0.70
Mean ± SD. fC = cardiac frequency (heart rate); SBP = systolic blood pressure; DBP = diastolic blood pressure; Na2+ = sodium concentration; K+ = potassium concentration; Cl- = chloride
concentration; Hb = haemoglobin concentration; Hct = haematocrit; PV = plasma volume; cTnI = cardiac troponin-1; BNP = brain natriuretic peptide; Cr = creatinine; CK-MB = creatine kinase;
FVC = forced vital capacity; FEV1 = forced expiratory volume in 1-second; PEF = peak expiratory flow; FEF25-75 = forced expiratory flow between 25 and 75% of FVC; IC = inspiratory capacity;
FIV1 = forced inspiratory volume in 1-second; R5 = airway resistance at 5 Hz; R5-R19 = airway resistance at 5 Hz minus resistance at 19 Hz (small airways); FeNO = exhaled nitric oxide; DLCO =
diffusing capacity of the lung for carbon monoxide; DLCO,HbCorr = diffusing capacity of the lung for carbon monoxide corrected to reference haemoglobin concentrations; DLCO/VA = diffusing
capacity of the lung for carbon monoxide relative to alveolar volume; DLNO = diffusing capacity of the lung for nitric oxide; DMCO = diffusing capacity of the pulmonary membrane for carbon
monoxide; VC = pulmonary capillary blood volume; PIMAX = maximum inspiratory pressure; PEMAX = maximum expiratory pressure; SV = stroke volume; Q
= cardiac output. † = statistically
significant overall (n=16) change from baseline; p = p-value from paired-samples t-test; d = Cohen’s d effect size; *statistically significant within-group (n=8) change from baseline (Benjamini-
Hochberg-adjusted p-value).
559
