Eur J Appl Physiol DOI 10.1007/s00421-015-3186-9
ORIGINAL ARTICLE
The effects of high intensity interval training in women with rheumatic disease: a pilot study Janne Sandstad1 · Dorthe Stensvold1 · Mari Hoff2,3 · Bjarne M. Nes1 · Ingerid Arbo1 · Anja Bye1,4,5
Received: 23 September 2014 / Accepted: 8 May 2015 © Springer-Verlag Berlin Heidelberg 2015
Abstract Purpose Rheumatoid arthritis (RA) and juvenile idiopathic arthritis (JIA) are inflammatory diseases which involve increased risk of cardiovascular disease (CVD). High intensity interval training (HIIT) is known to be effective in improving cardiovascular health. The aim of this study was to investigate whether 10 weeks of HIIT at 85–95 % of HRmax would improve important risk factors of CVD in rheumatic patients, and if these patients would tolerate exercise intensities above today’s recommendations. Methods Seven women with RA and eleven with adultJIA, 20–50 years, were recruited to this cross-over study. Participants performed HIIT, consisting of 4 × 4 min intervals at 85–95 % of HRmax twice a week for 10 weeks on Communicated by Keith Phillip George. Norwegian Health Association, Revmafondet (foundation for rheumatic disease in Norway), Liaison Committee between the Central Norway Regional Health Authority (RHA) and the Norwegian University of Science and Technology (NTNU). * Anja Bye
[email protected] 1
Department of Circulation and Medical Imaging, Faculty of Medicine, Medical Technology Research Centre, KG Jebsen Center of Exercise in Medicine, Norwegian University of Science and Technology (NTNU), P.O. box 8905, 7491 Trondheim, Norway
2
Department of Rheumatology, St. Olavs Hospital, Trondheim, Norway
3
Department of Public Health and General Practice, Norwegian University of Science and Technology, Trondheim, Norway
4
Norwegian Health Association, Oslo, Norway
5
St. Olavs Hospital, Trondheim, Norway
spinning bikes. Maximal oxygen uptake (VO2max), heart rate recovery, blood pressure, body composition, and blood variables were measured before and after the exercise and control period. Disease activity was determined and questionnaire data were collected. Results HIIT resulted in 12.2 % increase in VO2max and 2.9 % improvement in heart rate recovery (p < 0.05). BMI, body fat, and waist circumference decreased 1.2, 1.0, and 1.6 %, respectively, whereas muscle mass increased 0.6 % (p < 0.05). A trend toward decreased CRP was detected after HIIT (p = 0.08). No changes were detected in disease activity or pain. Conclusion Despite rigorous high intensity exercise, no increase was detected in disease activity or pain, indicating that HIIT was well tolerated by these patients. Furthermore, HIIT had positive effects on several CVD risk factors. In light of this pilot study, HIIT seems like a promising nonpharmacological treatment strategy for patients with RA and adult-JIA. Keywords Rheumatology · Exercise · Cardiovascular diseases Abbreviations BMI Body mass index CVD Cardiovascular disease COMP Cartilage oligomeric matrix protein CAD Coronary artery diseases CRP C-reactive protein HIIT High intensity interval training HDL High-density lipoprotein IGF-1 Insulin-like growth factor JIA Juvenile idiopathic arthritis HRmax Maximal heart rate VO2max Maximal oxygen uptake
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1-minHRR One-minute heart rate recovery PTX3 Pentraxin 3 RA Rheumatoid arthritis SD Standard deviations VAS Visual analog scale
Introduction Rheumatoid arthritis (RA) is the most common type of inflammatory arthritis, affecting approximately 0.5–1 % of the world’s population (Alamanos et al. 2006). The incidence varies by age, race, and geographic location, and females are affected 3-times more often than males (Alamanos et al. 2006). RA is classified as a chronic, systemic, and autoimmune disease. The major symptoms are synovial inflammation and swollen joints, autoantibody production, deformation of cartilage and bone structures, and systemic features such as cardiovascular, pulmonary, psychological, and skeletal disorders (McInnes and Schett 2011). RA is associated with increased risk of cardiovascular diseases (CVD), like atherosclerosis and myocardial infarction, likely due to the chronic systemic inflammation and physical inactivity (Pahor et al. 2006; Solomon et al. 2003; Maradit-Kremers et al. 2005). The overall mortality rate in patients with RA is 1.6 compared to that of the general population, and CVD accounts for 40–50 % of the deaths in this group (Avina-Zubieta et al. 2008). An especially high risk has been observed in female patients with RA who were diagnosed at young age. Those being 20–39 years of age at first diagnosis had a more than fivefold increased risk of death from coronary artery diseases (CAD) compared to the general population (Bjornadal et al. 2002). Patients with RA therefore have a shorter life expectancy compared to the general population, and CVDrelated deaths often occurs at an earlier age (Pahor et al. 2006; Goodson et al. 2002). Juvenile idiopathic arthritis (JIA) is not a single disease, but a term that encompasses all forms of arthritis that is revealed before a person is 16 years of age. JIA is not only a disease of childhood, as more than a third will continue to have active disease as adults, named adult-JIA (Foster et al. 2003). The disease is poorly described in adult patients, due to absence of research and understanding of the pathology. Adult-JIA is often associated with life-long disability and risk for emotional and social dysfunction (Moorthy et al. 2010). Regular exercise is an important treatment strategy for patients with rheumatic disease and has been shown to induce long-term anti-inflammatory effects and reduce the risk of CVD (Petersen and Pedersen 2005). The exercise recommendations for RA-patients today ranges from 2 to 7 days a week depending on the goal of the exercise. If
