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SCIENTIFIC LETTER

Selecting the increment size for a maximal incremental cycle test in patients with COPD JORINE E. HARTMAN,1,2 DIRK-JAN SLEBOS,1,2 H. MARIKE BOEZEN,2,3 MATHIEU H.G. de GREEF,4 HUIB A.M. KERSTJENS1,2 AND NICK H.T. ten HACKEN1,2 Departments of 1Pulmonary Diseases, 3Epidemiology and 4Human Movement Sciences, and 2GRIAC Research Institute, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands

Currently, to our knowledge, there are no chronic obstructive pulmonary disease (COPD)-specific formulas to predict the maximum workload of an incremental cycle ergometer test. The aim of the study was to investigate different prediction models including COPD-specific variables of maximum workload in 113 mild to very severe COPD patients. This study shows that simple measures like forced expiratory volume in 1 s, chair-stand test and modified Medical Research Council dyspnoea score may improve the accuracy of the predicted maximum workload in COPD patients. Key words: chronic obstructive pulmonary disease, clinical respiratory medicine, exercise, pulmonary rehabilitation.

Abbreviations: ATS/ACCP,

American Thoracic Society/ American College of Chest Physicians; COPD, chronic obstructive pulmonary disease; ERS/ATS, European Respiratory Society/ American Thoracic Society; FEV1, forced expiratory volume in 1 s; ITGV, intrathoracic gas volume; MRC, Medical Research Council; mMRC, modified Medical Research Council; VO2peak, maximum oxygen uptake; Wpeak, maximum workload.

Cardiopulmonary exercise testing is frequently performed to evaluate the cause and extent of exercise intolerance, exercise-related symptoms and exerciselimiting factors in patients with chronic obstructive pulmonary disease (COPD).1 A frequently performed exercise test is the symptom-limited incremental cycle ergometer test. In line with the American Thoracic Society/American College of Chest Physicians (ATS/ACCP) statement on cardiopulmonary exercise testing,1 the protocols of this test often include 3 min of rest, followed by 3 min of unloaded pedalling, followed by the incremental phase of loaded pedalling with 1-min steps. During this incremental phase, the increment size increases by 5–25 W/min.

Correspondence: Jorine E. Hartman, Department of Pulmonary Diseases AA11, University Medical Center Groningen, PO Box 30001, 9700 RB Groningen, The Netherlands. Email: [email protected] Received 2 May 2014; Invited to revise 25 July 2014; Revised 21 August 2014; Accepted 15 October 2014 (Associate Editor: Melissa Benton). © 2014 Asian Pacific Society of Respirology

Selecting the appropriate incremental size is important. Buchfuhrer et al. stated that the incremental phase should last 8–12 min to be efficient and to provide useful diagnostic information.2 Furthermore, Debigaré et al. showed that the increment size influences the maximum workload (Wpeak) achieved.3 Therefore, the better the Wpeak is predicted, the better the increment size can be chosen. Currently, the guidelines recommend that the increment size should be based on the prediction of Wpeak, which is often based on maximum oxygen uptake (VO2peak) taking gender, age, height and weight into account. However, most COPD patients do not reach the predicted Wpeak for healthy individuals, and there are no COPD-specific prediction equations available. For sedentary individuals, like COPD patients, it is recommended that the increment size per minute could be based on clinical judgement, physical examination, pulmonary function and knowledge of the subject’s physical activity.1,4 This judgement requires a lot of experience in exercise testing and a COPD-specific prediction formula for Wpeak would be useful. This would also decrease intertest variability between different supervising physicians. Therefore, our aim was to investigate different prediction models of Wpeak including COPDspecific variables of an incremental cycle ergometer tests in COPD patients. A total of 113 COPD patients performed a maximal cycle ergometer test during a study on physical activity in COPD5 and were included in the analyses. Patients were included if they had a COPD diagnosis according to the Global Initiative for Chronic Obstructive Lung Disease criteria6 and had not been treated for a COPD exacerbation in the past 2 months nor had other serious active disease that necessitated medical treatment (e.g., recent myocardial infarction). The study was approved by the medical ethics committee, and all patients provided informed consent. Maximal exercise capacity was measured by a maximal symptom-limited incremental cycle ergometer test according to the earlier described ATS/ ACCP statement.1 VO2, heart rate, lactate, partial pressure of carbon dioxide, partial pressure of oxygen and oxygen saturation were measured during the test. The Respirology (2015) 20, 352–355 doi: 10.1111/resp.12451

