In these instances, patients are instructed to refer to a document when they are feeling concerned about their breathing. Perhaps the most widely used system is a physician provided paper checklist or “action plan”. ĭespite the recognized impact of exacerbations on morbidity, mortality, and health status, there is no standardized clinical approach to improve self-identification of COPD exacerbations by patients at home. A World Health Organization report anticipates that by 2030, COPD will become the third leading cause of mortality and the seventh leading cause of morbidity worldwide. Moreover, exacerbations are associated with long term declines in lung function and health status. Flare-ups (or exacerbations) are a frequent trigger of physician and hospital visits that are both costly and distressing to patients. COPD includes a spectrum of pulmonary phenotypes with emphysema and chronic bronchitis being the two most prominent members. This does not alter our adherence to PLOS ONE policies on sharing data and materials.Ĭhronic Obstructive Pulmonary Disease (COPD) is a serious long-term lung condition that progressively restricts airflow from the lungs and imposes a significant burden on patients’ daily lives. Gerber is a consultant for Revon Systems Inc and holds stock options. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: The data is available as a Supporting Information file.įunding: The authors received no specific funding for this work.Ĭompeting interests: We would like to disclose that Anthony N. Received: AugAccepted: NovemPublished: November 22, 2017Ĭopyright: © 2017 Swaminathan et al. (2017) A machine learning approach to triaging patients with chronic obstructive pulmonary disease. Citation: Swaminathan S, Qirko K, Smith T, Corcoran E, Wysham NG, Bazaz G, et al.
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