TY - JOUR
T1 - Patrones de progresión de la actividad física en pacientes con EPOC
AU - The Urban Training Study Group and PROactive Consortium members
AU - The Urban Training Study Group
AU - The PROactive Consortium members
AU - Koreny, Maria
AU - Demeyer, Heleen
AU - Benet, Marta
AU - Arbillaga-Etxarri, Ane
AU - Balcells, Eva
AU - Barberan-Garcia, Anael
AU - Gimeno-Santos, Elena
AU - Hopkinson, Nicholas S.
AU - De Jong, Corina
AU - Karlsson, Niklas
AU - Louvaris, Zafeiris
AU - Polkey, Michael I.
AU - Puhan, Milo A.
AU - Rabinovich, Roberto A.
AU - Rodríguez-Roisin, Robert
AU - Vall-Casas, Pere
AU - Vogiatzis, Ioannis
AU - Troosters, Thierry
AU - Garcia-Aymerich, Judith
AU - Delgado, Anna
AU - Torrent-Pallicer, Jaume
AU - Vilaró, J.
AU - Rodriguez-Roisín, Robert
AU - Chiaradía, Diego A.Rodríguez
AU - Marín, Alicia
AU - Ortega, Pilar
AU - Celorrio, Nuria
AU - Monteagudo, Mónica
AU - Montellà, Nuria
AU - Muñoz, Laura
AU - Toran, Pere
AU - Simonet, Pere
AU - Jané, Carme
AU - Martín-Cantera, Carlos
AU - Borrell, Eulàlia
AU - Ivanoff, Nathalie
AU - Corriol-Rohou, Solange
AU - Jarrod, Ian
AU - Erzen, Damijen
AU - Brindicci, Caterina
AU - Higenbottam, Tim
AU - Scuri, Mario
AU - McBride, Paul
AU - Kamel, Nadia
AU - Tabberer, Margaret
AU - Dobbels, Fabienne
AU - de Boer, Pim
AU - Kulich, Karoly
AU - Glendenning, Alastair
AU - Rudell, Katja
N1 - Publisher Copyright:
© 2020 SEPAR
PY - 2021/3
Y1 - 2021/3
N2 - Introduction: Although mean physical activity in COPD patients declines by 400–500 steps/day annually, it is unknown whether the natural progression is the same for all patients. We aimed to identify distinct physical activity progression patterns using a hypothesis-free approach and to assess their determinants. Methods: We pooled data from two cohorts (usual care arm of Urban Training [NCT01897298] and PROactive initial validation [NCT01388218] studies) measuring physical activity at baseline and 12 months (Dynaport MoveMonitor). We identified clusters (patterns) of physical activity progression (based on levels and changes of steps/day) using k-means, and compared baseline sociodemographic, interpersonal, environmental, clinical and psychological characteristics across patterns. Results: In 291 COPD patients (mean ± SD 68 ± 8 years, 81% male, FEV1 59 ± 19%pred) we identified three distinct physical activity progression patterns: Inactive (n = 173 [59%], baseline: 4621 ± 1757 steps/day, 12-month change (Δ): −487 ± 1201 steps/day), Active Improvers (n = 49 [17%], baseline: 7727 ± 3275 steps/day, Δ: + 3378 ± 2203 steps/day) and Active Decliners (n = 69 [24%], baseline: 11 267 ± 3009 steps/day, Δ: −2217 ± 2085 steps/day). After adjustment in a mixed multinomial logistic regression model using Active Decliners as reference pattern, a lower 6-min walking distance (RRR [95% CI] 0.94 [0.90–0.98] per 10 m, P =.001) and a higher mMRC dyspnea score (1.71 [1.12–2.60] per 1 point, P =.012) were independently related with being Inactive. No baseline variable was independently associated with being an Active Improver. Conclusions: The natural progression in physical activity over time in COPD patients is heterogeneous. While Inactive patients relate to worse scores for clinical COPD characteristics, Active Improvers and Decliners cannot be predicted at baseline.
AB - Introduction: Although mean physical activity in COPD patients declines by 400–500 steps/day annually, it is unknown whether the natural progression is the same for all patients. We aimed to identify distinct physical activity progression patterns using a hypothesis-free approach and to assess their determinants. Methods: We pooled data from two cohorts (usual care arm of Urban Training [NCT01897298] and PROactive initial validation [NCT01388218] studies) measuring physical activity at baseline and 12 months (Dynaport MoveMonitor). We identified clusters (patterns) of physical activity progression (based on levels and changes of steps/day) using k-means, and compared baseline sociodemographic, interpersonal, environmental, clinical and psychological characteristics across patterns. Results: In 291 COPD patients (mean ± SD 68 ± 8 years, 81% male, FEV1 59 ± 19%pred) we identified three distinct physical activity progression patterns: Inactive (n = 173 [59%], baseline: 4621 ± 1757 steps/day, 12-month change (Δ): −487 ± 1201 steps/day), Active Improvers (n = 49 [17%], baseline: 7727 ± 3275 steps/day, Δ: + 3378 ± 2203 steps/day) and Active Decliners (n = 69 [24%], baseline: 11 267 ± 3009 steps/day, Δ: −2217 ± 2085 steps/day). After adjustment in a mixed multinomial logistic regression model using Active Decliners as reference pattern, a lower 6-min walking distance (RRR [95% CI] 0.94 [0.90–0.98] per 10 m, P =.001) and a higher mMRC dyspnea score (1.71 [1.12–2.60] per 1 point, P =.012) were independently related with being Inactive. No baseline variable was independently associated with being an Active Improver. Conclusions: The natural progression in physical activity over time in COPD patients is heterogeneous. While Inactive patients relate to worse scores for clinical COPD characteristics, Active Improvers and Decliners cannot be predicted at baseline.
KW - COPD
KW - Cluster analysis
KW - Determinants
KW - Patterns of progression
KW - Physical activity
UR - http://www.scopus.com/inward/record.url?scp=85092247401&partnerID=8YFLogxK
U2 - 10.1016/j.arbres.2020.08.001
DO - 10.1016/j.arbres.2020.08.001
M3 - Artículo
C2 - 33041107
AN - SCOPUS:85092247401
SN - 0300-2896
VL - 57
SP - 214
EP - 223
JO - Archivos de Bronconeumologia
JF - Archivos de Bronconeumologia
IS - 3
ER -