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the goal is to improve endurance, maximal oxygen uptake (VO2max), and cardiovascular function, the recommended frequency is 2–3 times a week at an intensity of 60–80 % of HRmax with a duration of 30–60 min (Stenstrom and Minor 2003). Improving VO2max is crucial if the goal of exercise treatment is to reduce the risk of CVD. VO2max is found to be the single best predictor of cardiovascular morbidity and premature cardiovascular mortality, and low VO2max is clearly associated with a clustering of cardiovascular risk factors (Aspenes et al. 2011). A large metaanalysis in healthy individuals reported that a ~3.5 ml/kg/ min higher fitness level was associated with 13 and 15 % decreased risk of all-cause mortality and cardiovascular events, respectively (Kodama et al. 2009). Several studies have shown that high intensity interval training (HIIT) is superior to moderate intensity endurance training in improving VO2max in people with and without CVD (Helgerud et al. 2007; Tjonna et al. 2009; Wisloff et al. 2007). Furthermore, there seems to be a dose– response relationship also within the 85–95 % of HRmax intensity zone. Our research group reported that an exercise intensity >92 % of HRmax during the high intensity intervals, resulted in significantly larger improvements of VO2peak than for exercise intensity between 85 and 92 % of HRmax (Moholdt et al. 2014). Based on the evidence for superior effects of exercise at high intensities, it seems likely that patients with RA would achieve even greater benefits of exercise training if they were recommended to perform exercise training at intensities between 85–95 % of HRmax. Despite this, the literature on the effect of exercise at high intensity in this patient group is sparse. Since these patients have a challenging and sometimes unstable disease, it is important to study whether exercise at these intensities would be tolerated by this patient group. The aims of this study were to investigate whether 10 weeks of HIIT at 85–95 % of HRmax would improve important risk factors of CVD in rheumatic patients and if these patients would tolerate exercise intensities above today’s recommendations.
Patients and methods Design This study was designed as a cross-over study, thus the participants were their own controls for the effect of the intervention. The participants were randomized to either start in the interval training group or in the control group. The randomization was carried out by The Unit for Applied Clinical Research at the Faculty of Medicine, NTNU. We stratified for RA and adult-JIA diagnosis, to secure equal numbers of both diseases in each study arm. After the first
Eur J Appl Physiol
Exercise program
Recruited n = 18
Excluded n = 3 - 1 due to arthris in knee - 1 started anTNF therapy - 1 diagnosed with diabetes Drop out n = 1 - 1 moved out of the region Re-included n = 1 - The one who started an-TNF therapy was reincluded due to stable disease
HIIT-group 1 n=9
Controlgroup 1 n=9
Analyzed HIIT n=6
Analyzed controls n=9
2 months washout-period
Controlgroup 2 n=6
HIIT- group 2 n=7
Analyzed controls n=6
Analyzed HIIT n=6
Drop out n = 2 - 2 moved out of region
Drop out n = 1 - 1 got pregnant
Fig. 1 Flow chart of the study design. n numbers of subjects, HIIT high intensity interval training
period of either training or control, the participants had a 2 months “washout-period” (Fig. 1). In the control period, the subjects were instructed to live their lives as normal. All measurements and tests were conducted before and after each 10-week period of interval training and control. The study was approved by the regional ethical committee (REK 2010/3347) and is published in www.ClinicalTrials. gov (NCT01478334). Patients Eighteen women with RA and adult-JIA, aged 20–50 years, were recruited through advertisement in a local newspaper, the university web page, and posters at the hospital. The inclusion criteria were patients with diagnosed RA or adult-JIA older than 18 years. The rheumatic disease should be stable with no changes in medication the last 2 months. Small changes in cortisone up to 5 mg a day were allowed. Exclusion criteria were regular exercise training >2 times a week before attending the study, participation in <80 % of the exercise sessions during the study, heart disease, lung disease, pregnancy, lactation, or active arthritis despite medication. Furthermore, patients who started with a new synthetic DMARD (disease-modifying drugs) or biologic DMARDs were excluded. Before inclusion, a rheumatologist (MH) ensured that the subjects were correctly diagnosed and did not have any exclusion criteria. No patients were excluded at the evaluating meeting. All subjects provided written informed consents, and the study was approved by the regional committee for medical research ethics. The study was performed according to the standards of the Helsinki Declaration.
Participants performed supervised exercise training two times a week for 10 weeks on a spinning bicycle (Impulse Spinning G2, Shandong, China). The exercises started with a warm-up for 10 min at ~70 % of maximal heart rate (HRmax, measured during the exercise test) followed by four 4-minute intervals at 85–95 % of HRmax, interspersed with 3 min recovery periods at ~70 % of HRmax. Total exercise duration was 35 min. All subjects used a heart rate monitor (Polar Electro, Kempele, Finland) during all exercise sessions to ensure that the assigned exercise intensities were obtained. The speed and work load were adjusted continuously to ensure that each exercise session was carried out at the assigned intensity throughout the exercise training period. During the exercise sessions, we made sure that the participants reached at least 85 % of their max HR within the first 1 min and 30 s of the 4-minute interval. Maximal oxygen uptake and heart rate recovery The subjects’ maximal oxygen uptake (VO2max) was tested by ergospirometry (Jaeger, Oxycon Pro, Hoechberg, Germany). An individually adjusted test bike (Monark 839 E, Monark Exercise AB, Vansbro, Sweden) was used. During warm-up, the resistance of the bike was individually adjusted, based on the subject’s fitness level. After 10 min warm-up, the test started by increasing the work load of the bike. The work load was increased by 20 W whenever the oxygen uptake was levelling off and until exhaustion. The criteria used for VO2max was a leveled off or drop in oxygen uptake, despite increased work load, in combination with a respiratory exchange ratio above 1.05 (Howley et al. 1995). The heart rate was registered continuously during the test using a heart rate monitor (Polar Electro, Kempele, Finland). The highest heart rate during the test plus 5 additional beats was defined as HRmax. One-minute heart rate recovery (1-minHRR) was calculated as the difference between the highest heart rate measured during the test and the heart rate 1 min after the end of the test (Ingjer 1991). Blood pressure Blood pressure was measured using an automatic sphygmomanometer (Microlife BPA 100 Plus, Microlife AG, 9435 Heerbrugg, Switzerland). The subjects rested in a quiet room for 10 min prior to the measurements. The procedure was repeated three times. The first measurement was rejected and the average of the second and third measurement was used.
