Patterns of Physical Activity Progression in Patients With COPD

Koreny, Maria; Demeyer, Heleen; Benet, Marta; Arbillaga-Etxarri, Ane; Balcells, Eva; Barberán-García, Anael; Gimeno‐Santos, Elena; Hopkinson, Nicholas S; Jong, Corina de; Karlsson, Niklas; Louvaris, Zafeiris; Polkey, Michael I.; Puhan, Milo A.; Rabinovich, Roberto; Rodríguez-Roisín, Robert; Vall-Casas, Pere; Vogiatzis, Ioannis; Troosters, Thierry; Garcia‐Aymerich, Judith

doi:10.1016/j.arbres.2020.08.001

Cited by 8 publications

(8 citation statements)

References 39 publications

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“…In our study, we were able to identify that people with COPD from profiles 1, 2 and 3 might benefit from pulmonary rehabilitation (exercise, education and psychosocial support) to target their activity-related dyspnoea, impact of disease, lower-limb muscle dysfunction and/or functional status impairment [ 34 ]. Profiles among people with COPD who could benefit from pulmonary rehabilitation and physical activity promotion to address their symptoms, exercise intolerance and functional status impairments have been previously reported [ 8 , 10 , 32 , 35 – 37 ]. Those in profiles 1 and 3 might also benefit from dietary counselling and calorie restriction plus resistance exercise training [ 38 , 39 ] and referral for comorbidities’ management [ 40 ], due to their high BMI and severity of comorbidities.…”

Section: Discussionmentioning

confidence: 99%

COPD profiles and treatable traits using minimal resources: identification, decision tree and stability over time

et al. 2022

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Background and objective Profiles of people with chronic obstructive pulmonary disease (COPD) often do not describe treatable traits, lack validation and/or their stability over time is unknown. We aimed to identify COPD profiles and their treatable traits based on simple and meaningful measures; to develop and validate a decision tree and to explore profile stability over time. Methods An observational, prospective study was conducted. Clinical characteristics, lung function, symptoms, impact of the disease (COPD Assessment Test—CAT), health-related quality of life, physical activity, lower-limb muscle strength and functional status were collected cross-sectionally and a subsample was followed-up monthly over six months. A principal component analysis and a clustering procedure with k-medoids were applied to identify profiles. A decision tree was developed and validated cross-sectionally. Stability was explored over time with the ratio between the number of timepoints that a participant was classified in the same profile and the total number of timepoints (i.e., 6). Results 352 people with COPD (67.4 ± 9.9 years; 78.1% male; FEV1 = 56.2 ± 20.6% predicted) participated and 90 (67.6 ± 8.9 years; 85.6% male; FEV1 = 52.1 ± 19.9% predicted) were followed-up. Four profiles were identified with distinct treatable traits. The decision tree included CAT (< 18 or ≥ 18 points); age (< 65 or ≥ 65 years) and FEV1 (< 48 or ≥ 48% predicted) and had an agreement of 71.7% (Cohen’s Kappa = 0.62, p < 0.001) with the actual profiles. 48.9% of participants remained in the same profile whilst 51.1% moved between two (47.8%) or three (3.3%) profiles over time. Overall stability was 86.8 ± 15%. Conclusion Four profiles and treatable traits were identified with simple and meaningful measures possibly available in low-resource settings. A decision tree with three commonly used variables in the routine assessment of people with COPD is now available for quick allocation to the identified profiles in clinical practice. Profiles and treatable traits may change over time in people with COPD hence, regular assessments to deliver goal-targeted personalised treatments are needed.

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Section: Discussionmentioning

confidence: 99%

COPD profiles and treatable traits using minimal resources: identification, decision tree and stability over time

et al. 2022

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“… 3 , 47 Moreover, a recent study analysing physical activity progression over time identified that a higher mMRC dyspnoea score was independently related to an inactive pattern. 48 These observations are most likely due to the respiratory mechanical constraints resulting from the development of dynamic hyperinflation. 49 , 50 Finally, regarding the independent association between the CAT score and inactivity observed in our study, quality of life was consistently related to physical activity in a former systematic review analysing the determinants and outcomes of physical activity in COPD.…”

Section: Discussionmentioning

confidence: 99%

Discriminant Validity of a Single Clinical Question for the Screening of Inactivity in Individuals Living with COPD

