Annals of the American Thoracic Society
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Review Multicenter Study
Diagnoses of early and late readmissions after hospitalization for pneumonia. A systematic review.
Pneumonia is a frequent cause of hospitalization, yet drivers of post-pneumonia morbidity remain poorly characterized. Causes of hospital readmissions may elucidate important sources of morbidity and are of particular interest given the U.S. Hospital Readmission Reductions Program. ⋯ Pneumonia, heart failure/cardiovascular disease, and chronic obstructive pulmonary disease/pulmonary disease are the most common readmission diagnoses after pneumonia hospitalization. Although pneumonia was the most common readmission diagnosis, it accounted for only a minority of all readmissions. Late readmission diagnoses are less thoroughly described, and further research is needed to understand how hospitalization for pneumonia fits within the broader context of patients' health trajectory.
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Multicenter Study Comparative Study
Environmental risks for nontuberculous mycobacteria. Individual exposures and climatic factors in the cystic fibrosis population.
Persons with cystic fibrosis are at high risk of pulmonary nontuberculous mycobacterial infection, with a national prevalence estimated at 13%. The risk of nontuberculous mycobacteria associated with specific environmental exposures, and the correlation with climatic conditions in this population has not been described. ⋯ Atmospheric conditions explain more of the variation in disease prevalence than individual behaviors. The risk of specific exposures may vary by geographic region due to differences in conditions favoring mycobacterial growth and survival. However, because exposure to these organisms is ubiquitous and behaviors are similar among persons with and without pulmonary nontuberculous mycobacteria, genetic susceptibility beyond cystic fibrosis is likely to be important for disease development. Common individual risk factors in high-risk populations remain to be identified.
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Pulmonary arterial hypertension (PAH) includes a heterogeneous group of diseases characterized by pulmonary vasoconstriction and remodeling of the lung circulation. Although PAH is a disease of the lungs, patients with PAH frequently die of right heart failure. Indeed, survival of patients with PAH depends on the adaptive response of the right ventricle (RV) to the changes in the lung circulation. ⋯ More recently, the right heart has been identified as a direct treatment target in PAH. The effects of well established therapies for left heart failure, such as β-adrenergic receptor blockers, inhibitors of the renin-angiotensin system, exercise training, and assist devices, are currently being investigated in PAH. Future treatment of patients with PAH will likely consist of a multifaceted approaches aiming to reduce the pressure in the lung circulation and improving right heart adaptation simultaneously.
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Randomized Controlled Trial Comparative Study
Cluster analysis and characterization of response to mepolizumab. A step closer to personalized medicine for patients with severe asthma.
Detailed characterization of asthma phenotypes is essential for identification of responder populations to allow directed personalized medical intervention. ⋯ Using supervised cluster analysis helped identify specific patient characteristics related to disease and therapeutic response. Patients with eosinophilic inflammation received significant therapeutic benefit with mepolizumab, and responses differed within clusters. Clinical trial registered with www.clinicaltrials.gov (NCT01000506).
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The Big Data movement in computer science has brought dramatic changes in what counts as data, how those data are analyzed, and what can be done with those data. Although increasingly pervasive in the business world, it has only recently begun to influence clinical research and practice. As Big Data draws from different intellectual traditions than clinical epidemiology, the ideas may be less familiar to practicing clinicians. ⋯ Second, Big Data asks different kinds of questions of data and emphasizes the usefulness of analyses that are explicitly associational but not causal. Third, Big Data brings new analytic approaches to bear on these questions. And fourth, Big Data embodies a new set of aspirations for a breaking down of distinctions between research data and operational data and their merging into a continuously learning health system.