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Body composition To assess body fat percentage, muscle mass percentage, weight, and BMI, the bioelectrical impedance analyzer HBF-352-W (Omron Healtcare Co, Kyoto, Japan) was used subsequent to an overnight fast. Body weight was recorded to the nearest 0.1 kg, with the subject wearing light clothing without shoes. Body fat percentage and muscle mass percentage were measured to the nearest 0.1 %. All measurements during post-testing were taken at the same time of the day as the pre-test. Blood analysis Venous blood drawn from venepuncture of the antecubital vein was collected after 12 h fasting in EDTA and serum tubes (Greiner-Bio One GmbH, Frickenhausen, Germany). EDTA plasma and serum were centrifuged at 3000 g for 10 min at 20 °C. Serum and plasma were stored at −80 °C for later analyses. Blood analyses were performed at the Department of Medical Biochemistry at St. Olavs University Hospital, Trondheim, Norway. We analyzed S-ferritin, triglyceride, total cholesterol, HDL-cholesterol, hemoglobin, high sensitive C-reactive protein (CRP), insulin C-peptide, and insulin-like growth factor (IGF-1). In addition, white blood cell count was performed. Blood samples taken for the post-test were collected 48–96 h after the last exercise session to avoid acute effects.
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disease activity between 3.2 and 5.1, and low disease activity is below 3.2 (Prevoo et al. 1995). Functional disability Patient satisfaction in performing activities of daily living (ADL) was assessed by a self-administered questionnaire modified from the Stanford health assessment questionnaire (MHAQ). The MHAQ includes questions to determine a patient’s degree of difficulty and need for help and assistive devices in ADL. The patients answer if they have difficulty performing ADL from 0 = no difficulty; 1 = some difficulty; 2 = much difficulty, and 4 = unable to do (Pincus et al. 1983). Statistical analyses Power calculations indicated that we needed to include at least ten participants in this cross-over study to achieve a power of 80 % to find significant changes in VO2max. Statistical analyses were performed using SPSS, version 19.0 (SPSS Inc.). Descriptive statistics are presented as means and standard deviations (SD), or median and interquartile range. To test the normality of the data, the Smirnov Kolmogorov test was used. Paired Student’s t test was used for pre- and post-test comparisons. For correlation analysis, we calculated the nonparametric Spearman correlation coefficients (rs). The level of significance was set to p < 0.05. Trends toward significance were commented at p < 0.10.
Enzyme‑linked immunosorbent assay (ELISA) Plasma levels of pentraxin 3 (PTX3) and cartilage oligomeric matrix protein (COMP) were measured before and after both the exercise and control periods by use of Quantikine Human Pentraxin 3/TGS-14 Immunoassay kit and the Quantikine Human COMP Immunoassay kit (R&D Systems, Minneapolis, USA). The assays were performed according to the manufacturer’s instructions, and the analyses were automated and performed by use of a DS2 Twoplate Automated ELISA Processing System (Dynex Technologies, Chantilly, USA). All samples were analyzed in duplicate reactions. Disease activity All patients were examined by a rheumatologist (MH) before and after the training and the control period. Disease activity was calculated by the disease activity score (DAS28), based on the number of tender and swollen joints (out of 28), visual analog scale (VAS)-score for general health (indicated by marking a 10 cm line between very good and very bad), and CRP levels (Wewers and Lowe 1990; Crowson et al. 2009). High disease activity was defined as DAS28 >5.1, moderate
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Results Baseline characteristics of the participants are shown in Table 1. Out of the eighteen participants, 72 % used disease modifying anti-rheumatic drugs (DMARD) and 39 % used Table 1 Diagnosis and the number of participants on medication that was included in the study Diagnosis and medication RA diagnoses (n) Adult-JIA diagnoses (n)
Number of participants 7 11
ACPA positive (n)
7
RFIgM positive (n)
6
ANA positive (n)
1
Erosions in hands/feet, positive (n) Uses DMARD (n)
7 13
Uses antiTNF-α medication (n)
7
Smokers (n)
3
RA rheumatoid arthritis, JIA juvenile idiopathic arthritis, ACPA anti cyclic citrullinated peptide antibodies, RFIgM rheumatoid factor for immunoglobulin M, ANA anti-nuclear antibodies, DMARD disease modifying anti-rheumatic drugs, TNF-α tumor necrosis factor-alpha
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VO2max
ml/kg/min
45
significant difference were observed in the control group (Fig. 2). The 1-minHRR increased 2.9 % after HIIT (p = 0.02), whereas no changes were observed in the control group (Table 2). No significant differences in VO2max and 1-minHRR were observed at Pretest between the HIIT and the control group, or between those attending the training group before or after the control period.