Ramon¹,

Esteban²,

Ortega³

et al. 2022

COPD

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Introduction Quantifying physical activity in chronic obstructive pulmonary disease (COPD) with questionnaires and activity monitors in clinical practice is challenging. The aim of the present study was to analyse the discriminant validity of a single clinical question for the screening of inactive individuals living with COPD. Methods A multicentre study was carried out in stable COPD individuals both in primary and tertiary care. Patients wore the Dynaport accelerometer for 8 days and then answered 5 physical activity questions developed for the study, referring to the week in which their physical activity was monitored. Receiver operating characteristic (ROC) curve analysis with physical activity level (PAL) as the gold standard reference was used to determine the best cut-off point for each of the 5 clinical physical activity questions tested. Results A total of 86 COPD participants were analysed (males 68.6%; mean (SD) age 66.6 (8.5) years; FEV 1 50.9 (17.3)% predicted; mean of 7305 (3906) steps/day). Forty-two (48.8%) participants were considered physically inactive (PAL ≤1.69). Answers to 4 out of 5 questions significantly differed in active vs inactive patients. The Kappa index and ROC curves showed that the answer to the question “On average, how many minutes per day do you walk briskly?” had the best discriminative capacity for inactivity, with an area under the curve (AUC) (95% Confidence interval (CI)) of 0.73 (0.63–0.84) and 30 min/day was identified as the best cut-off value (sensitivity (95% CI): 0.75 (0.60–0.87); specificity: 0.76 (0.61–0.88)). Conclusion The present results indicate that self-reported brisk walk time lower than 30 min/day may be a valid tool for the screening of inactivity in individuals living with COPD in routine care, if more detailed physical activity measures are not feasible.

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“…Likewise, Bradley et al [21] reported that neither lung function (FEV 1 % predicted) nor disease severity (BSI score) was correlated with sedentary behaviour in patients with bronchiectasis. Data collected from patients with COPD have shown that physical activity decliners vary from 35% to 59% over time [41,42], but the clinical characteristics could not predict or explain the subsequent patterns of decline, included the number of exacerbations [42][43][44][45]. This indicates that the common clinical and functional assessments are unsuitable for use as indicators of risk of physical activity decline and/or increase in sedentary behaviour, which further highlights the need for further longitudinal and objective assessment in clinical settings.…”

Section: Discussionmentioning

confidence: 99%

“…This indicates that the common clinical and functional assessments are unsuitable for use as indicators of risk of physical activity decline and/or increase in sedentary behaviour, which further highlights the need for further longitudinal and objective assessment in clinical settings. Moving forward, the whole spectrum of those behaviours must be included, accounting for the potential impacts of psychological, interpersonal, social, and environmental correlates in the assessment [5,42,46].…”

Section: Discussionmentioning

confidence: 99%

Exacerbations and Changes in Physical Activity and Sedentary Behaviour in Patients with Bronchiectasis after 1 Year

Alcaraz-Serrano

Arbillaga-Etxarri

Oscanoa

et al. 2021

JCM

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Background: Low physical activity and high sedentary behaviour in patients with bronchiectasis are associated with hospitalisation over one year. However, the factors associated with longitudinal changes in physical activity and sedentary behaviour have not been explored. We aimed to identify clinical and sociodemographic characteristics related to a change in physical activity and sedentary behaviour in patients with bronchiectasis after one year. Methods: This was a prospective observational study during which physical activity measurements were recorded using a SenseWear Armband for one week at baseline and at one year. At each assessment point, patients were classified as active or inactive (measured as steps per day) and as sedentary or not sedentary (measured as sedentary time). Results: 53 patients with bronchiectasis were analysed, and after one year, 18 (34%) had worse activity and sedentary levels. Specifically, 10 patients became inactive and sedentary. Multivariable analysis showed that the number of exacerbations during the follow-up period was the only outcome independently associated with change to higher inactivity and sedentary behaviour (odds ratio (OR), 2.19; 95% CI, 1.12 to 4.28). Conclusions: The number of exacerbations in patients with bronchiectasis was associated with changes in physical activity and sedentary behaviour. Exacerbation prevention may appear as a key factor in relation to physical activity and sedentary behaviour in patients with bronchiectasis.

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Patterns of Physical Activity Progression in Patients With COPD

Cited by 8 publications

References 39 publications

COPD profiles and treatable traits using minimal resources: identification, decision tree and stability over time

COPD profiles and treatable traits using minimal resources: identification, decision tree and stability over time

Discriminant Validity of a Single Clinical Question for the Screening of Inactivity in Individuals Living with COPD

Exacerbations and Changes in Physical Activity and Sedentary Behaviour in Patients with Bronchiectasis after 1 Year

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