==== Front BMC Musculoskelet Disord BMC Musculoskelet Disord BMC Musculoskeletal Disorders 1471-2474 BioMed Central London 6589 10.1186/s12891-023-06589-2 Research Article Cardiac output and arteriovenous oxygen difference contribute to lower peak oxygen uptake in patients with fibromyalgia http://orcid.org/0000-0002-4428-1401 Lehto Taneli taneli.lehto@helsinki.fi 12 Zetterman Teemu 345 Markkula Ritva 3 Arokoski Jari 2 Tikkanen Heikki 6 Kalso Eija 378 Peltonen Juha E. 19 1 grid.7737.4 0000 0004 0410 2071 Department of Sports and Exercise Medicine, Clinicum, University of Helsinki, Mäkelänkatu 47, Urhea-Hall, 00550 Helsinki, Finland 2 grid.15485.3d 0000 0000 9950 5666 Department of Physical and Rehabilitation Medicine, Helsinki University Hospital and Helsinki University, Helsinki, Finland 3 grid.15485.3d 0000 0000 9950 5666 Department of Anaesthesiology, Intensive Care and Pain Medicine, Pain Clinic, Helsinki University and Helsinki University Hospital, Helsinki, Finland 4 City of Vantaa Health Centre, Vantaa, Finland 5 grid.7737.4 0000 0004 0410 2071 Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland 6 grid.9668.1 0000 0001 0726 2490 Sports and Exercise Medicine, Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland 7 grid.7737.4 0000 0004 0410 2071 SLEEPWELL Research Programme, Faculty of Medicine, University of Helsinki, Helsinki, Finland 8 grid.7737.4 0000 0004 0410 2071 Department of Pharmacology, Faculty of Medicine, University of Helsinki, Helsinki, Finland 9 Foundation for Sports and Exercise Medicine, Helsinki Sports and Exercise Medicine Clinic, Helsinki, Finland 1 7 2023 1 7 2023 2023 24 54119 9 2022 30 5 2023 © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Background Patients with fibromyalgia (FM) exhibit low peak oxygen uptake (V˙O2peak). We aimed to detect the contribution of cardiac output to (Q˙) and arteriovenous oxygen difference [C(a-v)O2] to V˙O2 from rest to peak exercise in patients with FM. Methods Thirty-five women with FM, aged 23 to 65 years, and 23 healthy controls performed a step incremental cycle ergometer test until volitional fatigue. Alveolar gas exchange and pulmonary ventilation were measured breath-by-breath and adjusted for fat-free body mass (FFM) where appropriate. Q˙ (impedance cardiography) was monitored. C(a-v)O2 was calculated using Fick’s equation. Linear regression slopes for oxygen cost (∆V˙O2/∆work rate) and Q˙ to VO2 (∆Q˙/∆V˙O2) were calculated. Normally distributed data were reported as mean ± SD and non-normal data as median [interquartile range]. Results V˙O2peak was lower in FM patients than in controls (22.2 ± 5.1 vs. 31.1 ± 7.9 mL∙min−1∙kg−1, P < 0.001; 35.7 ± 7.1 vs. 44.0 ± 8.6 mL∙min−1∙kg FFM−1, P < 0.001). Q˙ and C(a-v)O2 were similar between groups at submaximal work rates, but peak Q˙ (14.17 [13.34–16.03] vs. 16.06 [15.24–16.99] L∙min−1, P = 0.005) and C(a-v)O2 (11.6 ± 2.7 vs. 13.3 ± 3.1 mL O2∙100 mL blood−1, P = 0.031) were lower in the FM group. No significant group differences emerged in ∆V˙O2/∆work rate (11.1 vs. 10.8 mL∙min−1∙W−1, P = 0.248) or ∆Q˙/∆V˙O2 (6.58 vs. 5.75, P = 0.122) slopes. Conclusions Both Q˙ and C(a-v)O2 contribute to lower V˙O2peak in FM. The exercise responses were normal and not suggestive of a muscle metabolism pathology. Trial registration ClinicalTrials.gov, NCT03300635. Registered 3 October 2017—Retrospectively registered. https://clinicaltrials.gov/ct2/show/NCT03300635. Keywords Cardiopulmonary exercise test Impedance cardiography Leisure-time physical activity Ventilatory threshold Oxygen cost Finnish State Research FundingTYH2017215 http://dx.doi.org/10.13039/501100004325 Signe ja Ane Gyllenbergin Säätiö http://dx.doi.org/10.13039/100008376 Helsingin ja Uudenmaan Sairaanhoitopiiri HUS 76/2018 § 11 HUS 174/2019 § 1 Lehto Taneli http://dx.doi.org/10.13039/501100003126 Opetus- ja Kulttuuriministeriö University of Helsinki including Helsinki University Central HospitalOpen Access funding provided by University of Helsinki including Helsinki University Central Hospital. issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2023 ==== Body pmcBackground The key symptoms of fibromyalgia (FM) include persistent, widespread pain, disturbed sleep, fatigue, and cognitive and mood disturbances [1]. The exact pathophysiology of FM remains unknown. Central sensitization and defects in endogenous pain inhibition are now recognized, but peripheral factors may be equally pertinent [1]. The muscle in FM has been investigated since the 1980s [2], but compelling evidence of altered muscle function in FM is still lacking. Aerobic and strengthening exercise are strongly recommended in the multimodal management of FM [3], although exercise-induced worsening of symptoms is commonly reported [4]. Nevertheless, physiological adaptations to endurance [5] and resistance [6] exercise are comparable to those of healthy controls. Patients with FM have low peak oxygen uptake (V˙O2peak) [7] and V˙O2peak is associated with pain severity [8] in FM. Physical inactivity [9] is a conceivable explanation for low V˙O2peak, but it is not known which of its contributing factors, cardiac output (Q˙) or arteriovenous oxygen difference (C(a-v)O2), is limiting aerobic capacity in FM. Although FM per se does not seem to increase mortality [10], low cardiorespiratory fitness is a risk factor for all-cause mortality and morbidity [11] and is therefore a relevant health issue. Mitochondrial pathology, also suggested to be a part of the pathophysiology of FM [12–16], would be an intriguing explanation tying together exercise intolerance and the muscle symptoms of FM. The reason for these putative mitochondrial alterations is not known, and most of the studies do not account for physical activity. However, a genetic polymorphism in mitochondrial DNA, resulting in decreased oxidative phosphorylation, has been suggested to associate with FM [17]. Gerdle et al. [16] found higher pyruvate and lower adenosine triphosphate (ATP) and phosphocreatine (PCr) concentrations in the muscles of FM patients, which may reflect decreased cellular respiration in the mitochondria. Altogether, FM symptoms share similarities with those of mitochondrial myopathies (MM) [15]. MM can be investigated with the cardiopulmonary exercise test (CPET) [18]. CPET findings in MM may include low V˙O2peak, early anaerobic threshold, high respiratory exchange ratio (RER), high resting lactate, high peak minute ventilation to oxygen uptake ratio (V˙ E/V˙O2), steep heart rate (HR) to oxygen uptake (V˙O2) slope (ΔHR/ΔV˙O2), and low C(a-v)O2, which reflects muscle oxygen extraction [18, 19]. Taivassalo et al. [19] found steep Q˙ to V˙O2 slopes (ΔQ˙/ΔV˙O2) in MM patients. A recent study demonstrated steeper V˙O2 to work rate (P) slopes (ΔV˙O2/ΔP) in patients with different metabolic (including mitochondrial) myopathies as well as ‘non-metabolic myalgia’ compared with controls [20]. To our knowledge, these slopes have not been studied in FM before. We hypothesized that a possible pathology in muscle metabolism in patients with FM would result in altered exercise responses in a CPET and that pain intensity would affect exercise capacity. More precisely, if mitochondrial oxygen demand was decreased due to deficits in the cellular respiration pathways or simply due to lower muscle mitochondrial density, this would result in lower oxygen extraction and hence lower C(a-v)O2 and V˙O2peak as observed in MM [19]. Our primary objectives were to determine the contributing factors to V˙O2, to compare the ΔQ˙/ΔV˙O2 and ΔV˙O2/ΔP slopes between FM patients and controls, and to explore other exercise responses, including ventilatory thresholds (VTs), stroke volume (SV), systemic vascular resistance (SVR), and ventilatory efficacy (ΔV˙ E/ΔV˙CO2, where V˙ E is pulmonary ventilation and V˙CO2 is carbon dioxide