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Publications [#315452] of James A. Blumenthal

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Journal Articles

  1. Blumenthal, JA; Smith, PJ; Durheim, M; Mabe, S; Emery, CF; Martinu, T; Diaz, PT; Babyak, M; Welty-Wolf, K; Palmer, S (2016). Biobehavioral Prognostic Factors in Chronic Obstructive Pulmonary Disease: Results From the INSPIRE-II Trial.. Psychosom Med, 78(2), 153-162. [doi]
    (last updated on 2019/07/18)

    Abstract:
    OBJECTIVE: To examine the prognostic value of select biobehavioral factors in patients with chronic obstructive pulmonary disease (COPD) in a secondary analysis of participants from the INSPIRE-II trial. METHODS: Three hundred twenty-six outpatients with COPD underwent assessments of pulmonary function, physical activity, body mass index, inflammation, pulmonary symptoms, depression, and pulmonary quality of life and were followed up for up to 5.4 years for subsequent clinical events. The prognostic value of each biobehavioral factor, considered individually and combined, also was examined in the context of existing Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2011 risk stratification. RESULTS: Sixty-nine individuals experienced a hospitalization or died over a mean follow-up period of 2.4 (interquartile range = 1.6) years. GOLD classification was associated with an increased risk of clinical events (hazard ratio [HR] = 2.72 [95% confidence interval = 1.63-4.54], per stage); 6-minute walk (HR = 0.50 [0.34-0.73] per 500 ft), total steps (HR = 0.82 [0.71-0.94] per 1000 steps), high-sensitivity C-reactive protein (HR = 1.44 [1.01-2.06] per 4.5 mg/l), depression (HR = 1.12 [1.01-1.25] per 4 points), and pulmonary quality of life (HR = 1.73 [1.14-2.63] per 25 points) were each predictive over and above the GOLD assessment. However, only GOLD group and 6-minute walk were predictive of all-cause mortality and COPD hospitalization when all biobehavioral variables were included together in a multivariable model. CONCLUSIONS: Biobehavioral factors provide added prognostic information over and above measures of COPD severity in predicting adverse events in patients with COPD.


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