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Figure 1 Scatterplots and Bland–Altman plots of the achieved maximum workload and (Wpeak) the predicted workload. On average, a cycle ergometer test should last 10 min. Therefore, the predicted increment size can be obtained by dividing the predicted Wpeak by 10. (a) Prediction formula including sex, age, height and weight. (b) Prediction formula including sex, age, height, weight and FEV1. (c) Prediction formula including sex, age, height, weight, FEV1, chair stand and MRC. — Mean difference; - - - 95% limits of agreement. FEV1, forced expiratory volume in 1 s; MRC, Medical Research Council; mMRC, modified Medical Research Council. © 2014 Asian Pacific Society of Respirology

Respirology (2015) 20, 352–355

354 selected increment size was based on the prediction formula of Wasserman et al.4 and adjusted to the individual’s pulmonary function and fitness level (following the recommendations of Wasserman et al. and the ATS/ACCP1,4). As potential predictors of the Wpeak in patients with COPD, we selected factors that are easy to measure and can be performed on the same day as the cycle ergometer test. Therefore, we selected spirometry, dyspnoea severity score and leg muscle function. Forced expiratory volume in 1 s (FEV1) was measured by a spirometer according to the ERS/ATS guidelines.7 Dyspnoea severity was measured by the modified Medical Research Council Dyspnoea scale (mMRC).8 Leg muscle function was measured by a 30-s chair-stand test.9 The chair-stand test measures the number of times a person can stand up from a chair in 30 s and was found to be a valid indicator of lower body strength in older adults.9 Furthermore, we selected sex, age, height and weight because these factors are included in the frequently used prediction formula of Wasserman et al. and in most other equations for the prediction of VO2max.4 We analyzed three different linear regression prediction models with Wpeak as dependent variable and potential predictors as independent variables. First, we constructed a model with sex, age, height and weight as independent variables. In the second model, we added FEV1 to the previous model as an independent variable. Finally, we added the chairstand score and mMRC score to the previous model as independent variables (the statistical analyses are reported in the online supporting information). Patient characteristics and results of the cycle ergometer test can be found in Supplementary Tables S1 and S2. With the standard Wasserman et al. equation containing sex, age, height and weight as independent variables, the explained variance was only 25%. There was considerable overestimation at lower workloads and underestimation at higher workloads. The explained variance improved importantly to 76% after entering FEV1 into a model with sex, age, height and weight and improved further after entering the chair-stand score and mMRC score. Figure 1 depicts the association and agreement between the Wpeak achieved by the patient and the predicted Wpeak for the patient according to the different prediction formulas. The 95% limit of agreement (Fig. 1: Bland– Altman plot) decreased approximately by half with the prediction models based on FEV1 addition alone or FEV1, chair-stand score and mMRC score addition compared with the non-COPD-specific formula. This study shows that FEV1, mMRC dyspnoea score and chair-stand score significantly improved the prediction equations of the Wpeak of an incremental cycle ergometer test in COPD patients. The nonCOPD-specific formula, which only includes sex, age, height and weight, had poor predictive value in our COPD population. We selected FEV1, mMRC dyspnoea score and the chair-stand test to predict exercise capacity as these three tests are easy to perform and reflect different aspects of exercise limitation. FEV1 is the best known parameter of airway obstruction in COPD and is easy to measure. Lung hyperinflation has been described Respirology (2015) 20, 352–355

JE Hartman et al.

in the literature to limit exercise capacity as well.10 Indeed, intrathoracic gas volume (ITGV) was significantly associated with maximal workload as well in our population; however, the explained variance of the model with FEV1 was higher than with ITGV (data not shown). FEV1 is also easier to measure than ITGV. The mMRC scale is an easily applicable and valid method of categorizing COPD patients in terms of their disabilities due to dyspnoea and was shown to complement FEV1 in the classification of COPD severity.8 Muscle dysfunction is highly prevalent, even in patients with mild COPD,11 and is strongly associated with exercise capacity in COPD patients.12,13 We chose to include the chair-stand test because we wanted a simple to measure parameter of the function of large muscle groups involved in important daily activities as walking and cycling and the chair-stand test takes only 30 s. A disadvantage of our study is that the selected increment size was based on the judgement and experience of the respiratory physician and lung function personnel executing the ergometer test. This could have influenced the achieved Wpeak by our patients as approximately 40% of all tests had a duration shorter than 8 min or longer than 12 min. This finding emphasizes the need for COPD-specific reference values even more and demonstrates that our prediction formulas should be validated further in another COPD population. Ideally, such a population should have a large sample size and include patients with mild to very severe COPD from different countries, covering a broad range of exercise capacity levels. In conclusion, this study shows that simple measures like FEV1, chair-stand test and mMRC dyspnoea score may improve the accuracy of the predicted Wpeak in COPD patients. Performing these tests before conducting a cycle ergometer test, and applying the prediction formula, may help to select the appropriate increment size.