production), among others. We expected to see 1) low V˙O2peak and C(a-v)O2, 2) low VTs, 3) steep ΔQ˙/ΔV˙O2 and ΔV˙O2/ΔP slopes, and 4) normal cardiac and pulmonary function in patients with FM. The secondary aim was to explore the relations between self-reported leisure-time physical activity (LTPA), disease severity, pain ratings, psychological factors, and exercise capacity. The work presented here is part of a larger study; Metabolism, Muscle Function, and Psychological Factors in Fibromyalgia, where the participants also underwent an electromyography study and an oral glucose tolerance test. Methods Study population In total, 38 women with FM and 28 age-matched healthy female controls participated in the exercise test. Of these participants, 35 women with FM, aged 23 to 65 years, and 23 controls completed the test without any technical issues in data recording and were included in the study. The secondary analysis, aiming to identify factors affecting exercise effort, included all 38 women with FM (Fig. 1). The initial recruitment process and exclusion criteria have previously been described [21]. Briefly, the American College of Rheumatology (ACR) 1990 Criteria for Fibromyalgia [22] were used as the inclusion criteria for the FM group. One of the researchers (TZ) performed a clinical examination on patients. Most of the patients were recruited from primary healthcare and from the Helsinki University Central Hospital outpatient clinics. The controls were recruited from the staff of the above-mentioned healthcare units and a local home economic organization (Uudenmaan Martat ry).Fig. 1 Flowchart of participant recruitment Questionnaires The participants reported the frequency and duration of their total LTPA and activity at different intensities (light, moderate, heavy). We then combined moderate and heavy physical activity (moderate to heavy) for the analyses, as the volumes of heavy LTPA were low. Other background data were collected utilizing questionnaires completed in the previous phase of the study [21]. These consisted of Finn-FIQ (Finnish version of the Fibromyalgia Impact Questionnaire) [23], PSS (Perceived Stress Scale) [24], STAI (State-Trait Anxiety Inventory) [25], PCS (Pain Catastrophizing Scale) [26], and ACR 2016 Criteria for Fibromyalgia (consisting of Widespread Pain Index [WPI] and Symptom Severity [SS]) questionnaires [27]. The STAI questionnaire comprises two parts: STAI-state, measuring current anxiety, and STAI-trait, measuring anxiety as a trait. In PSS, the timespan is the previous month. The delay between completing the questionnaires and the laboratory visit was long (median 5 months), and we therefore decided to omit STAI-state and PSS. PCS is validated for pain populations and FIQ for FM populations and are therefore not reported for the control group. Study protocol The study protocol is largely adopted from previous studies performed in our laboratory [28, 29]. All measurements (excluding the above-mentioned questionnaires) were performed on a single visit between January 2016 and April 2019. The participants arrived at the laboratory 2–3 h after a meal (breakfast or lunch). The visit consisted of pre-exercise measurements and a CPET. We measured the participants’ weight, height, and waist-to-hip ratio and calculated the body mass index (BMI). Body composition (e.g. fat-free body mass (FFM)) was analyzed using a bioimpedance device (InBody 720; Biospace Co., Ltd., Seoul, South Korea). In women, the InBody device yields roughly 8% higher FFM results compared with dual-energy x-ray absorptiometry [30]. Pre-exercise measurements included also a 12-lead ECG, blood pressure, and flow-volume spirometry (Medikro Spiro 2000; Medikro Oy, Kuopio, Finland). A physician evaluated the participants’ suitability for the exercise test. The CPET was performed on a cycle ergometer (Monark Ergomedic 839E; Monark Exercise AB, Vansbro, Sweden). The step incremental protocol was preceded by a 5-min rest while the subjects sat relaxed on the ergometer followed by a 5-min unloaded cycling (equivalent to ~ 6 W). Incremental exercise (25 W every 3 min) was then initiated, and the subjects continued exercising until volitional fatigue. The participants reported their rate of perceived exertion (RPE) using the Borg scale [31] (range 6 to 20) at the end of each work rate (P). They reported their sensation of pain at rest and after exercise using the numeric rating scale (NRS) (0 to 10). Lactate and pyruvate concentrations We collected blood samples at rest and immediately after exercise. For the pyruvate samples, we drew 1 mL of venous blood into EDTA tubes (Bd Vacutainer K2E 5.4 mg Bd-Plymouth, UK). Then, within 1 min, we pipetted 0.5 mL of blood into two pre-chilled tubes containing 1 mL of 8% perchloric acid each. We cooled the perchloric acid tubes by placing them into a container with cold gel packs for 5 min and then centrifugated them for 10 min at 4 °C and 1500 G. We pipetted the resulting supernatant into one perchloric acid tube. For the lactate samples, we drew 0.5 mL of venous blood into fluoride oxalate tubes (Vacutest NaF + K2OX, Vacutest Rima, Italy), which we then centrifugated for 10 min at 3000 rpm. Both samples were next placed in a freezer at -20.5 °C for a maximum of 3 days and then moved in dry ice to the Helsinki University Hospital Laboratory (HUSLAB) for analysis. The pyruvate samples were analyzed enzymatically by photometry, and the lactate samples were analyzed photometrically. We calculated lactate-to-pyruvate (L/P) ratios for each participant. Cardiorespiratory measurements We measured breath-by-breath ventilation by a low-resistance turbine (Triple V; Jaeger Mijnhardt, Bunnik, the Netherlands) during the exercise test. Expired and inspired gases were sampled continuously at the mouth and analyzed for concentrations of O2, CO2, N2, and Ar by mass spectrometry (AMIS 2000; Innovision A/S, Odense, Denmark) after calibration with precisely analyzed gas mixtures. Breath-by-breath respiratory data were collected as raw data, transferred to a computer to determine gas delays for each breath. The concentrations were aligned with the volume data and the profiles of each breath were built. Breath-by-breath alveolar gas exchange was then calculated with the AMIS algorithms, and the data were interpolated to obtain second-by-second values. V˙O2peak was determined as the highest value of a 60 s moving averaging interval. We analyzed cardiorespiratory responses during exercise at six different time points (i.e. work rates): rest, unloaded cycling, 25 W, 50 W, 75 W, and peak exercise, using the mean values of the last 30 s of each step. 75 W was the highest work rate which every participant could reach. VTs were determined as previously reported [32, 33]. Due to the multifaceted terminology, we chose to use the terms ventilatory threshold 1 (VT1) and ventilatory threshold 2 (VT2). We monitored arterial O2 saturation (SpO2) with fingertip pulse oximetry (Nonin 9600; Nonin Medical, Inc., Plymouth, MA, USA). We evaluated cardiac function with an impedance cardiograph (ICG) device (PhysioFlow; Manatec Biomedical, Paris, France). ICG measures changes in transthoracic impedance during cardiac ejection to calculate SV, which is multiplied by HR to provide an estimate of Q˙. Q˙ determined by ICG during exercise has been validated against the “gold standard”, the direct Fick method [34]. Systolic (SAP) and diastolic (DAP) blood pressures were measured automatically (Tango + ; SunTech Medical, Morrisville, NC, USA) from the brachial artery at rest and at the end of each work rate. We transferred blood pressure values into the ICG device, which calculated mean arterial pressure (MAP) and SVR. The impedance cardiograph data were averaged at 15 s intervals and the average of the last 30 s of each step