Person: Moy, Marilyn
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Moy
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Marilyn
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Moy, Marilyn
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Publication Study design and rationale for investigating phosphodiesterase type 5 inhibition for the treatment of pulmonary hypertension due to chronic obstructive lung disease: the TADA-PHiLD (TADAlafil for Pulmonary Hypertension associated with chronic obstructive Lung Disease) trial(University of Chicago Press, 2013) Maron, Bradley; Goldstein, Ronald H.; Rounds, Sharon I.; Shapiro, Shelley; Jankowich, Matthew; Garshick, Eric; Moy, Marilyn; Gagnon, David; Choudhary, GauravAbstract In patients with chronic obstructive pulmonary disease (COPD), moderate or severe pulmonary hypertension (COPD-PH) is associated with increased rates of morbidity and mortality. Despite this, approaches to treatment and the efficacy of phosphodiesterase type 5 inhibition (PDE-5i) in COPD-PH are unresolved. We present the clinical rationale and study design to assess the effect of oral tadalafil on exercise capacity, cardiopulmonary hemodynamics, and clinical outcome measures in COPD-PH patients. Male and female patients 40–85 years old with GOLD stage 2 COPD or higher and pulmonary hypertension diagnosed on the basis of invasive cardiac hemodynamic assessment (mean pulmonary artery pressure [mPAP] >30 mmHg, pulmonary vascular resistance [PVR] >2.5 Wood units, and pulmonary capillary wedge pressure ≤18 mmHg at rest) will be randomized at a 1∶1 ratio to receive placebo or oral PDE-5i with tadalafil (40 mg daily for 12 months). The primary end point is change from baseline in 6-minute walk distance at 12 months. The secondary end points are change from baseline in PVR and mPAP at 6 months and change from baseline in peak volume of oxygen consumption () during exercise at 12 months. Changes in systemic blood pressure and/or oxyhemoglobin saturation (Sao2) at rest and during exercise will function as safety outcome measures. TADA-PHiLD (TADAlafil for Pulmonary Hypertension assocIated with chronic obstructive Lung Disease) is the first sufficiently powered randomized clinical trial testing the effect of PDE-5i on key clinical and drug safety outcome measures in patients with at least moderate PH due to COPD.Publication Physical activity assessed in routine care predicts mortality after a COPD hospitalisation(European Respiratory Society, 2016) Moy, Marilyn; Gould, Michael K.; Liu, In-Lu Amy; Lee, Janet S.; Nguyen, Huong Q.The independent relationship between physical inactivity and risk of death after an index chronic obstructive pulmonary disease (COPD) hospitalisation is unknown. We conducted a retrospective cohort study in a large integrated healthcare system. Patients were included if they were hospitalised for COPD between January 1, 2011 and December 31, 2011. All-cause mortality in the 12 months after discharge was the primary outcome. Physical activity, expressed as self-reported minutes of moderate to vigorous physical activity (MVPA), was routinely assessed at outpatient visits prior to hospitalisation. 1727 (73%) patients were inactive (0 min of MVPA per week), 412 (17%) were insufficiently active (1–149 min of MVPA per week) and 231 (10%) were active (≥150 min of MVPA per week). Adjusted Cox regression models assessed risk of death across the MVPA categories. Among 2370 patients (55% females and mean age 73±11 years), there were 464 (20%) deaths. Patients who were insufficiently active or active had a 28% (adjusted HR 0.72 (95% CI 0.54–0.97), p=0.03) and 47% (adjusted HR 0.53 (95% CI 0.34–0.84), p<0.01) lower risk of death, respectively, in the 12 months following an index COPD hospitalisation compared to inactive patients. Any level of MVPA is associated with lower risk of all-cause mortality after a COPD hospitalisation. Routine assessment of physical activity in clinical care would identify persons at high risk for dying after COPD hospitalisation.Publication Daily Step Count Predicts Acute Exacerbations in a US Cohort with COPD(Public Library of Science, 2013) Moy, Marilyn; Teylan, Merilee Ann; Weston, Nicole A.; Gagnon, David R.; Garshick, EricBackground: COPD is characterized by variability in exercise capacity and physical activity (PA), and acute exacerbations (AEs). Little is known about the relationship between daily step count, a direct measure of