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A decision tree to assess short-term mortality after an emergency department visit for an exacerbation of COPD: a cohort study.

Overview of attention for article published in Respiratory Research, January 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

Mentioned by

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4 tweeters
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

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16 Dimensions

Readers on

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62 Mendeley
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Title
A decision tree to assess short-term mortality after an emergency department visit for an exacerbation of COPD: a cohort study.
Published in
Respiratory Research, January 2015
DOI 10.1186/s12931-015-0313-4
Pubmed ID
Authors

Cristóbal Esteban, Inmaculada Arostegui, Susana Garcia-Gutierrez, Nerea Gonzalez, Iratxe Lafuente, Marisa Bare, Nerea Fernandez de Larrea, Francisco Rivas, José M Quintana, $author.firstName $author.lastName

Abstract

Creating an easy-to-use instrument to identify predictors of short-term (30/60-day) mortality after an exacerbation of chronic obstructive pulmonary disease (eCOPD) could help clinicians choose specific measures of medical care to decrease mortality in these patients. The objective of this study was to develop and validate a classification and regression tree (CART) to predict short term mortality among patients evaluated in an emergency department (ED) for an eCOPD. We conducted a prospective cohort study including participants from 16 hospitals in Spain. COPD patients with an exacerbation attending the emergency department (ED) of any of the hospitals between June 2008 and September 2010 were recruited. Patients were randomly divided into derivation (50 %) and validation samples (50 %). A CART based on a recursive partitioning algorithm was created in the derivation sample and applied to the validation sample. Two thousand four hundred eighty-seven patients, 1252 patients in the derivation sample and 1235 in the validation sample, were enrolled in the study. Based on the results of the univariate analysis, five variables (baseline dyspnea, cardiac disease, the presence of paradoxical breathing or use of accessory inspiratory muscles, age, and Glasgow Coma Scale score) were used to build the CART. Mortality rates 30 days after discharge ranged from 0 % to 55 % in the five CART classes. The lowest mortality rate was for the branch composed of low baseline dyspnea and lack of cardiac disease. The highest mortality rate was in the branch with the highest baseline dyspnea level, use of accessory inspiratory muscles or paradoxical breathing upon ED arrival, and Glasgow score <15. The area under the receiver-operating curve (AUC) in the derivation sample was 0.835 (95 % CI: 0.783, 0.888) and 0.794 (95 % CI: 0.723, 0.865) in the validation sample. CART was improved to predict 60-days mortality risk by adding the Charlson Comorbidity Index, reaching an AUC in the derivation sample of 0.817 (95 % CI: 0.776, 0.859) and 0.770 (95 % CI: 0.716, 0.823) in the validation sample. We identified several easy-to-determine variables that allow clinicians to classify eCOPD patients by short term mortality risk, which can provide useful information for establishing appropriate clinical care. NCT02434536 .

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Spain 1 2%
Canada 1 2%
Unknown 59 95%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 23%
Researcher 9 15%
Student > Ph. D. Student 7 11%
Other 5 8%
Professor > Associate Professor 5 8%
Other 13 21%
Unknown 9 15%
Readers by discipline Count As %
Medicine and Dentistry 24 39%
Nursing and Health Professions 9 15%
Mathematics 4 6%
Computer Science 3 5%
Biochemistry, Genetics and Molecular Biology 2 3%
Other 7 11%
Unknown 13 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 December 2015.
All research outputs
#8,139,764
of 15,689,103 outputs
Outputs from Respiratory Research
#799
of 1,977 outputs
Outputs of similar age
#132,771
of 368,997 outputs
Outputs of similar age from Respiratory Research
#62
of 146 outputs
Altmetric has tracked 15,689,103 research outputs across all sources so far. This one is in the 47th percentile – i.e., 47% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,977 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has gotten more attention than average, scoring higher than 57% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 368,997 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.
We're also able to compare this research output to 146 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.