Inaccuracy of Estimating Peak Work Rate from Six-Minute Walk Distance in Patients with COPD

1

ORIGINAL RESEARCH

Inaccuracy of Estimating Peak Work Rate from Six-Minute Walk Distance in Patients with COPD

Maurice J.H. Sillen,1 Jan H. Vercoulen,2,3 Alex J. van ’t Hul,4,5 Peter H.C. Klijn,6 Emiel F.M. Wouters,7,8 Dirk van Ranst,4 Jeannette B. Peters,2,3 Anton R.J. van Keimpema,6 Frits M.E. Franssen,1 Henk J.A.M. Otten,4,9 Johan Molema,3 Jerôme J. Jansen,10 and Martijn A. Spruit1

The research of Maurice J.H. Sillen is financially supported by grants from the Netherlands Asthma Foundation, Leusden, the Netherlands, Grant 3.4.09.024 and the Weijerhorst Foundation, Maastricht, the Netherlands.

Keywords: Cardiopulmonary exercise testing, Chronic obstructive pulmonary disease, Peak work rate, Six-minute walk distance.

Correspondence to: Maurice J.H. Sillen, MSc, PT, Program Development Centre, CIRO+, Centre of Expertise for Chronic Organ Failure, Hornerheide 1, 6085 NM, Horn, the Netherlands, phone +31 475 587 725, fax +31 475 587 666, email: [email protected]

Abstract

Introduction. The cardiopulmonary exercise test (CPET) and the 6-minute walk test (6MWT) are used to prescribe the appropriate training load for cycling and walking exercise in patients with chronic obstructive pulmonary disease (COPD). The primary aims were: (i) to compare estimated peak work rate (Wpeakestimated) derived from six existing Wpeak regression equations with actual peak work rate (Wpeakactual); and (ii) to derive a new Wpeak regression equation using six-minute walk distance (6MWD) and conventional outcome measures in COPD patients. Methods. In 2906 patients with COPD, existing Wpeak regression equations were used to estimate Wpeak using 6MWD and a new equation was derived after a stepwise multiple regression analysis. Results. The 6 existing Wpeak regression equations were inaccurate to predict Wpeakactual in 82% of the COPD patients. The new Wpeak regression equation differed less between Wpeakestimated and Wpeakactual compared to existing models. Still, in 74% of COPD patients Wpeakestimated and Wpeakactual differed more than (±) 5 watts. Conclusion. In conclusion, estimating peak work load from 6MWD in COPD is inaccurate. We recommend assessment of Wpeak using CPET during pre-rehabilitation assessment in addition to 6MWT.

COPD, 9:1–8, 2012ISSN: 1541-2555 print / 1541-2563 onlineCopyright © Informa Healthcare USA, Inc.DOI: 10.3109/15412555.2012.655866

1 Program Development Centre; CIRO+, Centre of Expertise for Chronic Organ Failure; Horn, the Netherlands

2 Department of Medical Psychology; Radboud University Nijmegen Medical Centre; Nijmegen, the Netherlands

3 Department of Pulmonary Diseases; Radboud University Nijmegen Medical Centre; Nijmegen, the Netherlands

4 Rehabilitation Centre Breda; Revant Rehabilitation Centre; Breda, the Netherlands

5 Department of pulmonary diseases, VU Medical Centre, Amsterdam, the Netherlands

6 Asthma Centre Heideheuvel; Merem Behandelcentra; Hilversum, the Netherlands

7 Director; CIRO+, Centre of Expertise for Chronic Organ Failure; Horn, the Netherlands

8 Department of Respiratory Medicine; Maastricht University Medical Centre (MUMC+); Maastricht, the Netherlands

9 Department of Respiratory Medicine; Erasmus Medical Center; Rotterdam, the Netherlands

10 Sports Training; CIRO+, Centre of Expertise for Chronic Organ Failure; Horn, the Netherlands Introduction

It is well-recognized that pulmonary rehabilitation is an important part of the integrated care of patients with chronic obstructive pulmonary disease (COPD) (1, 2). Pulmonary rehabilitation programs typically include com-ponents such as patient assessment, supervised exercise training, health education, nutritional modulation, and behavioural support (1, 3). Indeed, supervised exercise training is the cornerstone of a comprehensive, multidis-ciplinary pulmonary rehabilitation in COPD, which improves health status and exercise performance (4).

To date, about half of the exercise-based pulmonary rehabilitation pro-grams for patients with COPD use leg cycling ergometry as the main exercise training modality (1, 5, 6). International guidelines suggest that cycling train-ing of at least 8 weeks at an intensity of at least 60% of actual peak work rate (Wpeakactual) is required to improve health status and exercise performance in patients with COPD (1). Therefore, it is important to assess patients’ Wpeakactual during a pre-rehabilitation assessment in order to prescribe a patient-tailored training load (1).

CO

PD D

ownl

oade

d fr

om in

form

ahea

lthca

re.c

om b

y 80

.112

.253

.66

on 0

2/23

/12

For

pers

onal

use

onl

y.