+12.2% p<0.001
40
35
30 25
Body composition and blood pressure Pre
HIIT
Post
Pre
Post
Control
Fig. 2 VO2max-levels at Pre-test (white) and Post-test (black) in the HIIT and control group. A significant improvement was found from pre to post in the HIIT group (p < 0.001). Baseline values were similar in both groups. Results are shown as mean ± SD. VO2max maximal oxygen uptake, HIIT high intensity interval training
tumor necrosis factor-alpha (TNF-α) inhibitors. As seen from Fig. 1, three participants were excluded from the data analysis after completing the first HIIT period based on the exclusion criteria. In the second HIIT period, one participant dropped out during the training period due to pregnancy. The results from a total of 12 participants were therefore included in the analysis from the HIIT group. 15 participants were included in the analysis from the control group. 11 of the participants completed both the HIIT and control period. Maximal oxygen uptake and heart rate recovery In the exercise training group, maximal oxygen uptake (VO2max) increased by 12.2 % (p < 0.001), while no
Table 2 Physiological parameters in the HIIT and control group
In the HIIT group, body mass index (BMI), total body fat, and waist circumference decreased by 1.2 % (p = 0.04), 1.0 % (p = 0.04), and 1.6 % (p = 0.004), respectively (Table 2), whereas no changes were detected in the control group. Furthermore, a 0.6 % increase in muscle mass was found after HIIT (p = 0.03), while no differences were found in the control group (Table 2). No significant difference in blood pressure was observed in HIIT or the control group (Table 2). No significant differences were found between those attending the training group before or after the control period. Blood analysis In the HIIT group, serum levels of hemoglobin and ferritin decreased 2.2 % (p = 0.03), and 24.0 % (p = 0.006), respectively. A trend toward a decrease in serum high sensitive CRP from 1.98 (0.95–4.01) to 1.23 (0.72– 2.46) mg/l was observed in the HIIT group (p = 0.08). No changes were found in the other analyzed biomarkers (Table 3).
HIIT group
Age (years) Height (cm) Weight (kg) BMI (kg/m2) Body fat (%) Visceral fat (%) Muscle mass (%) Waist circumference (cm) 1-minHRR (beats/min) Systolic BP (mmHg) Diastolic BP (mmHg)
Control group
Pre
Post
Pre
Post
32.4 ± 8.3 166.3 ± 5.3 70.5 ± 14.6 24.8 ± 4.9 36.9 ± 9.1 5.5 ± 2.6 26.4 ± 3.9 89.5 ± 12.0 38.6 ± 2.3 120.7 ± 9.6
32.4 ± 8.3 166.3 ± 5.3 69.8 ± 14.0 24.5 ± 4.6* 35.9 ± 9.5* 5.3 ± 2.6 27.0 ± 4.2* 88.1 ± 11.2* 39.7 ± 2.7* 118.8 ± 11.4
33.4 ± 8.5 166.4 ± 5.0 67.7 ± 15.0 24.0 ± 4.3 35.5 ± 8.5 5.0 ± 2.4 26.8 ± 3.7 86.2 ± 12.9 37.9 ± 2.0 120.0 ± 14.0
34.3 ± 8.7 167.3 ± 4.7 67.4 ± 13.7 24.2 ± 4.9 35.1 ± 8.1 5.1 ± 2.5 27.0 ± 3.4 85.9 ± 12.2 38.0 ± 2.3 116.6 ± 9.4
73.7 ± 7.5
73.1 ± 7.0
73.5 ± 10.2
73.8 ± 10.2
Values presented as mean ± SD HIIT high intensity interval training, BMI body mass index, 1-minHRR one-minute heart rate recovery, BP blood pressure * p < 0.05
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Table 3 Blood variables in the HIIT and control group HIIT group
Control group
Pre
Post
Pre
Post
Insuline C-peptides (nmol/l) IGF-1 (nmol/l) HDL-cholesterol (mmol/l) Cholesterol (mmol/l) Hemoglobin (g/dl) Ferritin (μg/l) Triglyceride (mmol/l) Pentraxin-3 (ng/ml) COMP (ng/ml)
0.59 ± 0.24 27.2 ± 9.5 1.52 ± 0.47 4.78 ± 1.11 13.9 ± 0.9 78.8 ± 69.6 0.91 ± 0.42 0.22 ± 0.20 114.5 ± 55.3
0.62 ± 0.29 23.4 ± 7.6 1.50 ± 0.42 4.79 ± 1.08 13.6 ± 1.1* 59.9 ± 54.3* 0.95 ± 0.52 0.16 ± 0.16 128.9 ± 52.1
0.66 ± 0.29 26.7 ± 9.9 1.62 ± 0.52 4.83 ± 1.09 13.6 ± 0.9 63.6 ± 41.6 1.04 ± 0.56 0.18 ± 0.12 122.6 ± 62.8
0.62 ± 0.22 26.0 ± 10.1 1.59 ± 0.53 4.71 ± 0.96 13.6 ± 1.0 66.8 ± 52.5 1.01 ± 0.64 0.21 ± 0.22 110.4 ± 54.9
hsCRP (mg/l)
1.98 (0.95–4.01)
1.23 (0.72–2.46)$
1.32 (0.89–5.39)
2.65 (1.59–3.08)
Values are presented as mean ± SD, except for hsCRP which is reported as median (interquartile range) HIIT high intensity interval training, IGF-1 insulin-like growth factor 1, HDL high-density lipoprotein, COMP human cartilage oligometric matrix protein, hsCRP high sensitive C-reactive protein * p < 0.05 $
p < 0.10
Disease activity No changes were detected in disease activity and pain during the study. The fatigue score did not change during HIIT, but decreased significantly in the control group (p = 0.03) (Table 4).
