Forecasting COPD hospitalization in the clinic: optimizing the chronic respiratory questionnaire

Beatriz Abascal-Bolado,1 Paul J Novotny,2 Jeff A Sloan,2 Craig Karpman,3 Megan M Dulohery,3 Roberto P Benzo31Pulmonary Division, Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; 2Department of Cancer Center Statistics, Health Science Research, 3Mindful Breathing...

Full description

Bibliographic Details
Main Authors: Abascal-Bolado B, Novotny PJ, Sloan JA, Karpman C, Dulohery MM, Benzo RP
Format: Article
Language:English
Published: Dove Medical Press 2015-10-01
Series:International Journal of COPD
Online Access:https://www.dovepress.com/forecasting-copd-hospitalization-in-the-clinic-optimizing-the-chronic--peer-reviewed-article-COPD
id doaj-7d87a4db64384dfa9bc613a3a19ccf15
record_format Article
spelling doaj-7d87a4db64384dfa9bc613a3a19ccf152020-11-24T23:55:38ZengDove Medical PressInternational Journal of COPD1178-20052015-10-012015Issue 12295230124275Forecasting COPD hospitalization in the clinic: optimizing the chronic respiratory questionnaireAbascal-Bolado BNovotny PJSloan JAKarpman CDulohery MMBenzo RPBeatriz Abascal-Bolado,1 Paul J Novotny,2 Jeff A Sloan,2 Craig Karpman,3 Megan M Dulohery,3 Roberto P Benzo31Pulmonary Division, Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; 2Department of Cancer Center Statistics, Health Science Research, 3Mindful Breathing Laboratory, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USAPurpose: Forecasting hospitalization in patients with COPD has gained significant interest in the field of COPD care. There is a need to find simple tools that can help clinicians to stratify the risk of hospitalization in these patients at the time of care. The perception of quality of life has been reported to be independently associated with hospitalizations, but questionnaires are impractical for daily clinical use. Individual questions from valid questionnaires can have robust predictive abilities, as has been suggested in previous reports, as a way to use patient-reported outcomes to forecast important events like hospitalizations in COPD. Our primary aim was to assess the predictive value of individual questions from the Chronic Respiratory Questionnaire Self-Assessment Survey (CRQ-SAS) on the risk of hospitalization and to develop a clinically relevant and simple algorithm that clinicians can use in routine practice to identify patients with an increased risk of hospitalization.Patients and methods: A total of 493 patients with COPD prospectively recruited from an outpatient pulmonary clinic completed the CRQ-SAS, demographic information, pulmonary function testing, and clinical outcomes. The cohort had a mean age of 70 years, was 54% male, with forced expiratory volume in 1 second percentage predicted 42.8±16.7, and modified Medical Research Council dyspnea scale score of 2±1.13.Results: Our analysis validated the original CRQ-SAS domains. Importantly, recursive partitioning analysis identified three CRQ-SAS items regarding fear or panic of breathlessness, dyspnea with basic activities of daily living, and depressive symptoms that were highly predictive of hospitalization. We propose a robust (area under the curve =0.70) but short and easy algorithm for daily clinical care to forecast hospitalizations in patients with COPD.Conclusion: We identified three themes – fear of breathlessness, dyspnea with basic activities of daily living, and depressive symptoms – as important patient-reported outcomes to predict hospitalizations, and propose a short and easy algorithm to forecast hospitalizations in patients with COPD.Keywords: quality of life, COPD, exacerbationhttps://www.dovepress.com/forecasting-copd-hospitalization-in-the-clinic-optimizing-the-chronic--peer-reviewed-article-COPD
collection DOAJ
language English
format Article
sources DOAJ
author Abascal-Bolado B
Novotny PJ
Sloan JA
Karpman C
Dulohery MM
Benzo RP
spellingShingle Abascal-Bolado B
Novotny PJ
Sloan JA
Karpman C
Dulohery MM
Benzo RP
Forecasting COPD hospitalization in the clinic: optimizing the chronic respiratory questionnaire
International Journal of COPD
author_facet Abascal-Bolado B