Copyright © 2012 Informa Healthcare USA, Inc

2 M.J.H. Sillen et al.

The cardiopulmonary exercise test (CPET) on a sta-tionary cycle ergometer is recommended in daily clini-cal practice to determine baseline Wpeakactual (7). Based on the characterisation of pulmonary rehabilitation programmes in Canada (8) and the United kingdom (9) it is estimated that over 50% of the pulmonary reha-bilitation programs (outpatient and inpatient) do not perform pre-rehabilitation CPET. Therefore, exercise testing is mostly limited to field walking tests, like an incremental shuttle walk test or a 6-minute walk test (6MWT)(10).

Several authors (11–14) have developed regression equations to estimate peak work rate (Wpeakestimated) by using the 6-min walk distance (6MWD) of 22 to 53 patients with COPD (Table 1). Validation of these Wpeak regression equations in a large sample of patients with COPD seems necessary before clini-cal implementation can be considered. Indeed, Hol-land et al. (15) showed substantial variation between Wpeakestimated and Wpeakactual in 64 patients with COPD using the Wpeak regression equations of Hill et al. (12) and Luxton et al. (14). Moreover, generalizability of existing Wpeak regression equations is limited due to strict exclusion criteria, like use of supplemental oxygen (12, 14), ambulation aid during 6MWT (12), very mild symptoms (Medical Research Council, MRC, dyspnea grade 1) (13), and/or a body mass index (BMI, weight in kilograms divided by the square of height in meters) greater than 35 kg/m2 (12). Therefore, it seems reasonable to derive a new Wpeak regression equation in a large sample of patients with COPD entering pul-monary rehabilitation using 6MWD and a number of conventional characteristics of COPD, like forced expi-ratory volume in the first second (FEV1), gender, age, height and weight (16, 17).

The aim of the present study was two-fold: (i) to com-pare the accuracy of current Wpeak regression equa-tions in a large sample of patients with COPD entering pulmonary rehabilitation; and (ii) to derive a new Wpeak regression equation based on a large cohort of COPD

Table 1. Regression equations predicting peak work rate including 6-min walk distance in patients with COPD

Authors Wpeak regression equation

Hill et al. (#1) (14) (0.122 X 6MWD) + (72.683 X height) – 117.109

Hill et al. (#2) (14) 17.393 + (1.442 x6MWW [km·kg–1])

Luxton et al. (16) 103.217 + (30.50 × gender) + (–1.613 × age) + (0.002 × 6MWW [m·kg–1])

Cavalheri et al. (13) -27.9717 + [3.7792*(6MWD*FFM)]

Kozu et al. (#1) (15) (0.168 X 6MWD) -4.085

Kozu et al. (#2) (15) (2.310 X 6MWW [km·kg–1]) + 8.820

FEV1 = forced expiratory volume in 1 second; FFM = fat free mass; 6MWD = 6-min walk distance; 6MWW = 6-min walk-work (6MWD in meters multiplied by body weight in kilograms). Height in meters; 6MWD in meters; gender is given a value of 1 for male and 0 for female.

patients using 6MWD and conventional outcome mea-sures.

Methods

Data were extracted of 2906 patients with COPD who were referred to four specialized pulmonary rehabilita-tion centres in the Netherlands (n = 1522 in CIRO+ in Horn (2); n = 251 in UCCZ Dekkerswald Nijmegen; n =764 in Revant Rehabilitation Centre Breda; and n = 369 in Asthma Centre Heideheuvel Hilversum) from January 2005 to June 2010. Indeed, since January 2005 the participating four specialized pulmonary rehabilita-tion centres standardized test procedures according to international guidelines (7, 18) and in agreement with request from Dutch healthcare insurers.

All patients were referred by chest physicians from multiple hospitals for a comprehensive pulmonary rehabilitation program (2). Patients met the following inclusion criteria: (i) primary diagnosis of COPD (19); (ii) no acute COPD exacerbations in the past 4 weeks; and (iii) absence of co-morbidities precluding exercise testing, e.g., neuromuscular disorders or joint disorders in hip, leg and/or knee. Th ese retrospective analyses were institutional review board exempt due to the use of de-identified, preexisting data.

As part of a standardized routine baseline assessment (2) patients underwent, amongst other tests, a CPET in accordance with the latest international guidelines where Wpeakactual was determined (7). All exercise tests were performed on electromagnetically braked bicycle ergometers (UCCZ Dekkerswald Nijmegen and Asthma Centre Heideheuvel Hilversum: Lode, Groningen, the Netherlands; Revant Rehabilitation Centre Breda and CIRO+ Horn, Ergoline Ergoselect 200 P, Carefusion, Houten, The Netherlands).

Post-bronchodilator spirometry was performed according to international recommendations (20–22). All centres used lung function equipment of Carefusion (Houten, The Netherlands). Patients underwent physi-cal examination by a chest physician (including assess-ment of body weight and height) and medical history as described before (23). Fat-free mass index (FFMI, fat free mass in kilograms divided by the square of height in meters) was determined using bio-electrical impedance assessment (24). A 6MWT was performed according to ATS guidelines (18), including a practice walk (25). The best of two tests was used for further analysis.