Discussion The main findings of this present study were that high intensity interval training at intensities above today’s recommendations were well tolerated by patients with RA and adult-JIA, and that the exercise induced significant improvements in several risk factors of CVD. No increase in disease activity or inflammation was seen after 10 weeks of HIIT. In fact a trend toward decreased levels of CRP was detected after the exercise intervention, indicating a decline in general inflammation. Furthermore, the patients improved their cardiorespiratory fitness shown by significant improvements in VO2max and 1-minHRR. Other parameters related to the risk of cardiovascular disease as body mass index (BMI), total body fat, and waist circumference were also improved after 10 weeks of interval training. Several studies have shown that regular physical activity is just as important for people with arthritis or other rheumatic conditions as for the general population, as reviewed by Brady et al. (2003). Participation in moderate-intensity exercise improves pain, function, mood, and quality of life without worsening symptoms or disease severity (Brady
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et al. 2003). Being physically active can also delay the onset of disability in patients with arthritis (Baillet et al. 2010). However, literature on the effect of exercise at high intensity in this patient group is sparse. To our knowledge, only two research groups have studied the effects of exercise at up to 85–90 % of HRmax (de Jong et al. 2003; van den Ende et al. 2000). Our research group has previously shown that the average VO2max in Norwegian women 20–50 years old is between 42.9 and 37.9 ml/kg/min (Aspenes et al. 2011). The average baseline values of VO2max reported in this study is in line with a previous study reporting that VO2max is reduced by ~20 % in patients with RA (Ekdahl and Broman 1992). Table 4 Disease activity in the HIIT and control group HIIT group Pre
Control group Post
Pre
Post
DAS28 2.56 ± 0.94 2.29 ± 0.58 2.48 ± 0.93 2.48 ± 0.64 MHAQ 0.65 ± 0.43 0.49 ± 0.45 0.42 ± 0.41 0.50 ± 0.49 Self-reported 32.0 ± 20.7 21.2 ± 18.6 26.0 ± 20.4 25.2 ± 17.3 health score Self-reported 2.45 ± 2.34 2.36 ± 1.86 3.08 ± 2.29 3.46 ± 2.26 joint pain Pain score
30.2 ± 23.1 19.7 ± 20.0 24.3 ± 20.6 28.0 ± 19.6
Fatigue score 39.2 ± 30.2 39.3 ± 28.2 40.1 ± 31.2 26.2 ± 26.3* Values presented as mean ± SD HIIT high intensity interval training, DAS28 disease activity score from 28 joints, MHAQ modified health assessment questionnaire * p ≤ 0.05
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It has previously been shown that HIIT is effective in improving VO2max both for healthy individuals at all ages and for other patient groups (Helgerud et al. 2007; Makrides et al. 1990; Nemoto et al. 2007; Wenger and Bell 1986; Tjonna et al. 2008, 2009; Wisloff et al. 2007). As anticipated, our results show an average 12 % increase (4.4 ml/kg/min) in VO2max after the exercise intervention. This is in line with a previous study from our research group showing that 12 weeks of HIIT resulted in 11 % increase in VO2max in metabolic syndrome patients (Stensvold et al. 2010). A large meta-analysis in healthy individuals reported that a ~3.5 ml/kg/min increase in fitness was associated with 13 and 15 % decreased risk of all-cause mortality and cardiovascular events, respectively (Kodama et al. 2009). Based on these data, the RA and adult-JIA patients included in this present study are likely to have improved their CVD risk considerably during the exercise intervention. Furthermore, we found a significant improvement in 1-minHRR after the exercise intervention. Improved 1-minHRR is associated with decreased risk of all-cause death in individuals without CVD, and may therefore be regarded as an independent risk factor for mortality (Wandell et al. 2010). Slow and abnormal 1-minHRR is also associated with inflammatory markers, which could contribute to the high incidence of CVD in these subjects (Jae et al. 2007). High blood pressure is associated with increased risk for CVD, and exercise has been shown to lower BP in hypertensive individuals (Fagard 2001). As the patients in this study had normal blood pressure at baseline, no changes in blood pressure were expected. Moreover, the exercise period resulted in a significant decrease in BMI, total body fat, and waist circumference, while percentage muscle mass increased. The mean BMI before the exercise intervention was 24.8 kg/m2, which means close to the limit for overweight. For overweight individuals, a decline in BMI lowers the risk of cardiovascular morbidity and premature cardiovascular mortality (Lu et al. 2014). Also the distribution of the fat in the body is essential and high waist circumference and high amount of visceral fat increase the risk of CVD (Janssen et al. 2002). Studies have suggested that waist circumference might be an even better predictor of mortality risk than BMI (Koster et al. 2008; Leitzmann et al. 2011). Furthermore, a small but significant increase in muscle mass was found in this study. Several circulating biomarkers previously associated with inflammation, rheumatic disease activity, and CVD risk were measured in the patients before and after the exercise intervention. Patients with rheumatic diseases often have elevated levels of CRP, which reflects the low-grade inflammation. As several studies demonstrate