Novotny PJ
Sloan JA
Karpman C
Dulohery MM
Benzo RP
author_sort Abascal-Bolado B
title Forecasting COPD hospitalization in the clinic: optimizing the chronic respiratory questionnaire
title_short Forecasting COPD hospitalization in the clinic: optimizing the chronic respiratory questionnaire
title_full Forecasting COPD hospitalization in the clinic: optimizing the chronic respiratory questionnaire
title_fullStr Forecasting COPD hospitalization in the clinic: optimizing the chronic respiratory questionnaire
title_full_unstemmed Forecasting COPD hospitalization in the clinic: optimizing the chronic respiratory questionnaire
title_sort forecasting copd hospitalization in the clinic: optimizing the chronic respiratory questionnaire
publisher Dove Medical Press
series International Journal of COPD
issn 1178-2005
publishDate 2015-10-01
description Beatriz Abascal-Bolado,1 Paul J Novotny,2 Jeff A Sloan,2 Craig Karpman,3 Megan M Dulohery,3 Roberto P Benzo31Pulmonary Division, Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; 2Department of Cancer Center Statistics, Health Science Research, 3Mindful Breathing Laboratory, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USAPurpose: Forecasting hospitalization in patients with COPD has gained significant interest in the field of COPD care. There is a need to find simple tools that can help clinicians to stratify the risk of hospitalization in these patients at the time of care. The perception of quality of life has been reported to be independently associated with hospitalizations, but questionnaires are impractical for daily clinical use. Individual questions from valid questionnaires can have robust predictive abilities, as has been suggested in previous reports, as a way to use patient-reported outcomes to forecast important events like hospitalizations in COPD. Our primary aim was to assess the predictive value of individual questions from the Chronic Respiratory Questionnaire Self-Assessment Survey (CRQ-SAS) on the risk of hospitalization and to develop a clinically relevant and simple algorithm that clinicians can use in routine practice to identify patients with an increased risk of hospitalization.Patients and methods: A total of 493 patients with COPD prospectively recruited from an outpatient pulmonary clinic completed the CRQ-SAS, demographic information, pulmonary function testing, and clinical outcomes. The cohort had a mean age of 70 years, was 54% male, with forced expiratory volume in 1 second percentage predicted 42.8±16.7, and modified Medical Research Council dyspnea scale score of 2±1.13.Results: Our analysis validated the original CRQ-SAS domains. Importantly, recursive partitioning analysis identified three CRQ-SAS items regarding fear or panic of breathlessness, dyspnea with basic activities of daily living, and depressive symptoms that were highly predictive of hospitalization. We propose a robust (area under the curve =0.70) but short and easy algorithm for daily clinical care to forecast hospitalizations in patients with COPD.Conclusion: We identified three themes – fear of breathlessness, dyspnea with basic activities of daily living, and depressive symptoms – as important patient-reported outcomes to predict hospitalizations, and propose a short and easy algorithm to forecast hospitalizations in patients with COPD.Keywords: quality of life, COPD, exacerbation
url https://www.dovepress.com/forecasting-copd-hospitalization-in-the-clinic-optimizing-the-chronic--peer-reviewed-article-COPD
work_keys_str_mv AT abascalboladob forecastingcopdhospitalizationintheclinicoptimizingthechronicrespiratoryquestionnaire
AT novotnypj forecastingcopdhospitalizationintheclinicoptimizingthechronicrespiratoryquestionnaire
AT sloanja forecastingcopdhospitalizationintheclinicoptimizingthechronicrespiratoryquestionnaire
AT karpmanc forecastingcopdhospitalizationintheclinicoptimizingthechronicrespiratoryquestionnaire
AT duloherymm forecastingcopdhospitalizationintheclinicoptimizingthechronicrespiratoryquestionnaire
AT benzorp forecastingcopdhospitalizationintheclinicoptimizingthechronicrespiratoryquestionnaire
_version_ 1725461375672647680