was used in the analyses. To account for differences in body composition, we calculated indices for V˙O2, Q˙ and SV (marked with subscript i) by dividing them with FFM, whereas SVR was multiplied with FFM. The evidence for scaling V˙O2 to FFM instead of total body weight is robust [35–37]. In addition, research suggests prioritizing FFM over total body weight or body surface area when scaling cardiac function [38, 39]. We defined maximal effort as the inability to maintain a pedalling cadence of 60 rpm and using the age-adjusted RER criteria published by Edvardsen et al. [40]. Statistical analyses We assessed the normal distribution of the data with visual inspection and Shapiro–Wilk’s test. Differences between groups (FM and controls) were assessed using unpaired t-tests for normal variables and Mann–Whitney U test for non-normal variables. As not all participants reached maximal effort, we analyzed separately the peak exercise responses after excluding these participants. We used repeated measures ANOVA, where work rate was a within-subject factor and group a between-subject factor, for the analysis of cardiorespiratory responses during exercise. We then performed a separate MANOVA to further identify the work rates where between-group differences exist. We analyzed ΔV˙O2/ΔP, ΔHR/ΔV˙O2, and ΔQ˙/ΔV˙O2 slopes with linear regression as previously reported [29]. Group means from five time points (unloaded cycling (~ 6 W), 25 W, 50 W, 75 W, and peak exercise) were included. Resting values were omitted due to the rapid initial increase in oxygen uptake in the transition from rest to unloaded cycling. First, we performed regression analyses, where V˙O2 was a dependent variable and work rate an independent variable, for the FM and control groups separately. We then performed another linear regression analysis to evaluate the contribution of FM to the slopes. We created a dummy variable, where the FM group received a value of 1 and the control group a value of 0. The interaction term dummy*independent variable was then included in the model. ΔHR/ΔV˙O2, ΔQ˙/ΔV˙O2, and ΔV˙ E/ΔV˙CO2 slopes were assessed in a similar manner. The range used for the ΔV˙ E/ΔV˙CO2 slope was from rest until the second ventilatory threshold, after which there is a steep increase in the slope. We used Spearman correlations to explore the relations between work rate, HR, Q˙, V˙O2, and C(a-v)O2 at peak exercise, LTPA, and pain. We conducted a secondary analysis with the FM group. We identified a subgroup of participants who could not reach maximal effort (the ‘submaximal’ group) and they were compared with those who reached maximal effort (the ‘maximal’ group). All normal data are reported as mean ± SD, non-normal data as median [interquartile range], and categorical data as count (%), unless otherwise stated. Alpha was set to 0.05. The P values were not adjusted for multiple comparisons, as increasing type II error was deemed more harmful than reducing type I error. Statistical analyses were conducted using SPSS (IBM SPSS Statistics for Windows, versions 25.0 and 27.0. Armonk, NY, USA). Results Group demographics Weight, BMI, body fat percentage, and waist-to-hip ratio were higher and height lower in the FM group, but there was no difference in FFM between the groups. Patients with FM had higher STAI-trait scores, were less likely to be working, had fewer years of education, and had more comorbidities (the three most common being migraine, asthma, and gastroesophageal reflux) than controls. No significant differences were observed in the baseline spirometry values. Background data and spirometry values are shown in Table 1. Self-reported total and light LTPA were similar between groups, but moderate to heavy LTPA was significantly lower in the FM group (Fig. 2). LTPA data were missing for four participants in the FM group.Table 1 Participant data on demography and spirometry Fibromyalgia (n = 35) Missing (n) Controls (n = 23) Missing (n) P Demographic data  Age (years) 48.0 [43.1–56.5] 51.1 [39.5–53.7] 0.867a  Height (cm) 165 ± 5 168 ± 4 0.032*  Weight (kg) 77.0 ± 15.7 68.5 ± 10.2 0.016*  BMI (kg·m−2) 28.4 ± 5.6 24.4 ± 3.4 0.002*  Body fat (%) 38 ± 8 30 ± 8  < 0.001*  Fat-free mass (kg) 46.7 ± 5.2 47.3 ± 3.7 0.605  Waist-to-hip ratio 0.89 [0.82–0.94] 1 0.80 [0.78–0.85]  < 0.001a*  Smoking 6 (17) 1 (4) 0.226b  Working 22 (65) 1 23 (100)  < 0.001b*  Education (years after basic education) 4.7 ± 3.1 8.3 ± 2.1  < 0.001*  Number of other diagnoses 2 [1–3] 0 [0–1]  < 0.001a*  ACR 2016 diagnosis 32 (91) 0 (0)  < 0.001b*  ACR 2016 WPI 11 [8–15] 1 [0–2]  < 0.001a*  ACR 2016 SS 8 [5–9] 2 [1–3]  < 0.001a*  ACR 1990 tenderpoint count 16 [13–18] 3 [1–6]  < 0.001a*  FIQ 43 ± 15 1 n/a n/a  PCS 15 [10–23] n/a n/a  STAI-trait 46 ± 10 1 28 ± 6 1  < 0.001 Spirometry  FVC (L) 3.51 ± 0.45 3.68 ± 0.43 0.173  FVC (% ref. value) 96.0 ± 11.4 96.7 ± 11.2 0.827  FEV1 (L) 2.73 ± 0.42 2.92 ± 0.37 0.080  FEV1/FVC 0.78 ± 0.08 0.79 ± 0.06 0.340  PEF (L∙min−1) 6.40 ± 0.68 6.77 ± 0.96 0.118 Parametric data expressed as mean ± SD, nonparametric data as median [interquartile range], and categorical data as count (%). P values refer to unpaired t-test, except for a, refers to Mann–Whitney U Test, and b, refers to Pearson Χ2 or Fisher’s Exact Test ACR American College of Rheumatology, WPI Widespread Pain Index, SS Symptom Severity, FIQ Fibromyalgia Impact Questionnaire, PCS Pain Catastrophizing Scale, STAI State-Trait Anxiety Inventory, FVC forced vital capacity, FEV1 forced expiratory volume in one second, PEF peak expiratory flow *P < 0.05 aMann-Whitney U Test bPearson Χ2 or Fisher’s Exact Test Fig. 2 Self-reported leisure-time physical activity. White boxes, fibromyalgia (n = 31); shaded boxes, controls (n = 23). *, between-group difference significant (P < 0.05). Dashed line represents the lower bound of the WHO recommendations for moderate physical activity (see reference 53) Baseline heart rate, blood pressure, lactate and pyruvate at rest HR (85 ± 13 bpm vs. 80 ± 12 bpm, P = 0.145), SAP (124 [117–140] mmHg vs. 118 [111–137] mmHg, P = 0.112), and DAP (90 ± 8 mmHg vs. 85 ± 9 mmHg, P = 0.072) were not significantly different between FM and control groups, whereas mean arterial pressure (100 [96–109] mmHg vs. 96 [91–102] mmHg, P = 0.042) was higher in the FM group. No significant differences emerged in resting lactate (0.9 [0.7–1.2] mmol∙L−1 vs. 0.9 [0.7–1.2] mmol∙L−1, P = 0.694), pyruvate (92 [82–98] µmol∙L−1 vs. 91 [80–100] µmol∙L−1, P = 0.920), or L/P ratio (10.6 [8.3–12.9] vs. 10.8 [8.6–13.0], P = 0.610) between the groups. Lactate and pyruvate data were missing for four participants in both groups. Responses to incremental exercise Figure 3 illustrates the exercise responses for V˙O2 and its contributing factors. Significant group*work rate interactions were observed in V˙O2, V˙O2i, Q˙, Q˙ i, and C(a-v)O2, although the between-group differences were small at submaximal work rates. C(a-v)O2 slopes of the two groups were almost identical until peak exercise. SpO2 was within normal range throughout the exercise in both groups, but a group*work rate interaction was noted. Other cardiovascular response slopes are shown in Fig. 4. HR in the FM group was lower at peak exercise, and a significant group*work rate interaction was observed. MAP, SV, SVi, SVR, and SVRi showed no significant group*work rate interactions.Fig. 3 Oxygen uptake (A-B), cardiac output (C-D), arteriovenous oxygen difference (E), and arterial oxygen saturation (F) as a function of work rate. White circles (○), fibromyalgia (n = 35); black circles (●), controls (n = 23). Values are group means, vertical error bars ± SD. Horizontal error bars represent ± SD of mean peak work rate. P values refer to repeated measures ANOVA. *, between-group difference significant (P < 0.05) at given work rate Fig. 4 Heart rate (A), mean arterial pressure (B), systemic vascular resistance (C-D), and stroke volume (E–F) as a function of work rate. White circles (○), fibromyalgia (n = 35); black circles (●), controls (n = 23). Values are group means, vertical error bars ± SD. Horizontal error bars represent ± SD of mean peak work rate. P values refer to repeated measures ANOVA. *, between-group difference significant (P < 0.05) at given work rate Ventilatory thresholds Participants with FM reached both VT1 and VT2 at lower work rates (51 ± 17 W vs. 65 ± 23 W, P = 0.009, and 93 ± 22 W vs. 118 ± 23 W, P < 0.001) and lower oxygen consumption (13 ± 4 mL∙min−1∙kg−1 vs. 16 ± 5 mL∙min−1∙kg−1, P = 0.008, and 20 ± 5 mL∙min−1∙kg−1 vs. 25 ± 6 mL∙min−1∙kg−1, P < 0.001) than controls. When adjusted for FFM, the difference in oxygen consumption at VT1 was no longer significant (21 ± 5 mL∙min−1∙kg FFM−1 vs. 23 ± 5 mL∙min−1∙kg FFM−1, P = 0.176), but significance remained at VT2 (32 ± 6 mL∙min−1∙kg FFM−1 vs. 35 ± 6 mL∙min−1∙kg FFM−1, P = 0.034). V˙O2 at VTs as a percentage of V˙O2peak (VT1% and VT2%) was higher in the FM group (60 ± 9% vs. 53 ± 7%, P = 0.002, and 88 ± 8% vs. 81 ± 6%, P < 0.001). VTs could not be determined for one participant in the FM group, as no clear breakpoints were visible. Peak exercise Peak RER and RPE between the groups were comparable. Altogether 25 participants (71%) in the FM group and 21 (91%) in the control group (Fisher’s exact test, P = 0.099) fulfilled the RER criteria for maximal effort. Peak HR (HRpeak) and HR as a percentage of predicted heart rate were lower and breathing reserve (BR) higher in the FM group. Peak work rate (Ppeak), V˙O2, V˙O2i, V˙CO2, and V˙E were lower in the FM group. PETO2 was lower (117 ± 5 mmHg vs. 120 ± 4 mmHg, P = 0.020) and PETCO2 higher (35 ± 4 mmHg vs. 33 ± 3 mmHg, P = 0.014) in the FM group. No significant differences were seen in peak V˙E/V˙CO2, V˙E/V˙O2, VD/VT, or SpO2 between FM and control groups. Peak SAP, DAP, and MAP were similar between groups. Oxygen pulse was slightly lower in the FM group (10.5 ± 2.2 mL∙beat−1 vs. 11.7 ± 2.1 mL∙beat−1, P = 0.028). Q˙ was lower in the FM group but failed to reach statistical significance when adjusted for FFM (Q˙ i). Neither SV nor SVi were significantly different between groups at peak exercise. SVR was higher in the FM group, but SVRi failed to reach statistical significance. A significant difference was seen in C(a-v)O2 at peak exercise. Peak exercise results for key parameters are shown in Table 2. Peak exercise responses and between group differences remained similar when those not reaching maximal effort were excluded (columns FMme and CTRLme in Table 2).Table 2 Values at peak exercise Fibromyalgia (n = 35) Controls (n = 23) P FMme (n = 25) CTRLme (n = 21) P Work rate (W) 111 ± 23 155 ± 28  < 0.001* 111 ± 22 153 ± 28  < 0.001* RPE (Borg) 18 [17–19] 19 [18–19] 0.304a 19 [17–20] 19 [18–19] 0.794a V˙O2 (L∙min−1) 1.66 ± 0.35 2.08 ± 0.44  < 0.001* 1.65 ± 0.32 2.05 ± 0.44  < 0.001* V˙O2 (mL∙min−1∙kg−1) 22.2 ± 5.1 31.1 ± 7.9  < 0.001* 22.5 ± 5.3 29.9 ± 7.1  < 0.001* V˙O2i (mL∙min−1∙kg FFM−1) 35.7 ± 7.1 44.0 ± 8.6  < 0.001* 35.3 ± 6.5 42.9 ± 8.0  < 0.001* V˙CO2 (L∙min−1) 1.94 ± 0.42 2.39 ± 0.45 0.001* 1.99 ± 0.42 2.38 ± 0.48 0.005* V˙E (L∙min−1) 67.1 ± 13.9 87.0 ± 17.0  < 0.001* 69.0 ± 12.3 86.5 ± 17.6  < 0.001* V˙E/V˙O2 40.8 ± 7.1 42.1 ± 4.3 0.402 42.6 ± 7.3 42.5 ± 4.3 0.956 V˙E/V˙CO2 34.9 ± 5.2 36.6 ± 3.7 0.159 35.4 ± 5.7 36.5 ± 3.8 0.447 RER 1.14 [1.09–1.21] 1.15 [1.11–1.18] 0.943a 1.17 [1.14–1.26] 1.15 [1.12–1.18] 0.127a Breathing reserve (%) 33 ± 0.18 20 ± 0.13 0.004* 30 ± 18 20 ± 14 0.026* VD/VT 0.14 [0.12–0.17] 0.14 [0.12–0.15] 0.581a 0.14 [0.12–0.18] 014 [0.12–0.16] 0.556a SpO2 (%) 97 [96–98] 97 [96–98] 0.404a 97 [96–98] 97 [96–98] 0.195a Heart rate (bpm) 167 [149–171] 174 [169–187] 0.001a* 168 [150–179] 174 [167–184] 0.020a* Heart rate (% of predicted max.) 90 ± 9 97 ± 6 0.001* 91 ± 8 97 ± 5 0.011* Systolic blood pressure (mmHg) 180 ± 25 183 ± 22 0.676 180 ± 25 184 ± 23 0.625 Diastolic blood pressure (mmHg) 89 ± 9 83 ± 15 0.090 91 ± 10 85 ± 13 0.103 Mean arterial pressure (mmHg) 120 ± 12 117 ± 13 0.347 120 ± 12 118 ± 12 0.462 SV (mL) 87 [82–96] 88 [86–98] 0.541a 87 [82–95] 88 [86–99] 0.384a SVi (mL∙kg FFM−1) 1.97 ± 0.31 1.92 ± 0.30 0.493 1.97 ± 0.30 1.91 ± 0.30 0.497 Q˙ (L∙min−1) 14.2 [13.3–16.0] 16.1 [15.2–17.0] 0.005a* 14.1 [13.4–15.9] 16.1 [15.1–16.9] 0.018a* Q˙i (mL∙kg FFM−1) 318 ± 45 337 ± 55 0.148 320 ± 45 332 ± 52 0.416 SVR (mmHg∙min∙L−1) 7.84 ± 1.19 7.11 ± 1.27 0.032* 7.82 ±  < 1.12 7.24 ± 1.23 0.103 SVRi (mmHg∙min∙kg FFM∙L−1) 365 ± 64 337 ± 65 0.107 364 ± 55 344 ± 60 0.243 C(a-v)O2 (mL O2 ∙100 mL blood−1) 11.6 ± 2.7 13.3 ± 3.1 0.031* 11.4 ± 2.7 13.3 ± 3.1 0.031* Parametric data expressed as mean ± SD and nonparametric data as median [interquartile range]. P values refer to unpaired t-test, except for a, refers to Mann–Whitney U test FMme maximal effort fibromyalgia group, CTRLme maximal effort control group, RPE rate of perceived exertion, V˙O2 oxygen uptake, V˙CO2 carbon dioxide production, V˙E ventilation, RER respiratory exchange ratio, VD/VT dead space to tidal volume ratio, SpO2 oxygen saturation, SV stroke volume, SVi stroke volume index, Q˙ cardiac output, Q˙i cardiac output index, SVR systemic vascular resistance, SVRi systemic vascular resistance index, C(a-v)O2 arteriovenous oxygen difference *P < 0.05 aMann Whitney U Test Postexercise lactate, pyruvate and L/P ratio The FM group had lower postexercise lactate concentration (8.1 [6.1–10.0] mmol∙L−1 vs. 11.1 [9.1–12.5] mmol∙L−1, P = 0.003) and L/P ratio (58.6 [44.5–78.6] vs. 71.4 [59.4–88.3], P = 0.032), while postexercise pyruvate concentrations were similar (140 [123–155] µmol∙L−1 vs. 155 [122–167] µmol∙L−1, P = 0.184) between groups. Data were missing for four participants in both groups. ΔV˙O2/ΔP, ΔHR/ΔV˙O2, ΔQ˙/ΔV˙O2, and ΔV˙E/ΔV˙CO2 slopes ΔV˙O2/ΔP, ΔHR/ΔV˙O2, ΔQ˙/ΔV˙O2, and ΔV˙ E/ΔV˙CO2 slopes were similar between groups, and the FM*independent variable interactions were not significant. Linear regression slopes are shown in Fig. 5.Fig. 5 Linear regression slopes for oxygen uptake as a function of work rate (A), heart rate (B) and cardiac output (C) as a function of oxygen uptake, and ventilation as a function of carbon dioxide production (ventilatory efficacy) (D). White circles (○), fibromyalgia (n = 35, except for panel D, n = 34); black circles (●), controls (n = 23). P values refer to the group*independent variable term in the regression model (see text for more information) Pain The FM group reported higher pain NRS at rest (3 [2–5] vs. 0 [0–0], P < 0.001) and after exercise (5.5 [3–8] vs. 0 [0–1], P < 0.001), with a median change of 2 (Wilcoxon Signed-Rank Test, P < 0.001). Of the FM patients, 24 (71%) experienced an increase in pain, whereas 8 (24%) reported no change and 2 (6%) a decrease in pain. Data were missing for one participant in the FM group. In the FM group, a negative correlation with baseline pain NRS and V˙O2peak (ρ = -0.46, P = 0.007) and PPeak (ρ = -0.43, P = 0.011) was observed. Postexercise pain NRS correlated negatively only with V˙O2peak (ρ = -0.40, P = 0.018). No significant associations emerged between the change in pain ratings (post–pre) and V˙O2peak (ρ = -0.23, P = 0.183) or Ppeak (ρ = -0.12, P = 0.493). Neither baseline nor postexercise pain NRS correlated with HRpeak (ρ = -0.31, P = 0.079 and ρ = -0.16, P = 0.355). Correlations between LTPA, V˙O2peak, Ppeak, HRpeak, C(a-v)O2, Q˙ peak and background data A positive correlation was observed with Q˙ peak and V˙O2ipeak (ρ = 0.30, P = 0.022) but not with V˙O2peak (ρ = 0.25, P = 0.058). Moderate to heavy LTPA correlated with V˙O2peak (ρ = 0.60, P < 0.001), HRpeak (ρ = 0.37, P = 0.005), and Ppeak (ρ = 0.55, P < 0.001) and total LTPA with V˙O2peak (ρ = 0.34, P < 0.013). However, no