an inverse relationship between regular physical activity and serum levels of inflammatory markers (Kasapis and Thompson 2005), we speculated whether exercise training would reduce the levels of CRP also in patients with RA and adult-JIA. As anticipated, we detected a trend toward decreased levels of CRP after the exercise intervention, possibly reflecting less joint inflammation. Since inflammation plays a pivotal role in the pathogenesis of atherosclerosis, the exercise-induced trend toward decreased levels of CPR may also reflect a decreased risk of cardiovascular morbidity and mortality (Ross 1999). Furthermore, we measured the circulating levels of pentraxin 3 (PTX3), which is a marker of inflammation, atherosclerosis, and the risk of CVD death (Jenny et al. 2009; Mantovani et al. 2008; Luchetti et al. 2000; Norata et al. 2010). However, no changes were detected in PTX3 during this study. Additionally, we measured circulating levels of the cartilage oligomeric matrix protein (COMP). Serum COMP has been suggested as marker of ongoing joint damage in patients with RA (Crnkic et al. 2003; Mansson et al. 1995). In line with the previous findings from a study of physical exercise in patients with knee osteoarthritis, no long-term changes in COMP were detected in response to the exercise intervention (Andersson et al. 2006). Serum ferritin is a wellknown inflammatory marker, but it is still unclear whether it reflects or causes inflammation (Kell and Pretorius 2014). The exercise-induced decrease in ferritin documented in this study, supports the previous indication of decreased inflammatory status achieved by HIIT. We also detected a significant decrease in hemoglobin after the exercise intervention. This observation is not unusual, however the mechanisms for exercise-induced reductions in hemoglobin is not yet elucidated (Beard and Tobin 2000). Surprisingly, we found a significant decrease in fatigue during the control period. This was unexpected, and we believe it might be a result of large variations within in the groups. The main limitation of this study was the low number of participants; however, it was intended to be a pilot study because interval training at these high intensities has not previously been tested in arthritis patients. Several trends were evident, however not significant, and it is likely that inclusion of more patients would have enhanced the statistical power. Furthermore, the crossover design has both strengths and limitations. The participants that were randomized to HIIT in the first period might have experienced some long-term benefit of the training in terms of a healthier lifestyle during the subsequent control period. We have tried to reduce this effect by including a wash-out period of 2 months. The fact that none of the tested variables were significantly different at Pre-test depending on whether the participants attended the training group first or last, indicate that the wash-out period was sufficient.
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To our knowledge, this is the first time supervised high intensity interval training reaching 95 % of maximal heart is tested on arthritis patients using a cross-over design. Despite rigorous high intensity exercise for 10 weeks, we detected no increase in disease activity, pain, inflammation, or joint damage (based on DAS28, MHAQ, high sensitive CRP, ferritin, PTX3, and COMP), indicating that HIIT is well tolerated by female patients with RA and adult-JIA. Furthermore, HIIT had positive effects on several risk factors for CVD like VO2max, 1-minHRR, BMI, waist circumference, and total body fat. In light of this pilot study, HIIT seems like a promising non-pharmacological treatment strategy for patients with RA and adult-JIA. We recommend that the study should be replicated in a larger group of patients with RA and adult-JIA, as well as in male patients. Conflict of interest The authors declare that they have no conflict of interest. Ethical standard All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
References Alamanos Y, Voulgari PV, Drosos AA (2006) Incidence and prevalence of rheumatoid arthritis, based on the 1987 American College of rheumatology criteria: a systematic review. Semin Arthritis Rheum 36(3):182–188. doi:10.1016/j.semarthrit.2006.08.006 Andersson ML, Thorstensson CA, Roos EM, Petersson IF, Heinegard D, Saxne T (2006) Serum levels of cartilage oligomeric matrix protein (COMP) increase temporarily after physical exercise in patients with knee osteoarthritis. BMC Musculoskelet Disord 7:98. doi:10.1186/1471-2474-7-98 Aspenes ST, Nilsen TI, Skaug EA, Bertheussen GF, Ellingsen O, Vatten L, Wisloff U (2011) Peak oxygen uptake and cardiovascular risk factors in 4631 healthy women and men. Med Sci Sports Exerc 43(8):1465–1473. doi:10.1249/MSS.0b013e31820ca81c Avina-Zubieta JA, Choi HK, Sadatsafavi M, Etminan M, Esdaile JM, Lacaille D (2008) Risk of cardiovascular mortality in patients with rheumatoid arthritis: a meta-analysis of observational studies. Arthritis Rheum 59(12):1690–1697. doi:10.1002/art.24092 Baillet A, Zeboulon N, Gossec L, Combescure C, Bodin LA, Juvin R, Dougados M, Gaudin P (2010) Efficacy of cardiorespiratory aerobic exercise in rheumatoid arthritis: meta-analysis of randomized controlled trials. Arthritis Care Res 62(7):984–992. doi:10.1002/acr.20146 Beard J, Tobin B (2000) Iron status and exercise. Am J Clin Nutr 72(2 Suppl):594S–597S Bjornadal L, Baecklund E, Yin L, Granath F, Klareskog L, Ekbom A (2002) Decreasing mortality in patients with rheumatoid arthritis: results from a large population based cohort in Sweden, 1964–95. J Rheumatol 29(5):906–912 Brady TJ, Kruger J, Helmick CG, Callahan LF, Boutaugh ML (2003) Intervention programs for arthritis and other rheumatic