All statistical analyses were performed using SPSS for Windows, Version 17.0.1 (SPSS, Inc., Chicago, Il, USA) and GraphPad Prism Version 4.03 (GraphPad Software, Inc., La Jolla, CA, USA). Continuous data were tested for normality and presented as mean and standard deviation unless otherwise stated. All data were normally distrib-uted. Agreement between the Wpeakestimated (using exist-ing Wpeak regression equations) and Wpeakactual was assessed using Bland and Altman plots and intraclass correlation coefficients (26). The Bland and Altman plot

CO

PD D

ownl

oade

d fr

om in

form

ahea

lthca

re.c

om b

y 80

.112

.253

.66

on 0

2/23

/12

For

pers

onal

use

onl

y.

Inaccuracy of Estimating Wpeak from 6MWD in COPD 3

www.copdjournal.com

Fair to moderate intraclass correlation coefficients (95% confidence interval) were found for the regression equations of Hill et al. (regression #1) 0.58 (0.56-0.61), Hill et al. (regression #2) (12) 0.59 (0.57-0.62), Luxton et al. (14) 0.68 (0.66-0.70), Cavalheri et al. (11) 0.74 (0.72-0.76), Kozu et al. (regression #1) 0.59 (0.57-0.62), and Kozu et al. (regression #2) 0.73 (0.71-0.74). The mean of Wpeakestimated and Wpeakactual resulted in a negative value in 19 patients in the regression equation of Cav-alheri et al. (11).

Proportion of COPD patients with a difference of only -5 to +5 watts between Wpeakestimated and Wpeakac-

tual varied amongst existing Wpeak regression equations: 22% for Hill et al. (#1) (Figure 1B); 20% for Hill et al. (#2) (12) (Figure 1D); 14% for Luxton et al. (14) (Figure 1F); 16% for Cavalheri et al. (11) (Figure 1H); 18% for Kozu et al. (#1) (Figure 1J); and 13% for Kozu et al. (#2) (13) (Figure 1L). The differences expressed as the quotient of Wpeakactual between Wpeakestimated and Wpeakactual were very broad in all regression equations (Table 3).

Derivation of a new Wpeak regression equationUsing the data of 2906 patients with COPD, single cor-relation coefficients of gender, age, height, body weight, FFM, 6MWD, and FEV1 with Wpeakactual were 0.23, 0.19, 0.37, 0.34, 0.40, 0.67, and 0.68, respectively (all p < 0.001). Abovementioned variables were retained in a stepwise multiple regression analysis. The new Wpeak regression equation is:

Wpeakestimated = -51.994 - (0.505*gender (1 for men, 0 for women)) - (0.234*age (in years)) + (0.091*height (in centimeters )) + (0.200*body weight (in kilograms)) + (0.353*FFM (in kilograms)) + (0.132*6MWD (in meters)) + (23.361*FEV1 (in litres)).

Accuracy of new Wpeak regression equationThe new Wpeak regression equation explains 67% of the variance in Wpeakactual. The mean difference between Wpeakestimated and Wpeakactual of the new regression equa-tions is 1 Watt (range: -128 to +84 watts; Figure 2A). The percentage of COPD patients with differences of -5 to +5 watts between Wpeakestimated and Wpeakactual was 26% (Figure 2B). Table 3 shows the percentage differ-ences between Wpeakestimated and Wpeakactual. The intrac-lass correlation coefficient (95% confidence interval) for Wpeakestimated and Wpeakactual for the new Wpeak regres-sion equation was 0.81 (0.79-0.82).

Differences between Wpeakactual and WpeakestimatedTable 4 shows the characteristics of the COPD patients after stratification for a difference between Wpeakestimated and Wpeakactual of <-6 watts, -5 to +5 watts or >+6 watts of the new Wpeak regression equation. Patients in the middle group (-5 to +5 watts) contained a higher pro-portion of women, were shorter, had a lower body weight and fat-free mass, and a worse pulmonary function com-pared to groups where the new Wpeak regression equa-tion was underestimating (<-6 watts) or overestimating

shows the mean of Wpeakestimated and Wpeakactual against the difference of Wpeakestimated and Wpeakactual. A pri-ori, the authors defined a difference of -5 to +5 watts between Wpeakestimated and Wpeakactual as acceptable. Pearson single correlation coefficients were calculated and a stepwise multiple regression analysis was used to develop a new Wpeak regression equation. Differences were considered significant at p < 0.05 (two-tailed).

Results

CharacteristicsOn average, patients had mild-to-very severe COPD (GOLD I: n = 121; GOLD II: n = 832; GOLD III: n = 1075; and GOLD IV: n = 878); a slight overweight; a normal fat free mass; and a poor peak and functional exercise capacity (Table 2). Of the included patients, 24% used long-term oxygen therapy and 28% used a walking aid during the 6MWT. Oxygen supplement was in all centres provided through a nasal cannula.