PA, and the risk of AEs, including hospitalizations. Methods: In an observational cohort study of 169 persons with COPD, we directly assessed PA with the StepWatch Activity Monitor, an ankle-worn accelerometer that measures daily step count. We also assessed exercise capacity with the 6-minute walk test (6MWT) and patient-reported PA with the St. George's Respiratory Questionnaire Activity Score (SGRQ-AS). AEs and COPD-related hospitalizations were assessed and validated prospectively over a median of 16 months. Results: Mean daily step count was 5804±3141 steps. Over 209 person-years of observation, there were 263 AEs (incidence rate 1.3±1.6 per person-year) and 116 COPD-related hospitalizations (incidence rate 0.56±1.09 per person-year). Adjusting for FEV1 % predicted and prednisone use for AE in previous year, for each 1000 fewer steps per day walked at baseline, there was an increased rate of AEs (rate ratio 1.07; 95%CI = 1.003–1.15) and COPD-related hospitalizations (rate ratio 1.24; 95%CI = 1.08–1.42). There was a significant linear trend of decreasing daily step count by quartiles and increasing rate ratios for AEs (P = 0.008) and COPD-related hospitalizations (P = 0.003). Each 30-meter decrease in 6MWT distance was associated with an increased rate ratio of 1.07 (95%CI = 1.01–1.14) for AEs and 1.18 (95%CI = 1.07–1.30) for COPD-related hospitalizations. Worsening of SGRQ-AS by 4 points was associated with an increased rate ratio of 1.05 (95%CI = 1.01–1.09) for AEs and 1.10 (95%CI = 1.02–1.17) for COPD-related hospitalizations. Conclusions: Lower daily step count, lower 6MWT distance, and worse SGRQ-AS predict future AEs and COPD–related hospitalizations, independent of pulmonary function and previous AE history. These results support the importance of assessing PA in patients with COPD, and provide the rationale to promote PA as part of exacerbation-prevention strategies.Publication Using Hierarchical Clustering Methods to Classify Motor Activities of COPD Patients from Wearable Sensor Data(BioMed Central, 2005) Sherrill, Delsey M.; Moy, Marilyn; Reilly, John J.; Bonato, PaoloBackground: Advances in miniature sensor technology have led to the development of wearable systems that allow one to monitor motor activities in the field. A variety of classifiers have been proposed in the past, but little has been done toward developing systematic approaches to assess the feasibility of discriminating the motor tasks of interest and to guide the choice of the classifier architecture. Methods: A technique is introduced to address this problem according to a hierarchical framework and its use is demonstrated for the application of detecting motor activities in patients with chronic obstructive pulmonary disease (COPD) undergoing pulmonary rehabilitation. Accelerometers were used to collect data for 10 different classes of activity. Features were extracted to capture essential properties of the data set and reduce the dimensionality of the problem at hand. Cluster measures were utilized to find natural groupings in the data set and then construct a hierarchy of the relationships between clusters to guide the process of merging clusters that are too similar to distinguish reliably. It provides a means to assess whether the benefits of merging for performance of a classifier outweigh the loss of resolution incurred through merging. Results: Analysis of the COPD data set demonstrated that motor tasks related to ambulation can be reliably discriminated from tasks performed in a seated position with the legs in motion or stationary using two features derived from one accelerometer. Classifying motor tasks within the category of activities related to ambulation requires more advanced techniques. While in certain cases all the tasks could be accurately classified, in others merging clusters associated with different motor tasks was necessary. When merging clusters, it was found that the proposed method could lead to more than 12% improvement in classifier accuracy while retaining resolution of 4 tasks. Conclusion: Hierarchical clustering methods are relevant to developing classifiers of motor activities from data recorded using wearable systems. They allow users to assess feasibility of a classification problem and choose architectures that maximize accuracy. By relying on this approach, the clinical importance of discriminating motor tasks can be easily taken into consideration while designing the classifier.