13
Eur J Appl Physiol diseases. Health Educ Behav: Off Publ Soc Public Health Educ 30(1):44–63 Crnkic M, Mansson B, Larsson L, Geborek P, Heinegard D, Saxne T (2003) Serum cartilage oligomeric matrix protein (COMP) decreases in rheumatoid arthritis patients treated with infliximab or etanercept. Arthritis Res Ther 5(4):R181–R185. doi:10.1186/ ar760 Crowson CS, Rahman MU, Matteson EL (2009) Which measure of inflammation to use? A comparison of erythrocyte sedimentation rate and C-reactive protein measurements from randomized clinical trials of golimumab in rheumatoid arthritis. J Rheumatol 36(8):1606–1610. doi:10.3899/jrheum.081188 de Jong Z, Munneke M, Zwinderman AH, Kroon HM, Jansen A, Ronday KH, van Schaardenburg D, Dijkmans BA, Van den Ende CH, Breedveld FC, Vliet Vlieland TP, Hazes JM (2003) Is a long-term high-intensity exercise program effective and safe in patients with rheumatoid arthritis? Results of a randomized controlled trial. Arthritis Rheum 48(9):2415–2424. doi:10.1002/ art.11216 Ekdahl C, Broman G (1992) Muscle strength, endurance, and aerobic capacity in rheumatoid arthritis: a comparative study with healthy subjects. Ann Rheum Dis 51(1):35–40 Fagard RH (2001) Exercise characteristics and the blood pressure response to dynamic physical training. Med Sci Sports Exerc 33(6):S484–S492 ; discussion S493–S484 Foster HE, Marshall N, Myers A, Dunkley P, Griffiths ID (2003) Outcome in adults with juvenile idiopathic arthritis: a quality of life study. Arthritis Rheum 48(3):767–775. doi:10.1002/art.10863 Goodson NJ, Wiles NJ, Lunt M, Barrett EM, Silman AJ, Symmons DP (2002) Mortality in early inflammatory polyarthritis: cardiovascular mortality is increased in seropositive patients. Arthritis Rheum 46(8):2010–2019. doi:10.1002/art.10419 Helgerud J, Hoydal K, Wang E, Karlsen T, Berg P, Bjerkaas M, Simonsen T, Helgesen C, Hjorth N, Bach R, Hoff J (2007) Aerobic high-intensity intervals improve VO2max more than moderate training. Med Sci Sports Exerc 39(4):665–671 Howley ET, Bassett DR Jr, Welch HG (1995) Criteria for maximal oxygen uptake: review and commentary. Med Sci Sports Exerc 27(9):1292–1301 Ingjer F (1991) Factors influencing assessment of maximal heart rate. Scand J Med Sci Sports 1(3):134–140 Jae SY, Ahn ES, Heffernan KS, Woods JA, Lee MK, Park WH, Fernhall B (2007) Relation of heart rate recovery after exercise to C-reactive protein and white blood cell count. Am J Cardiol 99(5):707–710. doi:10.1016/j.amjcard.2006.09.121 Janssen I, Heymsfield SB, Allison DB, Kotler DP, Ross R (2002) Body mass index and waist circumference independently contribute to the prediction of nonabdominal, abdominal subcutaneous, and visceral fat. Am J Clin Nutr 75(4):683–688 Jenny NS, Arnold AM, Kuller LH, Tracy RP, Psaty BM (2009) Associations of pentraxin 3 with cardiovascular disease and all-cause death: the cardiovascular health study. Arterioscler Thromb Vasc Biol 29(4):594–599. doi:10.1161/ATVBAHA.108.178947 Kasapis C, Thompson PD (2005) The effects of physical activity on serum C-reactive protein and inflammatory markers: a systematic review. J Am Coll Cardiol 45(10):1563–1569. doi:10.1016/j. jacc.2004.12.077 Kell DB, Pretorius E (2014) Serum ferritin is an important inflammatory disease marker, as it is mainly a leakage product from damaged cells. Metall Integr Biometal Sci 6(4):748–773. doi:10.1039/c3mt00347g Kodama S, Saito K, Tanaka S, Maki M, Yachi Y, Asumi M, Sugawara A, Totsuka K, Shimano H, Ohashi Y, Yamada N, Sone H (2009) Cardiorespiratory fitness as a quantitative predictor of all-cause mortality and cardiovascular events in healthy men and women:
Eur J Appl Physiol a meta-analysis. JAMA 301(19):2024–2035. doi:10.1001/ jama.2009.681 Koster A, Leitzmann MF, Schatzkin A, Mouw T, Adams KF, van Eijk JT, Hollenbeck AR, Harris TB (2008) Waist circumference and mortality. Am J Epidemiol 167(12):1465–1475. doi:10.1093/aje/ kwn079 Leitzmann MF, Moore SC, Koster A, Harris TB, Park Y, Hollenbeck A, Schatzkin A (2011) Waist circumference as compared with body-mass index in predicting mortality from specific causes. PLoS One 6(4):e18582. doi:10.1371/journal.pone.0018582 Lu Y, Hajifathalian K, Ezzati M, Woodward M, Rimm EB, Danaei G, Global Burden of Metabolic Risk Factors for Chronic Diseases C (2014) Metabolic mediators of the effects of bodymass index, overweight, and obesity on coronary heart disease and stroke: a pooled analysis of 97 prospective cohorts with 1.8 million participants. Lancet 383(9921):970–983. doi:10.1016/ S0140-6736(13)61836-X Luchetti MM, Piccinini G, Mantovani A, Peri G, Matteucci C, Pomponio