Accuracy of existing Wpeak regression equationsFigure 1 shows Bland and Altman plots and the distribu-tion of the COPD patients according to existing Wpeak regression equations. Clear differences were found between Wpeakestimated and Wpeakactual for the regression equations of Hill et al. (regression #1) (mean: -6 watts (range: -177 to +70); Figure 1A), Hill et al. (regression #2) (-41 watts (-163 to +68); Figure 1C), Luxton et al. (14) (+16 watts (-136 to +139); Figure 1E), Cavalheri et al. (11) (-16 watts (-158 to +93); Figure 1G), Kozu et al. (regression #1) (13)(+3 watts (-183 to +73); Figure 1I), and Kozu et al. (regression #2) (13)(+16 watts (-128 to +84); Figure 1K).

Table 2. Characteristics

Variable Value Mean ± SD

Sex M/F 1529/1377

Age years 62.9 ± 9.4

Height centimetres 168 ± 9.4

Body weight kg 73.3 ± 17.4

BMI kg/m2 25.8 ± 5.5

FFM kg 47.2 ± 9.6

FFMI kg/m2 16.6 ± 2.5

FEV1 litres 1.19 ± 0.54

FEV1 % pred 44.0 ± 17.6

FEV1/VC % 39.4 ± 14.1

Wpeakactual watts 60.0 ± 33.2

6MWD meters 400 ± 120

M = male; F = female; kg = kilogram; BMI = body mass index; FFM = fat-free mass; FFMI = fat-free mass index; FEV1 = forced expiratory volume in 1 second; VC = vital capacity; Wpeakactual = actual peak work rate; % pred = percentage predicted value; CPET = cardiopulmonary exercise test; 6MWD = distance achieved by the 6-minute walk test.

CO

PD D

ownl

oade

d fr

om in

form

ahea

lthca

re.c

om b

y 80

.112

.253

.66

on 0

2/23

/12

For

pers

onal

use

onl

y.

Copyright © 2012 Informa Healthcare USA, Inc

4 M.J.H. Sillen et al.

Figure 1. Bland and Altman plots and distribution of COPD patients of the existing Wpeak regression equations.

-50 50 100 150 200 250

-200

-150

-100

-50

50

100

150A

(Wpeakestimated+Wpeakactual) / 2

Wp

eak

esti

mat

ed-W

pea

k act

ual

<-26

-25-

-16

-15-

-6-5

-56-

1516

-25

>26

0

5

10

15

20

25

30

35

Hill1

B

Wpeakestimated-Wpeakactual (Watts)

% C

OPD

pat

ient

s

-50 50 100 150 200 250

-200

-150

-100

-50

50

100

150C

(Wpeakestimated+Wpeakactual) / 2

Wp

eak

esti

mat

ed-W

pe

ak a

ctu

al

<-26

-25-

-16

-15-

-6-5

-56-

1516

-25

>26

0

5

10

15

20

25

30

35

Hill2

D

Wpeakestimated-Wpeakactual (Watts)

% C

OPD

pat

ient

s

-50 50 100 150 200 250

-200

-150

-100

-50

50

100

150E

(Wpeakestimated+Wpeakactual) / 2

Wp

eak

esti

mat

ed-W

pe

ak a

ctu

al

<-26

-25-

-16

-15-

-6-5

-56-

1516

-25

>26

0

5

10

15

20

25

30

35

Luxton

F

W peakestimated-Wpeakactual (Watts)

% C

OP

D p

atie

nts

-50 50 100 150 200 250

-200

-150

-100

-50

50

100

150

G

(Wpeakestimated+Wpeakactual) / 2

Wp

eak

esti

mat

ed-W

pe

ak a

ctu

al

<-26

-25-

-16

-15-

-6-5

-56-

1516

-25

>26

0

5

10

15

20

25

30

35

Cav alheri

H

Wpeakestimated-Wpeakactual (Watts)

% C

OP

D p

ati

en

ts

-50 50 100 150 200 250

-200

-150

-100

-50

50

100

150

I

(Wpeakestimated+Wpeakactual) / 2

Wp

eak

esti

mat

ed-W

pe

ak a

ctu

al

<-26

-25-

-16

-15-

-6-5

-56-

1516

-25

>26

0

5

10

15

20

25

30

35

Kozu1

J

Wpeakestimated-Wpeakactual (Watts)

% C

OP

D p

ati

en

ts

-50 50 100 150 200 250

-200

-150

-100

-50

50

100

150

K

(Wpeakestimated+Wpeakactual) / 2

Wp

eak

esti

mat

ed-W

pe

ak a

ctu

al

<-26

-25-

-16

-15-

-6-5

-56-

1516

-25

>26

0

5

10

15

20

25

30

35

Kozu2

L

Wpeakestimated-Wpeakactual (Watts)

% C

OP

D p

ati

en

ts

CO

PD D

ownl

oade

d fr

om in

form

ahea

lthca

re.c

om b

y 80

.112

.253

.66

on 0

2/23

/12

For

pers

onal

use

onl

y.