correlation was observed between light LTPA and V˙O2peak (ρ = 0.03, P = 0.839), HRpeak (ρ = -0.21, P = 0.129) or PPeak (ρ = -0.02, P = 0.906). Peak C(a-v)O2 and Q˙ peak correlated only with moderate to heavy LTPA (ρ = 0.35, P = 0.010 and ρ = 0.33, P = 0.016). When excluding the controls, a significant correlation remained only with total LTPA and V˙O2peak (ρ = 0.37, P = 0.040) and moderate to heavy LTPA with V˙O2ipeak (ρ = 0.53, P = 0.002). FIQ, PCS, STAI-trait, ACR 2016 WPI, or ACR 2016 SS did nor correlate with V˙O2peak, Ppeak, HRpeak or LTPA in the FM group (data not shown). Demographic differences in submaximal and maximal effort FM groups The submaximal group had higher FIQ and STAI-trait scores. More participants in the submaximal group had a pulmonary diagnosis compared with the maximal group. Altogether eight FM patients had pulmonary comorbidities (asthma, n = 7; sleep apnea, n = 2; both, n = 1). Of the seven patients with concurrent FM and asthma, two reached maximal effort. No significant differences emerged in baseline spirometry between asthmatic and non-asthmatic FM patients or between submaximal and maximal groups (data not shown). Group demographics are shown in Table 3.Table 3 Comparison of submaximal versus maximal effort fibromyalgia groups Submaximal (n = 11) Missing (n) Maximal (n = 27) Missing (n) P Age (years) 43.3 ± 9.9 48.8 ± 10.6 0.154 Height (cm) 165 ± 5 165 ± 5 0.969 Weight (kg) 78.3 ± 11.9 76.3 ± 17.9 0.741 BMI (kg·m−2) 30.6 [23.2–31.5] 26.1 [22.9–33.6] 0.573a Fat free mass (kg) 46.2 ± 4.2 47.4 ± 5.9 0.529 Smoking 3 (27) 4 (15) 0.390b ACR 2016 diagnosis 10 (91) 24 (89) 1.000b FIQ 50 ± 11 39 ± 16 1 0.043* PCS 14 [11–27] 15 [10–23] 0.540a STAI-trait 51 ± 5 42 ± 11 1 0.012* Pain NRS at rest 3 [2–5] 3 [2–5] 1 0.402b Postexercise pain NRS 6 [3–8] 5 [3–8] 1 0.802a Comorbidities  Cardiovascular 1 (9) 2 (7) 1.000b  Endocrinological 0(0) 7 (26) 0.084b  Psychiatric 2 (18) 3 (11) 0.615b  Pulmonary 5 (46) 3 (11) 0.031b*  Neurological 5 (46) 9 (33) 0.482b  Total diagnoses count 2 [1–4] 2 [0–3] 0.242a Medications  Antidepressant 4 (36) 17 (63) 0.167b  Opioid 2 (18) 4 (15) 1.000b  Anticonvulsant 5 (46) 8 (30) 0.457b Parametric data expressed as mean ± SD, nonparametric data as median [interquartile range] and categorical data as count (%). P values refer to unpaired t-test, except for a, refers to Mann–Whitney U test, and b, refers to Pearson Χ2 or Fisher’s Exact Test ACR American College of Rheumatology, WPI widespread pain index, SS symptom severity, FIQ Fibromyalgia Impact Questionnaire, PCS Pain Catastrophizing Scale, STAI State-Trait Anxiety Inventory, NRS numeric rating scale *P < 0.05 aMann-Whitney U Test bPearson Χ2 or Fishers's Exact Test Discussion Main results The 29% lower V˙O2peak (mL∙min-1∙kg-1) in FM patients in this study is in concordance with previous studies where a cycle ergometer exercise was used [41–43]. The between-group difference in V˙O2peak did not dissipate when adjusted for FFM, demonstrating that lower V˙O2peak in the FM group was not related to body composition. In healthy fit subjects, V˙O2peak is limited primarily by Q˙, whereas mitochondrial oxidative capacity is the primary limiting factor in unfit subjects [44]. It should be noted that although Q˙ and C(a-v)O2 are separate factors in the Fick principle, there is interdependence between the two variables [45]. In this study, both central (Q˙ 12% and Q˙ i 6% lower in the FM group) and peripheral (C(a-v)O2 13% lower in the FM group) mechanisms contributed to lower V˙O2peak in FM, although the difference in peak Q˙ i was not statistically significant. Q˙ (a product of HR and SV), in turn, was limited by HRpeak, while SV was similar between groups. Lower HRpeak is a common finding in FM exercise studies [41, 42, 46–48]. In addition to submaximal effort, lower HR has been proposed to be a consequence of metabolic impairment and dysregulation of the autonomic nervous system [42, 47, 48]. We examined the associations between HRpeak respectively with pain ratings, LTPA, and symptom severity in the FM group, but we did not find any correlations. V˙O2peak and Ppeak, however, were negatively associated with baseline pain ratings. C(a-v)O2 is affected by not only oxygen extraction and muscle oxidative capacity but also vascular function and blood flow distribution. Exercise increases bloodflow to the working muscles via peripheral vasodilatation, while sufficient vascular resistance needs to be maintained to ensure adequate MAP [49]. MAP and SVR responses to incremental exercise were similar between groups (Fig. 4 B-D), indicating functioning vascular control in FM at a whole-body level. Additionally, lower C(a-v)O2 could be a consequence of lower mitochondrial oxidative phosphorylation and oxygen demand or lower capillary density in the exercising muscle. Muscle capillary density [50], mitochondrial function [51], and hence the capability for greater oxygen extraction are increased with exercise training, while deconditioning reduces mitochondrial enzymatic activity [51]. We did not, however, find significant correlations between LTPA and C(a-v)O2 when analyzing the FM group. Obesity does seem to affect C(a-v)O2 [52], but if this were the case, we would have expected to see a difference in C(a-v)O2 already at submaximal workloads. This study does not provide an explanation for the lower C(a-v)O2, and in clinical settings differentiating mild myopathies from deconditioning may be problematic [18]. However, given the similar resting lactate and L/P ratio, V˙O2i at VT1, ΔV˙O2/ΔP, peak V˙E/V˙O2, and RER between groups and the lower peak lactate and peak L/P ratio in the FM group, our data do not suggest an impairment in muscle metabolism. Participants in the FM group reported low moderate to heavy LTPA and failed to meet the WHO physical activity recommendation of 150 to 300 min of weekly moderate exercise [53]. A recent study [54] in a Swiss population demonstrated positive associations of moderate and vigorous, but not light, physical activity with V˙O2peak. Correlation analysis in our study yielded similar results, suggesting that low moderate to heavy LTPA is a plausible explanation for the lower V˙O2peak in the FM group. A few previous studies have reported exercise thresholds (ventilatory or lactate) in FM patients [5, 41, 43, 46]. Regardless of the definition and method used, they show consistently that FM patients reach these thresholds at lower V̇O2 and work rate. Paradoxical to the fact that exercise training shifts VTs closer to V˙O2peak [55], VT1% and VT2% in our study were higher in the FM group, while VTs in absolute terms were lower. This is consistent with the study by Valim et al. [46]. Higher relative VTs could be explained by submaximal exercise effort, which is supported by the notion that HRpeak in relation to predicted maximal HR was lower and peak BR higher in the FM group. Submaximal effort of FM patients has been reported earlier [42, 43, 46]. The concept of maximal effort and the issue of possible submaximal effort in the FM group needs to be addressed. Maximal oxygen uptake (V˙O2max) is an important measure of cardiorespiratory fitness representing maximal level of oxidative metabolism. A plateau in V˙O2 occurs near maximal exercise and this is traditionally considered to be the best evidence of achieved V˙O2max [56]. However, a clear plateau is often not achieved [57], and V˙O2peak is used instead of V˙O2max. In case a V˙O2 plateau is not attained, secondary criteria are used to determine maximal effort. These criteria most commonly include one or more of the following: HR ≤ 10 - 15 bpm or ≤ 5 - 10% of the age-predicted (220-age) maximum, blood lactate concentration ≥ 8 mM, or RER ≥ 1.00, 1.05, 1.10, or 1.13 [57]. Although low HRpeak in the FM group points towards a less than maximal effort, we argue