Supervised exercise training improves outcomes in patients with pulmonary arterial hypertension (PAH). The effect of an unsupervised activity intervention has not been tested.Can a text-based mobile health intervention increase step counts in patients with PAH?We performed a randomized, parallel arm, single-blind clinical trial. We randomized patients to usual care or a text message-based intervention for 12 weeks. The intervention arm received three automated text messages per day with real-time step count updates and encouraging messages rooted in behavioral change theory. Individual step targets increased by 20% every four weeks.The primary endpoint was mean Week 12 step counts. Secondary endpoints included the six minute walk test, quality of life, right ventricular function, and body composition.Among 42 randomized participants, the change in raw steps between baseline and Week 12 was higher in the intervention group (1409 steps (IQR -32, 2220) vs. -149 steps (IQR -1010, 735); p=0.02), which persisted after adjustment for age, sex, baseline step counts, and functional class (model estimated difference 1250 steps, P = 0.03). The intervention arm took a higher average number of steps on all days between days 9 to 84 (P <0.05 all days). There was no difference in Week 12 six minute walk distance. Analysis of secondary endpoints suggested improvements in the emPHasis-10 score (adjusted change -4.2, P =0.046), a reduction in visceral fat volume (adjusted change -170ml, p=0.023), and nearly significant improvement in tricuspid annular plane systolic excursion (Model estimated difference 1.2mm, P = 0.051).This study demonstrated the feasibility of an automated text message-based intervention to increase physical activity in patients with PAH. Additional studies are warranted to examine the effect of the intervention on clinical outcomes.
Anna R Hemnes, Luke Silverman-Loyd, Shi Huang, Grant MacKinnon, Jeffrey Annis, Carolyn S Whitmore, Ravinder Mallugari, Rashundra N Oggs, Rezzan Hekmat, Rongzi Shan, Pauline P Huynh, Chang Yu, Seth S Martin, Michael J Blaha, Evan L Brittain