↓ Skip to main content

How Well Does CAPTURE Translate? An Exploratory Analysis of a COPD Case-Finding Method for Spanish-Speaking Patients

Overview of attention for article published in CHEST, April 2017
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

news
5 news outlets
twitter
4 X users
facebook
1 Facebook page

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
47 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
How Well Does CAPTURE Translate? An Exploratory Analysis of a COPD Case-Finding Method for Spanish-Speaking Patients
Published in
CHEST, April 2017
DOI 10.1016/j.chest.2017.03.047
Pubmed ID
Authors

Wilson A. Quezada, Beth A. Whippo, Patricia A. Jellen, Nancy K. Leidy, David M. Mannino, Katherine J. Kim, MeiLan K. Han, Julia F. Houfek, Barry Make, Karen G. Malley, Catherine A. Meldrum, Stephen I. Rennard, Barbara P. Yawn, Fernando J. Martinez, Byron M. Thomashow, High-Risk-COPD Screening Study Group∗, R. Graham Barr, Russ P. Bowler, Rebecca Copeland, Tim Dorius, Karen Ishitani, Marge Kurland, James Melson, Randel Plant, Christina Schnell, Jason Shiffermiller, Sonja Stringer, Deb Sumnick, Kyle Textor, Jennifer Underwood, John Walsh

Abstract

This study tested the properties of a Spanish translation of CAPTURE™ (COPD Assessment in Primary Care To Identify Undiagnosed Respiratory Disease and Exacerbation Risk) with selective use of peak expiratory flow (PEF). Analyses of data from the Spanish-speaking cohort of the cross-sectional, case-control study used to develop CAPTURE. Translation procedures included forward and backward translation, reconciliation, and cognitive interviewing to assure linguistic and cultural equivalence. Spanish-speaking participants were recruited through one center and designated as Cases (clinically significant COPD: FEV1 < 60% predicted and/or at risk of COPD exacerbation) or Controls (No or mild COPD). Subjects completed a questionnaire booklet that included 44 candidate items, COPD Assessment Test (CAT), and modified Medical Research Council (mMRC) dyspnea question. PEF and spirometry were also performed. N=30 participants: 17 cases; 13 controls. Mean (SD) age: 62.6 (11.49) years; 33% male. CAPTURE-S scores were significantly correlated with PEF (r=-0.78), FEV1/FVC ratio (r=-0.74), FEV1r= (-0.69), FEV1% predicted (r=-0.69), CAT score (r=0.70), and mMRC (r=0.59) (p<0.0001), with significantly higher scores in cases than controls (t=6.16, p<0.0001). PEF significantly correlated with FEV1 (r=0.89), FEV1 % predicted (r=0.79), and FEV1/FVC (r=0.75) (p<0.0001), with significantly lower PEF in cases than controls (t=5.08, p<0.0001). CAPTURE-S score plus PEF differentiated cases and controls with sensitivity = 88.2% and specificity = 92.3%. CAPTURE-S with selective use of PEF appears to be useful for identifying Spanish-speaking patients in need of diagnostic evaluation for clinically significant COPD who may benefit from initiation of COPD treatment.

X Demographics

X Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 21%
Student > Bachelor 6 13%
Researcher 5 11%
Student > Postgraduate 4 9%
Student > Doctoral Student 3 6%
Other 7 15%
Unknown 12 26%
Readers by discipline Count As %
Medicine and Dentistry 17 36%
Nursing and Health Professions 5 11%
Psychology 3 6%
Social Sciences 2 4%
Chemical Engineering 1 2%
Other 6 13%
Unknown 13 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 37. 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 08 November 2017.
All research outputs
#1,100,984
of 25,382,440 outputs
Outputs from CHEST
#859
of 13,212 outputs
Outputs of similar age
#22,074
of 323,237 outputs
Outputs of similar age from CHEST
#12
of 107 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,212 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.1. This one has done particularly well, scoring higher than 93% 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 323,237 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 107 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.