that our peak exercise comparisons are justified. First, peak mean RER and RPE between FM and control groups were alike, indicating similar maximal effort. Second, the median postexercise lactate was ≥ 8 mM in both groups. Third, the between-group differences in peak exercise responses did not substantially change even when those not reaching maximal effort were excluded from the analysis (Table 2). Furthermore, even though we used relatively strict RER-criteria, defining maximal exercise effort using secondary criteria (including RER and HR) is ambiguous [58]. The exercise responses recorded in this study do not represent their theoretical maximum but rather demonstrate the highest achievable response in the existing circumstances, i.e., peak values. The FM patients had a pronounced, albeit not significantly different, circulatory response to increasing oxygen demand, which manifested as steeper ΔHR/ΔV˙O2 (similarly to ref. [42]) and ΔQ˙/ΔV˙O2 slopes. Q˙ is increased approximately five liters per increased liter of V˙O2 [49]. Although in this study the slope of the FM group was steeper (6.6 L blood / 1 L V˙O2), the value falls within one SD of the mean of healthy subjects in the study by Beck et al. [59]. The ΔHR/ΔV˙O2 slope is also well within the normal range of the recently published reference values [60]‬.‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬ We noted a possible association between the ability to reach maximal effort and FIQ and STAI-trait (Table 3), although neither FIQ nor STAI-trait correlated with V˙O2peak. In contrast, others have reported an association between cardiorespiratory fitness (assessed by the 6-min walk test) and STAI [61] as well as disease severity (assessed by the Revised Fibromyalgia Impact Questionnaire (FIQR) [62] in FM. As mentioned earlier, difficulties in reaching maximal effort in patients with FM has been reported before, but this has not been connected to disease severity or psychological factors. The notion that asthma, even when controlled, could affect exercise effort is not surprising considering the myriad ways, including the fear of triggering symptoms, that asthma can affect physical capacity [63]. In addition, even though the resting spirometry of the asthmatic participants was normal, we cannot rule out exercise-induced bronchial reactivity, as postexercise spirometry was not measured. Strengths and limitations Although the sample size was adequate for the primary outcomes, the subgroups in our secondary analysis were small, diminishing statistical reliability. The patient and control groups were not entirely homogeneous regarding their anthropometrics, educational and employment status. This reflects real-life differences between patients with FM and their same-aged peers. Although obesity has a multitude of systemic effects, adipose tissue does not affect oxygen uptake during exercise, and V˙O2 between obese and lean subjects is similar when corrected for FFM [64, 65]. Gathering LTPA data with more objective methods, such as accelerometers, would yield more reliable results. Patients with FM may be inaccurate in estimating their physical activity, but overreporting of moderate and vigorous activity is observed also in healthy individuals [9].The questionnaires were not completed at the time of the exercise test. Nevertheless, FIQ, PCS, and STAI-trait seem to be relatively stable over time [23, 66, 67]. Although studies on the PhysioFlow impedance cardiography have proven acceptable reliability in both healthy subjects and pulmonary patients and in submaximal as well as maximal exercise [34, 68, 69], other studies have shown overestimation of cardiac output in chronic obstructive pulmonary disease [70] and chronic heart failure patients [71]. Moreover, the subjects of the aforementioned studies are predominantly male, whereas participants in our study were women. As we have not measured C(a-v)O2 directly, but rather solved it from the Fick equation, any imprecision in measuring cardiac output would additionally impact our C(a-v)O2 results. The study population consisted of only women, and our results cannot be extrapolated to male FM patients. The main strength of this study lies in the simultaneous recording of ventilatory gas exchange and ICG data. To the best of our knowledge, exercise responses in patients with FM have not been studied this intensively before. Conclusions Patients with FM display poor cardiorespiratory fitness and both cardiac output and arteriovenous oxygen difference were lower compared with healthy controls. Abnormal muscle metabolism seems unlikely, whereas a possible explanation for the observed lower V˙O2peak is deconditioning and less moderate to heavy LTPA. Abbreviations FM Fibromyalgia V˙O2 Oxygen uptake Q˙  Cardiac output C(a-v)O2 Arteriovenous oxygen difference FFM Fat-free body mass SD Standard deviation V˙O2peak Peak oxygen uptake MM Mitochondrial myopathy CPET Cardiopulmonary exercise test RER Respiratory exchange ratio HR Heart rate P Work rate VT Ventilatory threshold SV Stroke volume SVR Systemic vascular resistance V˙E Ventilation V˙CO2 Carbon dioxide production LTPA Leisure-time physical activity ACR American College of Rheumatology FIQ Fibromyalgia Impact Questionnaire PSS Perceived Stress Scale STAI State-trait Anxiety Inventory PCS Pain Catastrophizing Scale WPI Widespread Pain Index SS Symptom Severity BMI Body-mass index RPE Rate of perceived exertion NRS Numeric rating scale L/P Lactate-to-pyruvate ratio VT1 First ventilatory threshold VT2 Second ventilatory threshold SpO2 Arterial oxygen saturation ICG Impedance cardiography SAP Systolic arterial blood pressure DAP Diastolic arterial blood pressure MAP Mean arterial pressure ANOVA Analysis of Variance MANOVA Multivariate analysis of variance V˙O2i Oxygen uptake index Q˙i Cardiac output index SVi Stroke volume index SVRi Systemic vascular resistance index VT1% Oxygen uptake at first ventilatory threshold as a percentage of peak oxygen uptake VT2% Oxygen uptake at second ventilatory threshold as a percentage of peak oxygen uptake BR Breathing reserve PETO2 End-tidal oxygen partial pressure PETCO2 End-tidal carbon dioxide partial pressure VD/VT Dead space to tidal volume ratio FMme Maximal effort fibromyalgia group CTRLme Maximal effort control group WHO World Health Organization V˙O2max Maximal oxygen uptake Acknowledgements The authors thank all staff at the Helsinki Sports and Exercise Medicine Clinic and the participants in this study for their time and effort. Authors’ contributions HT, EK, JEP, RM, and TZ conceived and designed research; TZ recruited the study participants; TL analyzed data; TL and JEP interpreted results of experiments; TL prepared figures; TL drafted manuscript; TL, TZ, JA, RM, HT, EK, and JEP, edited and revised manuscript. All authors read and approved the final manuscript. Funding This study was supported by Finnish State Research Funding (TYH2017215), the Signe and Ane Gyllenberg Foundation, the Department of Internal Medicine and Rehabilitation, Helsinki University Hospital (HUS 76/2018 § 11, HUS 174/2019 § 1), and the Ministry of Education and Culture, Finland. Open access funded by Helsinki University Library. Availability of data and materials The datasets generated and analyzed during the current study are not publicly available as consent for this was not asked from the study subjects. The data are available from the corresponding author on reasonable request if also approved by our ethics committee. Declarations Ethics approval and consent to participate The study was conducted in accordance with the Declaration of Helsinki and all subjects provided written consent. The study protocol was approved by the Ethics Committee of the Helsinki and Uusimaa Hospital District and it was registered in ClinicalTrials.gov (NCT03300635). Consent for publication Not applicable. Competing interests Eija Kalso serves on the advisory boards of Orion Pharma and Pfizer and has received a lecture fee, unrelated to this work, from GSK. Ritva Markkula has received lecture fees, unrelated to this work, from Oy Eli Lilly Finland Ab. The other authors have no potential conflicts of interest to declare. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Taneli Lehto and Teemu Zetterman as well as Eija Kalso and Juha E. Peltonen equally contributed this works. ==== Refs References 1. Sarzi-Puttini P Giorgi V Marotto D Atzeni F Fibromyalgia: an update on clinical characteristics, aetiopathogenesis and treatment Nat Rev Rheumatol 2020 16 11 645 660 10.1038/s41584-020-00506-w 33024295 2. Yunus MB Kalyan-Raman UP Kalyan-Raman K Masi AT Pathologic changes in muscle in primary fibromyalgia syndrome Am J Med 1986 81 3A 38 42 10.1016/0002-9343(86)90872-7 3464207 3. Macfarlane GJ Kronisch C Dean LE Atzeni F Häuser W Fluß E EULAR revised recommendations for the management of fibromyalgia Ann Rheum Dis 2017 76 2 318 328 10.1136/annrheumdis-2016-209724 27377815 4. Taylor SJ Steer M Ashe SC Furness PJ Haywood-Small S Lawson K Patients’ perspective of the effectiveness and acceptability of pharmacological and non-pharmacological treatments of fibromyalgia Scand J Pain 2019 19 1 167 181 10.1515/sjpain-2018-0116 30315738 5. Bardal EM Roeleveld K Mork PJ Aerobic and cardiovascular autonomic adaptations to moderate intensity endurance exercise in patients with fibromyalgia J Rehabil Med 2015 47 7 639 646 10.2340/16501977-1966 26035415 6. Häkkinen A Häkkinen K Hannonen P Alen M Strength training induced adaptations in neuromuscular function of premenopausal women with fibromyalgia: comparison with healthy women Ann Rheum Dis 2001 60 1 21 26 10.1136/ard.60.1.21 11114277 7. Gaudreault N Boulay P Cardiorespiratory fitness among adults with fibromyalgia Breathe 2018 14 2 e25 33 10.1183/20734735.019717 30131831 8. Hooten M Smith J Eldrige J Olsen D Mauck WD Moeschler S Pain severity is associated with muscle strength and peak oxygen uptake in adults with fibromyalgia J Pain Res 2014 7 237 10.2147/JPR.S61312 24833914 9. McLoughlin MJ Colbert LH Stegner AJ Cook DB Are women with fibromyalgia less physically active than healthy women? Med Sci Sports Exerc 2011 43 5 905 912 10.1249/MSS.0b013e3181fca1ea 20881881 10. Wolfe F Hassett AL Walitt B Michaud K Mortality in fibromyalgia : a study of 8,186 patients over thirty-five years Arthritis Care Res (Hoboken) 2011 63 1 94 101 10.1002/acr.20301 20662040 11. Ross R Blair SN Arena R Church TS Després J-P Franklin BA Importance of assessing cardiorespiratory fitness in clinical practice: a case for fitness as a clinical vital sign: a scientific statement from the American heart association Circulation 2016 134 24 e653 e699 10.1161/CIR.0000000000000461 27881567 12. Sprott H Salemi S Gay RE Bradley LA Alarcón GS Oh SJ Increased DNA fragmentation and ultrastructural changes in fibromyalgic muscle fibres Ann Rheum Dis 2004 63 3 245 251 10.1136/ard.2002.004762 14962957 13. Cordero MD De Miguel M Moreno Fernández AM Carmona López IM Garrido Maraver J Cotán D Mitochondrial dysfunction and mitophagy activation in blood mononuclear cells of fibromyalgia patients: implications in the pathogenesis of the disease Arthritis Res Ther 2010 12 1 R17 10.1186/ar2918 20109177 14. Sánchez-Domínguez B Bullón P Román-Malo L Marín-Aguilar F Alcocer-Gómez E Carrión AM Oxidative stress, mitochondrial dysfunction and inflammation common events in skin of patients with Fibromyalgia Mitochondrion 2015 21 69 75 10.1016/j.mito.2015.01.010 25662535 15. Cordero MD Alcocer-Gómez E Marín-Aguilar F Rybkina T Cotán D Pérez-Pulido A Mutation in cytochrome b gene of mitochondrial DNA in a family with fibromyalgia is associated with NLRP3-inflammasome activation J Med Genet 2016 53 2 113 122 10.1136/jmedgenet-2015-103392 26566881 16. Gerdle B Ghafouri B Lund E Bengtsson A Lundberg P van Ettinger-Veenstra H Evidence of mitochondrial dysfunction in fibromyalgia: deviating muscle energy metabolism detected using microdialysis and magnetic resonance J Clin Med 2020 9 11 3527 10.3390/jcm9113527 33142767 17. van Tilburg MAL Parisien M Boles RG Drury GL Smith-Voudouris J Verma V A genetic polymorphism that is associated with mitochondrial energy metabolism increases risk of fibromyalgia Pain 2020 161 12 2860 2871 10.1097/j.pain.0000000000001996 32658146 18. Riley MS Nicholls DP Cooper CB Cardiopulmonary exercise testing and metabolic myopathies Ann Am Thorac Soc 2017 14 S129 S139 10.1513/AnnalsATS.201701-014FR 28590155 19. Taivassalo T Jensen TD Kennaway N DiMauro S Vissing J Haller RG The spectrum of exercise tolerance in mitochondrial myopathies: A study of 40 patients Brain 2003 126 2 413 423 10.1093/brain/awg028 12538407 20. Noury JB Zagnoli F Petit F Marcorelles P Rannou F Exercise efficiency impairment in metabolic myopathies Sci Rep 2020 10 1 1 9 10.1038/s41598-020-65770-y 31913322 21. Zetterman T Markkula R Partanen JV Miettinen T Estlander AM Kalso E Muscle activity and acute stress in fibromyalgia BMC Musculoskelet Disord 2021 22 1 1 13 10.1186/s12891-021-04013-1 33397351 22. Wolfe F Smythe HA Yunus MB Bennett RM Bombardier C Goldenberg DL The American college of rheumatology 1990 criteria for the classification of fibromyalgia. Report of the multicenter criteria committee Arthritis Rheum 1990 33 2 160 172 10.1002/art.1780330203 2306288 23. Gauffin J Hankama T Kautiainen H Marja A-K Hannonen P Haanpää M Validation of a Finnish version of the Fibromyalgia Impact Questionnaire (Finn-FIQ) Scand J Pain 2012 3 1 15 20 10.1016/j.sjpain.2011.10.004 29913759 24. Cohen S Kamarck T Mermelstein R A global measure of perceived stress J Health Soc Behav 1983 24 4 385 396 10.2307/2136404 6668417 25. Spielberger CD Gorsuch RL Lushene RE STAI manual for the state-trait anxiety inventory: (“Self-evaluation questionnaire”) 1970 Palo Alto Consulting Psychologists Press 26. Sullivan MJL Bishop SR Pivik J The pain catastrophizing scale: development and validation Psychol Assess 1995 7 4 524 532 10.1037/1040-3590.7.4.524 27. Wolfe F Clauw DJ Fitzcharles MA Goldenberg DL Häuser W Katz RL 2016 Revisions to the 2010/2011 fibromyalgia diagnostic criteria Semin Arthritis Rheum 2016 46 3 319 329 10.1016/j.semarthrit.2016.08.012 27916278 28. Peltonen JE Hägglund H Koskela-Koivisto T Koponen AS Aho JM Rissanen A-PE Alveolar gas exchange, oxygen delivery and tissue deoxygenation in men and women during incremental exercise Respir Physiol Neurobiol 2013 188 2 102 112 10.1016/j.resp.2013.05.014 23707876 29. Rissanen A-PE Koskela-Koivisto T Hägglund H Koponen AS Aho JM Pöyhönen-Alho M Altered cardiorespiratory response to exercise in overweight and obese women with polycystic ovary syndrome Physiol Rep. 2016 4 4 e12719 10.14814/phy2.12719 26884479 30. Völgyi E Tylavsky FA Lyytikäinen A Suominen H Alén M Cheng S Assessing body composition with DXA and bioimpedance: effects of obesity, physical activity, and age Obesity 2008 16 3 700 705 10.1038/oby.2007.94 18239555 31. Borg G Perceived exertion as an indicator of somatic stress Scand J Rehabil Med 1970 2 2 92 98 10.2340/1650197719702239298 5523831 32. Beaver WL Wasserman K Whipp BJ A new method for detecting anaerobic threshold by gas exchange J Appl Physiol 1986 60 6 2020 2027 10.1152/jappl.1986.60.6.2020 3087938 33. Mezzani A Cardiopulmonary exercise testing: Basics of methodology and measurements Ann Am Thorac Soc 2017 14 S3 11 10.1513/AnnalsATS.201612-997FR 28510504 34. Richard R Lonsdorfer-Wolf E Charloux A Doutreleau S Buchheit M Oswald-Mammosser M Non-invasive cardiac output evaluation during a maximal progressive exercise test, using a new impedance cardiograph device Eur J Appl Physiol 2001 85 3–4 202 207 10.1007/s004210100458 11560071 35. Lolli L Batterham AM Weston KL Atkinson G Size exponents for scaling maximal oxygen uptake in over 6500 humans: a systematic review and meta-analysis Sport Med 2017 47 7 1405 1419 10.1007/s40279-016-0655-1 36. Köhler A King R Bahls M Groß S Steveling A Gärtner S Cardiopulmonary fitness is strongly associated with body cell mass and fat-free mass: the Study of Health in Pomerania (SHIP) Scand J Med Sci Sport 2018 28 6 1628 1635 10.1111/sms.13057 37. Imboden MT Kaminsky LA Peterman JE Hutzler HL Whaley MH Fleenor BS Cardiorespiratory fitness normalized to fat-free mass and mortality risk Med Sci Sports Exerc 2020 52 7 1532 1537 10.1249/MSS.0000000000002289 31985577 38. Chantler PD Clements RE Sharp L George KP Tan LB Goldspink DF The influence of body size on measurements of overall cardiac function Am J Physiol - Hear Circ Physiol. 