Acknowledgments This study was funded by the Dutch Asthma Foundation (grant number 3.4.07.036) and an unrestricted grant of Boehringer Ingelheim (Alkmaar, The Netherlands, grant number S10406). Both study sponsors were not involved in the study.

REFERENCES 1 American Thoracic Society, American College of Chest Physicians. ATS/ACCP Statement on cardiopulmonary exercise testing. Am. J. Respir. Crit. Care Med. 2003; 167: 211–77. 2 Buchfuhrer MJ, Hansen JE, Robinson TE, Sue DY, Wasserman K, Whipp BJ. Optimizing the exercise protocol for cardiopulmonary assessment. J. Appl. Physiol. 1983; 55: 1558–64. 3 Debigaré R, Maltais F, Mallet M, Casaburi R, LeBlanc P. Influence of work rate incremental rate on the exercise responses in patients with COPD. Med. Sci. Sports Exerc. 2000; 32: 1365–8. 4 Wasserman K, Hansen JE, Sue DY, Stringer WW, Sietsema KE, Sun XG, Whipp BJ. Clinical exercise testing. In: Principles of Exercise Testing and Interpretation. Lippincott Williams & Wilkins, Philadelphia, PA, 1999; 115–42. 5 Hartman JE, Boezen HM, de Greef MH, ten Hacken NHT. Physical and psychosocial factors associated with physical activity in © 2014 Asian Pacific Society of Respirology

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patients with chronic obstructive pulmonary disease. Arch. Phys. Med. Rehabil. 2013; 94: 2396–402. Vestbo J, Hurd SS, Agusti AG, Jones PW, Vogelmeier C, Anzueto A, Barnes PJ, Fabbri LM, Martinez FJ, Nishimura M et al. Global strategy for the diagnosis, management and prevention of chronic obstructive pulmonary disease, GOLD executive summary. Am. J. Respir. Crit. Care Med. 2013; 187: 347–65. Miller MR, Hankinson J, Brusasco V, Burgos F, Casaburi R, Coates A, Crapo R, Enright P, van der Grinten CP, Gustafsson P et al. Standardisation of spirometry. Eur. Respir. J. 2005; 26: 319– 38. Bestall JC, Paul EA, Garrod R, Garnham R, Jones PW, Wedzicha JA. Usefulness of the Medical Research Council (MRC) dyspnoea scale as a measure of disability in patients with chronic obstructive pulmonary disease. Thorax 1999; 54: 581–6. Jones CJ, Rikli RE, Beam WC. A 30-s chair-stand test as a measure of lower body strength in community-residing older adults. Res. Q. Exerc. Sport 1999; 70: 113–19. Cooper CB. The connection between chronic obstructive pulmonary disease symptoms and hyperinflation and its impact on exercise and function. Am. J. Med. 2006; 119(10 Suppl. 1): 21–31.

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11 Clark CJ, Cochrane LM, Mackay E, Paton B. Skeletal muscle strength and endurance in patients with mild COPD and the effects of weight training. Eur. Respir. J. 2000; 15: 92–7. 12 Mador MJ, Bozkanat E. Skeletal muscle dysfunction in chronic obstructive pulmonary disease. Respir. Res. 2001; 2: 216–24. 13 Gosselink R, Troosters T, Decramer M. Peripheral muscle weakness contributes to exercise limitation in COPD. Am. J. Respir. Crit. Care Med. 1996; 153: 976–80.

Supplementary Information Additional Supplementary Information can be accessed via the html version of this article at the publisher’s web-site: Supplementary Table S1 Patient characteristics (n = 113). Supplementary Table S2 Results of the cycle ergometer test (n = 113). Supplementary Table S3 Linear regression analyses with maximum workload as dependent variable.

Respirology (2015) 20, 352–355

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