Inaccuracy of Estimating Wpeak from 6MWD in COPD 5

www.copdjournal.com

(>+6 watts) Wpeak (Table 3). Similar findings were found after using the existing Wpeak regression equa-tions (see online supplement for details).

Discussion

The main finding of the present study is the lack of accuracy to predict Wpeakactual by using existing Wpeak regression equations. Also a new regression equation, which includes more conventional clinical variables than previous Wpeak regression equations, shows a poor accuracy for individual patients with COPD. Indeed, in 74% of COPD patients Wpeakestimated and Wpeakac-

tual differed more than (±) 5 watts in the new Wpeak regression equation. Moreover, in the group of COPD patients where Wpeakestimated-Wpeakactual was between -5 and +5 watts, the difference expressed as percentage of Wpeakactual ranged still between -34% and 43%. So, Wpeakactual needs to be assessed in order to prescribe a patient-tailored training load during cycle ergometry training.

Cycling at 60% of Wpeak or higher is considered sufficient to elicit physiologic training effects (1). Due to the low absolute Wpeakactual in patients with COPD

(23), we decided that a difference of -5 to +5 watts between Wpeakestimated and Wpeakactual was acceptable to target cycling load during exercise training. However, all Wpeak regression equations (table 1), including the new regression equation, show a broad range of differ-ences between Wpeakestimated and Wpeakactual (Figures 1 and 2). Therefore, 82% of the patients in the existing Wpeak regression equations and 74% of the patients in the newly derived Wpeak regression equation had a dif-ference between Wpeakestimated and Wpeakactual <-5 watts and >+5 watts. Moreover, the mean of the estimated and actual Wpeak resulted in a negative value in 19 COPD patients with the regression equation of Caval-heri et al. (11) (Figure 1G) and in 3 COPD patients with the new Wpeak regression equation (Figure 2A). So, using Wpeak regression equations will result in an over- or underestimation of the Wpeak. In turn, most COPD patients would start the exercise training program not at an optimal cycling training load. This is in line with the findings of Holland and colleagues (15).

Wpeak is dependent of multiple clinical confound-ing variables, like gender, age and FFM (27-29). Nevertheless, only the Wpeak regression equation of Luxton et al. (14) included gender and age; while

Table 3. Percentage differences between Wpeakestimated and Wpeakactual

Regression equation Whole group < -6 Watts -5 to +5 Watts > +6 Watts

Hill et al. (#1) (14) 11 (-88, +2150) -29 (-88, -6) 0 (-33, +40) 72 (7, 2150)

Hill et al. (#2) (14) 25 (-68, +2400) -25 (-68, -6) 1 (-13, +21) 78 (5, 2400)

Luxton et al. (16) 50 (-121, +2400) -29 (-121, -3) 0 (-100, +40) 86 (5, 2400)

Cavalheri et al. (13) -24 (-380, +1200) -44 (-380, -5) -2 (-100, +125) 60 (5, 1200)

Kozu et al. (#1) (15) 29 (-83, +2500) -27 (-83, -6) 1 (-27, +80) 73 (6, 2500)

Kozu et al. (#2) (15) 55 (-65, +2950) -20 (-65, -4) 1 (-17, +33) 80 (3, 2950))

New regression equation 13 (-280, +1550) -27 (-280, -5) 1 (-31, +42) 60 (5, 1550)

Data are presented as mean (range).

-50 50 100 150 200 250

-200

-150

-100

-50

50

100

150A

(Wpeakestimated+Wpeakactual) / 2

Wp

eak

esti

mat

ed-W

pea

k act

ual

<-26

-25-

-16

-15-

-6-5

-56-

1516

-25

>26

0

5

10

15

20

25

30

35B

Wpeakestimated-Wpeakactual (Watts)

% C

OP

D p

ati

en

ts

Figure 2. Bland and Altman plots and distribution of COPD patients of the new Wpeak regression equations.

CO

PD D

ownl

oade

d fr

om in

form

ahea

lthca

re.c

om b

y 80

.112

.253

.66

on 0

2/23

/12

For

pers

onal

use

onl

y.

Copyright © 2012 Informa Healthcare USA, Inc

6 M.J.H. Sillen et al.

the Wpeak regression equation of Cavalheri et al. (11) included FFM. This may partially explain the moderate accuracy of the existing Wpeak regression equations. Then again, the new Wpeak regression equation did include gender, age, height, body weight, fat-free mass, 6MWD and FEV1. Obviously, the new Wpeak regression equation needs validation in a new cohort of patients with COPD, but it still appears not highly accurate to predict Wpeakactual (Figure 2).

A possible explanation of the moderate accuracy to estimate Wpeakactual is that the CPET and the 6MWT measure different aspects of exercise tolerance. For example, in patients with COPD peak aerobic capacity was similar for CPET and 6MWT, while ventilation, carbon dioxide production, respiratory exchange ratio and arterial lactate concentration were lower during the 6MWT compared with CPET (30). Thereby, dur-ing 6MWT oxygen uptake showed a steady-state profile from min 3 to 6 of the test which did not occur during CPET (30). In a recent study ventilatory responses were compared during an incremental treadmill test versus CPET (31). At peak exercise, partial pressure of alveo-lar oxygen and peak lactate levels were higher during cycling and the anaerobic threshold occurred at a lower oxygen uptake during cycling versus walking (31).