2005 289 5 58-5 15 21 39. Carrick-Ranson G Hastings JL Bhella PS Shibata S Fujimoto N Palmer D The effect of age-related differences in body size and composition on cardiovascular determinants of VO2max J Gerontol - Ser A Biol Sci Med Sci 2013 68 5 608 616 10.1093/gerona/gls220 23160363 40. Edvardsen E Hem E Anderssen SA End criteria for reaching maximal oxygen uptake must be strict and adjusted to sex and age: A cross-sectional study PLoS ONE 2014 9 1 18 20 10.1371/journal.pone.0085276 41. Lund E Kendall SA Janerot-Sjöberg B Bengtsson A Muscle metabolism in fibromyalgia studied by P-31 magnetic resonance spectroscopy during aerobic and anaerobic exercise Scand J Rheumatol 2003 32 3 138 145 10.1080/03009740310002461 12892249 42. Bachasson D Guinot M Wuyam B Favre-Juvin A Millet GY Levy P Neuromuscular fatigue and exercise capacity in fibromyalgia syndrome Arthritis Care Res (Hoboken) 2013 65 3 432 440 10.1002/acr.21845 22965792 43. Bardal E Olsen T Ettema G Mork P Scandinavian journal of rheumatology metabolic rate, cardiac response, and aerobic capacity in fibromyalgia: a case–control study Scand J Rheumatol 2013 42 5 417 420 10.3109/03009742.2013.767372 23527918 44. Wagner PD Modeling O2 transport as an integrated system limiting V̇O2MAX Comput Methods Progr Biomed 2011 101 2 109 114 10.1016/j.cmpb.2010.03.013 45. Poole DC Musch TI Solving the fick principle using whole body measurements does not discriminate “central” and “peripheral” adaptations to training Eur J Appl Physiol 2008 103 1 117 119 10.1007/s00421-007-0668-4 18188582 46. Valim V Oliveira LM Suda AL Silva LE Faro M Barros Neto TL Peak oxygen uptake and ventilatory anaerobic threshold in fibromyalgia J Rheumatol 2002 29 2 353 357 11842825 47. Valkeinen H Häkkinen A Alen M Hannonen P Kukkonen-Harjula K Häkkinen K Physical fitness in postmenopausal women with fibromyalgia Int J Sport Med 2008 29 408 413 10.1055/s-2007-965818 48. da Cunha Ribeiro RP Roschel H Artioli GG Dassouki T Perandini LA Calich AL Cardiac autonomic impairment and chronotropic incompetence in fibromyalgia Arthritis Res Ther 2011 13 6 R190 10.1186/ar3519 22098761 49. Joyner MJ Casey DP Regulation of increased blood flow (Hyperemia) to muscles during exercise: a hierarchy of competing physiological needs Physiol Rev 2015 95 2 549 601 10.1152/physrev.00035.2013 25834232 50. Gavin TP Kraus RM Carrithers JA Garry JP Hickner RC Aging and the skeletal muscle angiogenic response to exercise in women J Gerontol Ser A Biol Sci Med Sci 2015 70 10 1189 1197 10.1093/gerona/glu138 25182597 51. Fritzen A Thøgersen F Thybo K Vissing C Krag T Ruiz-Ruiz C Adaptations in mitochondrial enzymatic activity occurs independent of genomic dosage in response to aerobic exercise training and deconditioning in human skeletal muscle Cells 2019 8 3 237 10.3390/cells8030237 30871120 52. Vella CA Ontiveros D Zubia RY Cardiac function and arteriovenous oxygen difference during exercise in obese adults Eur J Appl Physiol 2011 111 6 915 923 10.1007/s00421-010-1554-z 21069380 53. World Health Organisation WHO guidelines on physical activity and sedentary behaviour 2020 Geneva World Health Organization. Geneva 54. Wagner J Knaier R Infanger D Königstein K Klenk C Carrard J Novel CPET reference values in healthy adults: associations with physical activity Med Sci Sports Exerc 2021 53 1 26 37 10.1249/MSS.0000000000002454 32826632 55. Davis JA Frank MH Whipp BJ Wasserman K Anaerobic threshold alterations caused by endurance training in middle-aged men J Appl Physiol 1979 46 6 1039 1046 10.1152/jappl.1979.46.6.1039 468620 56. Albouaini K Egred M Alahmar A Wright DJ Cardiopulmonary exercise testing and its application Postgrad Med J 2007 83 985 675 682 10.1136/hrt.2007.121558 17989266 57. Howley ET Bassett DR Welch HG Criteria for maximal oxygen uptake: review and commentary Med Sci Sport Exerc 1995 27 9 1292 1301 10.1249/00005768-199509000-00009 58. Poole DC Wilkerson DP Jones AM Validity of criteria for establishing maximal O 2 uptake during ramp exercise tests Eur J Appl Physiol 2008 102 4 403 410 10.1007/s00421-007-0596-3 17968581 59. Beck KC Randolph LN Bailey KR Wood CM Snyder EM Johnson BD Relationship between cardiac output and oxygen consumption during upright cycle exercise in healthy humans J Appl Physiol 2006 101 5 1474 1480 10.1152/japplphysiol.00224.2006 16873603 60. Sirichana W Neufeld EV Wang X Hu SB Dolezal BA Cooper CB Reference values for chronotropic index from 1280 incremental cycle ergometry tests Med Sci Sport Exerc 2020 52 12 2515 2521 10.1249/MSS.0000000000002417 61. Córdoba-Torrecilla S Aparicio VA Soriano-Maldonado A Estévez-López F Segura-Jiménez V Álvarez-Gallardo I Physical fitness is associated with anxiety levels in women with fibromyalgia: the al-Ándalus project Qual Life Res 2016 25 4 1053 1058 10.1007/s11136-015-1128-y 26350699 62. Soriano-Maldonado A Henriksen M Segura-Jiménez V Aparicio VA Carbonell-Baeza A Delgado-Fernández M Association of physical fitness with fibromyalgia severity in women: the al-ándalus project Arch Phys Med Rehabil 2015 96 9 1599 1605 10.1016/j.apmr.2015.03.015 25839088 63. Panagiotou M Koulouris NG Rovina N Physical activity: a missing link in asthma care J Clin Med 2020 9 3 706 10.3390/jcm9030706 32150999 64. Goran MI Fields DA Hunter GR Herd SL Weinsier RL Total body fat does not influence maximal aerobic capacity Int J Obes 2000 24 7 841 848 10.1038/sj.ijo.0801241 65. Ekelund U Franks PW Wareham NJ Åman J Oxygen uptakes adjusted for body composition in normal-weight and obese adolescents Obes Res 2004 12 3 513 520 10.1038/oby.2004.58 15044669 66. Lamé IE Peters ML Kessels AG Test – retest stability of the pain catastrophizing scale and the tampa scale for kinesiophobia in chronic pain patients over a longer period of time J Health Psychol 2008 13 6 280 826 10.1177/1359105308093866 67. Newmark CS Stability of state and trait anxiety Psychol Rep 1972 30 1 196 198 10.2466/pr0.1972.30.1.196 5012621 68. Charloux A Lonsdorfer-Wolf E Richard R Lampert E Oswald-Mammosser M Mettauer B A new impedance cardiograph device for the non-invasive evaluation of cardiac output at rest and during exercise: comparison with the “direct” Fick method Eur J Appl Physiol 2000 82 4 313 320 10.1007/s004210000226 10958374 69. Louvaris Z Spetsioti S Andrianopoulos V Chynkiamis N Habazettl H Wagner H Cardiac output measurement during exercise in COPD: A comparison of dye dilution and impedance cardiography Clin Respir J 2019 13 4 222 231 10.1111/crj.13002 30724023 70. Bougault V Lonsdorfer-Wolf E Charloux A Richard R Geny B Oswald-Mammosser M Does thoracic bioimpedance accurately determine cardiac output in COPD patients during maximal or intermittent exercise? Chest 2005 127 4 1122 1131 15821184 71. Kemps HMC Thijssen EJM Schep G Sleutjes BTHM De Vries WR Hoogeveen AR Evaluation of two methods for continuous cardiac output assessment during exercise in chronic heart failure patients J Appl Physiol 2008 105 6 1822 1829 10.1152/japplphysiol.90430.2008 18948448