G, Fratini M, Fraticelli P, Sambo P, Di Loreto C, Doni A, Introna M, Gabrielli A (2000) Expression and production of the long pentraxin PTX3 in rheumatoid arthritis (RA). Clin Exp Immunol 119(1):196–202 Makrides L, Heigenhauser GJ, Jones NL (1990) High-intensity endurance training in 20–30 and 60–70-year-old healthy men. J Appl Physiol 69(5):1792–1798 Mansson B, Carey D, Alini M, Ionescu M, Rosenberg LC, Poole AR, Heinegard D, Saxne T (1995) Cartilage and bone metabolism in rheumatoid arthritis. Differences between rapid and slow progression of disease identified by serum markers of cartilage metabolism. J Clin Investig 95(3):1071–1077. doi:10.1172/ JCI117753 Mantovani A, Garlanda C, Doni A, Bottazzi B (2008) Pentraxins in innate immunity: from C-reactive protein to the long pentraxin PTX3. J Clin Immunol 28(1):1–13. doi:10.1007/ s10875-007-9126-7 Maradit-Kremers H, Crowson CS, Nicola PJ, Ballman KV, Roger VL, Jacobsen SJ, Gabriel SE (2005) Increased unrecognized coronary heart disease and sudden deaths in rheumatoid arthritis: a population-based cohort study. Arthritis Rheum 52(2):402–411. doi:10.1002/art.20853 McInnes IB, Schett G (2011) The pathogenesis of rheumatoid arthritis. N Engl J Med 365(23):2205–2219. doi:10.1056/ NEJMra1004965 Moholdt T, Madssen E, Rognmo O, Aamot IL (2014) The higher the better? Interval training intensity in coronary heart disease. J Sci Med Sport Sports Med Aust 17(5):506–510. doi:10.1016/j. jsams.2013.07.007 Moorthy LN, Peterson MG, Hassett AL, Lehman TJ (2010) Burden of childhood-onset arthritis. Pediatr Rheumatol Online J 8:20. doi:10.1186/1546-0096-8-20 Nemoto K, Gen-no H, Masuki S, Okazaki K, Nose H (2007) Effects of high-intensity interval walking training on physical fitness and blood pressure in middle-aged and older people. Mayo Clin Proc 82(7):803–811 Norata GD, Garlanda C, Catapano AL (2010) The long pentraxin PTX3: a modulator of the immunoinflammatory response in atherosclerosis and cardiovascular diseases. Trends Cardiovasc Med 20(2):35–40. doi:10.1016/j.tcm.2010.03.005
Pahor A, Hojs R, Gorenjak M, Rozman B (2006) Accelerated atherosclerosis in pre-menopausal female patients with rheumatoid arthritis. Rheumatol Int 27(2):119–123. doi:10.1007/ s00296-006-0176-6 Petersen AM, Pedersen BK (2005) The anti-inflammatory effect of exercise. J Appl Physiol 98(4):1154–1162. doi:10.1152/ japplphysiol.00164.2004 Pincus T, Summey JA, Soraci SA Jr, Wallston KA, Hummon NP (1983) Assessment of patient satisfaction in activities of daily living using a modified Stanford health assessment questionnaire. Arthritis Rheum 26(11):1346–1353 Prevoo ML, van ’t Hof MA, Kuper HH, van Leeuwen MA, van de Putte LB, van Riel PL (1995) Modified disease activity scores that include twenty-eight-joint counts. Development and validation in a prospective longitudinal study of patients with rheumatoid arthritis. Arthritis Rheum 38(1):44–48 Ross R (1999) Atherosclerosis—an inflammatory disease. N Engl J Med 340(2):115–126. doi:10.1056/NEJM199901143400207 Solomon DH, Karlson EW, Rimm EB, Cannuscio CC, Mandl LA, Manson JE, Stampfer MJ, Curhan GC (2003) Cardiovascular morbidity and mortality in women diagnosed with rheumatoid arthritis. Circulation 107(9):1303–1307 Stenstrom CH, Minor MA (2003) Evidence for the benefit of aerobic and strengthening exercise in rheumatoid arthritis. Arthritis Rheum 49(3):428–434. doi:10.1002/art.11051 Stensvold D, Tjonna AE, Skaug EA, Aspenes S, Stolen T, Wisloff U, Slordahl SA (2010) Strength training versus aerobic interval training to modify risk factors of metabolic syndrome. J Appl Physiol 108(4):804–810 Tjonna AE, Lee SJ, Rognmo O, Stolen TO, Bye A, Haram PM, Loennechen JP, Al-Share QY, Skogvoll E, Slordahl SA, Kemi OJ, Najjar SM, Wisloff U (2008) Aerobic interval training versus continuous moderate exercise as a treatment for the metabolic syndrome. A pilot study. Circulation 22(118):346–354 Tjonna AE, Stolen TO, Bye A, Volden M, Slordahl SA, Odegard R, Skogvoll E, Wisloff U (2009) Aerobic interval training reduces cardiovascular risk factors more than a multitreatment approach in overweight adolescents. Clin Sci Lond 116(4):317–326. doi:10.1042/CS20080249 van den Ende CH, Breedveld FC, le Cessie S, Dijkmans BA, de Mug AW, Hazes JM (2000) Effect of intensive exercise on patients with active rheumatoid arthritis: a randomised clinical trial. Ann Rheum Dis 59(8):615–621 Wandell PE, Carlsson AC, Theobald H (2010) Effect of heart-rate recovery on long-term mortality among men and women. Int J Cardiol 144(2):276–279. doi:10.1016/j.ijcard.2009.01.053 Wenger HA, Bell GJ (1986) The interactions of intensity, frequency and duration of exercise training in altering cardiorespiratory fitness. Sports Med Auckl NZ 3(5):346–356 Wewers ME, Lowe NK (1990) A critical review of visual analogue scales in the measurement of clinical phenomena. Res Nurs Health 13(4):227–236 Wisloff U, Stoylen A, Loennechen JP, Bruvold M, Rognmo O, Haram PM, Tjonna AE, Helgerud J, Slordahl SA, Lee SJ, Videm V, Bye A, Smith GL, Najjar SM, Ellingsen O, Skjaerpe T (2007) Superior cardiovascular effect of aerobic interval training versus moderate continuous training in heart failure patients: a randomized study. Circulation 115(24):3086–3094
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