Oxyhemoglobin desaturation was greater during walking compared with cycling (31). Man and colleagues showed a significant reduction in maximum voluntary

contraction force of the quadriceps after cycling, while after walking no change was found in maximum volun-tary contraction force (32). Quadriceps fatigability is also reflected by the onset of leg discomfort occurred at lower oxygen uptake values for cycling compared with treadmill walking.

In addition, the performance of whole body exercise (e.g., walking, cycling) requires complex interactions involving many similar physiological functions.

In human exercise a comparatively high level of specificity exists (33). Although there is some carryover of training effects, the specificity principle of training states that to make adequate progression in one type of activity, training must closely match that activity (33). Moreover, activity specific outcome tools are essential to obtain pertinent results (consistency between train-ing and testing). Because walking exercise outputs (on treadmill or field tests) do not relate exactly to peak work in cycle ergometry it was perhaps unreasonable to expect a regression equation to work in any case.

Some methodological considerations need to be made. Although the exercise tests were performed in the four centres at the same standardized manner, the equipment among the centres differ from each other. Also, it can be argued that the existing Wpeak regression equations are region-specific, and, in turn, not to be validated in a large cohort of Dutch COPD patients which in particular consisted of Caucasians.

Table 4. Characteristics of the study subjects after stratification for Wpeakestimated-Wpeakactual

Variable Value

Wpeakestimated - Wpeakactual

< -6 Watts -5 to +5 Watts > +6 Watts

Patients Numbers (%) 1029 (35) 761 (26) 1116 (38)

Sex M/F 568/461 356/405 605/511

GOLD, I/II//III/IV numbers 40/301/353/335 23/192/290/256 58/339/432/287

Age years 63.0 ± 9.6 63.3 ± 9.4 62.7 ± 9.3

Height centimetres 169 ± 9.3* 167 ± 8.9 169 ± 9.7*

Body weight kg 74.2 ± 16.7* 70.7 ± 16.0 74.3 ± 18.8*

BMI kg/m2 26.0 ± 5.1* 25.3 ± 5.1 26.0 ± 6.0*

FFM kg 47.7 ± 9.6* 45.5 ± 8.8 47.9 ± 10.1*

FFMI kg/m2 16.7 ± 2.4* 16.3 ± 2.3 16.7 ± 2.7*

FEV1 litres 1.21 ± 0.58* 1.09 ± 0.47 1.24 ± 0.54*

FEV1 % pred 43.9 ± 17.4 42.4 ± 17.1 45.4 ± 18.1*

FEV1/VC % 40.7 ± 14.6* 37.8 ± 12.7 39.4 ± 14.5

Wpeakactual watts 79.4 ± 37.2* 56.2 ± 24.5 44.7 ± 24.4*‡

Wpeakestimated watts 60.5 ± 31.2 56.1 ± 24.5 62.5 ± 24.7*

6 MWD meters 396 ± 133 397 ± 115 405 ± 111

* p < 0.05 versus -5 to 5 Watts.‡ p < 0.05 versus < -6 Watts.M = male; F = female; BMI = body mass index; FFM = fat-free mass; FFMI = fat-free mass index; FEV1 = forced expiratory volume in 1 second; VC = vital capacity; CPET = cardiopulmonary exercise test; Wpeakactual = actual peak work rate; Wpeakestimated = estimated peak work rate; 6MWD = distance achieved by the 6-minute walk test; % pred = percentage predicted value.

CO

PD D

ownl

oade

d fr

om in

form

ahea

lthca

re.c

om b

y 80

.112

.253

.66

on 0

2/23

/12

For

pers

onal

use

onl

y.

Inaccuracy of Estimating Wpeak from 6MWD in COPD 7

www.copdjournal.com

Other ethnic groups and patients in other demographic regions may require other regression equations. Then again, Holland et al. showed a poor accuracy of the existing Australian-derived Wpeak regression equa-tions to predict Wpeakactual in a group 64 Australian COPD patients (15).

In about 50% of the pulmonary rehabilitation pro-grams pre-rehabilitation CPET is not assessed. This is often due to limited resources, staff and expertise neces-sary to conduct a CPET (8, 9). Nevertheless, the current results do justify pre-rehabilitation CPET, especially if the focus is high-intensity cycle-ergometry training (1). Other methods to anchor the training intensity such as dyspnoea rating, or pulse rate are less well defined or not reliable without the results of CPET.

In fact, CPET is generally important in the clini-cal assessment and evaluation of patients with COPD. CPET is recommended to determine exercise capacity, to determine the magnitude of hypoxemia, to establish exercise limitation(s) and to assess other potential con-tributing factors, especially occult ischemic heart dis-ease (7). Regarding the specificity of exercise training it can be argued to choose an exercise test which suits best to the exercise modality which will be trained.

It is recommended that CPET should be applied to assess peak work rate only in those programmes that use cycle ergometry for training (7), which may not neces-sarily constitute the majority of programmes. Indeed, programmes which use walk training as main exercise modality are also beneficial for patients with COPD (34). Moreover, these (brisk) walking programmes may want to consider the use of an incremental shuttle walk test or a 6MWT as exercise test.

In conclusion, estimating Wpeak from 6MWD is inaccurate in patients with COPD, also when conven-tional clinical variables are used in a Wpeak regression equation. Therefore, we recommend assessment of Wpeak using CPET during pre-rehabilitation assess-ment in addition to 6MWT in patients with COPD.

Declaration of interest

The authors do not have any conflict of interest with the contents of the present manuscript. The authors are responsible for the content and the writing of this paper.

References 1. Nici L, Donner C, Wouters E, Zuwallack R, Ambrosino N,

Bourbeau J, et al. American Thoracic Society/European Respiratory Society statement on pulmonary rehabilitation. Am J Respir Crit Care Med 2006; 173(12):1390–1413. Epub 2006/06/09.

2. Spruit MA, Vanderhoven-Augustin I, Janssen PP, Wouters EF. Integration of pulmonary rehabilitation in COPD. Lancet 2008; 371(9606):12–13. Epub 2008/01/08.

3. Ries AL, Bauldoff GS, Carlin BW, Casaburi R, Emery CF, Mahler DA, et al. Pulmonary Rehabilitation: Joint ACCP/

AACVPR Evidence-Based Clinical Practice Guidelines. Chest 2007; 131(5 Suppl):4S–42S. Epub 2007/05/15.

4. Spruit MA, Gosselink R, Troosters T, De Paepe K, Decramer M. Resistance versus endurance training in patients with COPD and peripheral muscle weakness. Eur Respir J 2002; 19(6):1072–1078. Epub 2002/07/11.

5. Spruit MA, Wouters EF. New modalities of pulmonary rehabilitation in patients with chronic obstructive pulmonary disease. Sports Med 2007; 37(6):501–518. Epub 2007/05/17.

6. Lacasse Y, Goldstein R, Lasserson TJ, Martin S. Pulmonary rehabilitation for chronic obstructive pulmonary disease. Cochrane Database Syst Rev 2006(4):CD003793. Epub 2006/10/21.

7. ATS/ACCP. Statement on cardiopulmonary exercise testing. Am J Respir Crit Care Med 2003; 167(2):211–277.

8. Brooks D, Sottana R, Bell B, Hanna M, Laframboise L, Selvanayagarajah S, et al. Characterization of pulmonary rehabilitation programs in Canada in 2005. Can Respir J 2007; 14(2):87–92. Epub 2007/03/21.

9. Yohannes AM, Connolly MJ. Pulmonary rehabilitation programmes in the UK: a national representative survey. Clin Rehabil 2004; 18(4):444–449. Epub 2004/06/08.

10. Spruit MA, Watkins ML, Edwards LD, Vestbo J, Calverley PM, Pinto-Plata V, et al. Determinants of poor 6-min walking distance in patients with COPD: the ECLIPSE cohort. Respir Med 2010; 104(6):849–857. Epub 2010/05/18.

11. Cavalheri V, Hernandes NA, Camillo CA, Probst VS, Ramos D, Pitta F. Estimation of maximal work rate based on the 6-minute walk test and fat-free mass in chronic obstructive pulmonary disease. Arch Phys Med Rehabil 2010; 91(10):1626–1628. Epub 2010/09/30.

12. Hill K, Jenkins SC, Cecins N, Philippe DL, Hillman DR, Eastwood PR. Estimating maximum work rate during incremental cycle ergometry testing from six-minute walk distance in patients with chronic obstructive pulmonary disease. Arch Phys Med Rehabil 2008; 89(9):1782–1787. Epub 2008/09/02.

13. Kozu R, Jenkins S, Senjyu H, Mukae H, Sakamoto N, Kohno S. Peak power estimated from 6-minute walk distance in Asian patients with idiopathic pulmonary fibrosis and chronic obstructive pulmonary disease. Respirology 2010; 15(4):706–13. Epub 2010/04/23.

14. Luxton N, Alison JA, Wu J, Mackey MG. Relationship between field walking tests and incremental cycle ergometry in COPD. Respirology 2008; 13(6):856–862. Epub 2008/09/25.

15. Holland AE, Hill K, Alison JA, Luxton N, Mackey MG, Hill CJ, et al. Estimating peak work rate during incremental cycle ergometry from the 6-minute walk distance: differences between reference equations. Respiration. 2011; 81(2):124–128. Epub 2010/04/02.

16. Jones NL, Makrides L, Hitchcock C, Chypchar T, McCartney N. Normal standards for an incremental progressive cycle ergometer test. Am Rev Respir Dis 1985; 131(5):700–708. Epub 1985/05/01.

17. Gosselink R, Troosters T, Decramer M. Peripheral muscle weakness contributes to exercise limitation in COPD. Am J Respir Crit Care Med 1996; 153(3):976–980.

18. ATS statement. Guidelines for the six-minute walk test. Am J Respir Crit Care Med 2002; 166(1):111–117. Epub 2002/07/02.

19. Rabe KF, Hurd S, Anzueto A, Barnes PJ, Buist SA, Calverley P, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med 2007; 176(6):532–535. Epub 2007/05/18.

20. Miller MR, Hankinson J, Brusasco V, Burgos F, Casaburi R, Coates A, et al. Standardisation of spirometry. Eur Respir J 2005; 26:319–38.

CO

PD D

ownl

oade

d fr

om in

form

ahea

lthca

re.c

om b

y 80

.112

.253

.66

on 0

2/23

/12

For

pers

onal

use

onl

y.

Copyright © 2012 Informa Healthcare USA, Inc

8 M.J.H. Sillen et al.

21. Macintyre N, Crapo RO, Viegi G, Johnson DC, van der Grinten CP, Brusasco V, et al. Standardisation of the single-breath determination of carbon monoxide uptake in the lung. Eur Respir J 2005; 26:720–735.

22. Wanger J, Clausen JL, Coates A, Pedersen OF, Brusasco V, Burgos F, et al. Standardisation of the measurement of lung volumes. Eur Respir J 2005; 26:511–522.

23. Spruit MA, Pennings HJ, Janssen PP, Does JD, Scroyen S, Akkermans MA, et al. Extra-pulmonary features in COPD patients entering rehabilitation after stratification for MRC dyspnea grade. Respir Med 2007; 101(12):2454–2463. Epub 2007/09/04.

24. Baarends EM, van Marken Lichtenbelt WD, Wouters EF, Schols AM. Body-water compartments measured by bio-electrical impedance spectroscopy in patients with chronic obstructive pulmonary disease. Clin Nutr 1998;17(1):15–22. Epub 1999/04/17.

25. Hernandes NA, Wouters EF, Meijer K, Annegarn J, Pitta F, Spruit MA. Reproducibility of 6-minute walking test in patients with COPD. Eur Respir J 2010. Epub 2010/12/24.

26. Bland JM, Altman DG. Measurement error proportional to the mean. BMJ 1996; 313(7049):106. Epub 1996/07/13.

27. Baarends EM, Schols AM, Mostert R, Wouters EF. Peak exercise response in relation to tissue depletion in patients with chronic obstructive pulmonary disease. Eur Respir J 1997; 10(12):2807–2813. Epub 1998/03/11.

28. Carter R, Holiday DB, Stocks J, Grothues C, Tiep B. Predicting oxygen uptake for men and women with moderate to severe chronic obstructive pulmonary disease. Arch Phys Med Rehabil 2003; 84(8):1158–1164. Epub 2003/08/15.

29. Vaes AW, Wouters EF, Franssen FM, Uszko-Lencer NH, Stakenborg KH, Westra M, et al. Task-related oxygen uptake during domestic activities of daily life in patients with COPD and healthy elderly subjects. Chest 2011; 140(4):970–979. Epub 2011/03/19.

30. Troosters T, Vilaro J, Rabinovich R, Casas A, Barbera JA, Rodriguez-Roisin R, et al. Physiological responses to the 6-min walk test in patients with chronic obstructive pulmonary disease. Eur Respir J 2002; 20(3):564–569. Epub 2002/10/03.

31. Mahler DA, Gifford AH, Waterman LA, Ward J, Machala S, Baird JC. Mechanism of greater oxygen desaturation during walking compared with cycling in COPD. Chest 2011. Epub 2011/01/29.

32. Man WD, Soliman MG, Gearing J, Radford SG, Rafferty GF, Gray BJ, et al. Symptoms and quadriceps fatigability after walking and cycling in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2003; 168(5):562–567. Epub 2003/06/28.

33. American College of Sports Medicine Position Stand. The recommended quantity and quality of exercise for developing and maintaining cardiorespiratory and muscular fitness, and flexibility in healthy adults. Med Sci Sports Exerc 1998; 30(6):975–991. Epub 1998/06/13.

34. Leung RW, Alison JA, McKeough ZJ, Peters MJ. Ground walk training improves functional exercise capacity more than cycle training in people with chronic obstructive pulmonary disease (COPD): a randomised trial. J Physiother 2010; 56(2):105–112. Epub 2010/05/21.

Online supplementThe online supplement shows the characteristics of the COPD patients after stratification for a difference between Wpeakestimated and Wpeakactual of <-6 watts, -5 to +5 watts or >+6 watts of the regression equations of Hill et al. (regression #1), Hill et al. (regression #2), Luxton et al., Cavalheri et al., Kozu et al. (regression #1), and Kozu et al. (regression #2).

CO

PD D

ownl

oade

d fr

om in

form

ahea

lthca

re.c

om b

y 80

.112

.253

.66

on 0

2/23

/12

For

pers

onal

use

onl

y.