Literature DB >> 33468128

Development and validation of a nomogram to predict pulmonary function and the presence of chronic obstructive pulmonary disease in a Korean population.

Sang Chul Lee1, Chansik An2, Jongha Yoo3, Sungho Park4, Donggyo Shin5, Chang Hoon Han1.   

Abstract

BACKGROUND: Early suspicion followed by assessing lung function with spirometry could decrease the underdiagnosis of chronic obstructive pulmonary disease (COPD) in primary care. We aimed to develop a nomogram to predict the FEV1/FVC ratio and the presence of COPD.
METHODS: We retrospectively reviewed the data of 4241 adult patients who underwent spirometry between 2013 and 2019. By linear regression analysis, variables associated with FEV1/FVC were identified in the training cohort (n = 2969). Using the variables as predictors, a nomogram was created to predict the FEV1/FVC ratio and validated in the test cohort (n = 1272).
RESULTS: Older age (β coefficient [95% CI], - 0.153 [- 0.183, - 0.122]), male sex (- 1.904 [- 2.749, - 1.056]), current or past smoking history (- 3.324 [- 4.200, - 2.453]), and the presence of dyspnea (- 2.453 [- 3.612, - 1.291]) or overweight (0.894 [0.191, 1.598]) were significantly associated with the FEV1/FVC ratio. In the final testing, the developed nomogram showed a mean absolute error of 8.2% between the predicted and actual FEV1/FVC ratios. The overall performance was best when FEV1/FVC < 70% was used as a diagnostic criterion for COPD; the sensitivity, specificity, and balanced accuracy were 82.3%, 68.6%, and 75.5%, respectively.
CONCLUSION: The developed nomogram could be used to identify potential patients at risk of COPD who may need further evaluation, especially in the primary care setting where spirometry is not available.

Entities:  

Keywords:  Chronic obstructive pulmonary disease; Machine learning; Primary care; Spirometry

Year:  2021        PMID: 33468128      PMCID: PMC7816387          DOI: 10.1186/s12890-021-01391-z

Source DB:  PubMed          Journal:  BMC Pulm Med        ISSN: 1471-2466            Impact factor:   3.317


  29 in total

1.  Ethnic differences in pulmonary function in healthy nonsmoking Asian-Americans and European-Americans.

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Review 2.  Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Lung Disease: the GOLD science committee report 2019.

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Journal:  Eur Respir J       Date:  2019-05-18       Impact factor: 16.671

3.  Prevalence and underdiagnosis of chronic obstructive pulmonary disease among patients at risk in primary care.

Authors:  Kylie Hill; Roger S Goldstein; Gordon H Guyatt; Maria Blouin; Wan C Tan; Lori L Davis; Diane M Heels-Ansdell; Marko Erak; Pauline J Bragaglia; Itamar E Tamari; Richard Hodder; Matthew B Stanbrook
Journal:  CMAJ       Date:  2010-04-06       Impact factor: 8.262

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Authors:  Douglas W Mapel; Floyd J Frost; Judith S Hurley; Hans Petersen; Melissa Roberts; Jeno P Marton; Hemal Shah
Journal:  J Manag Care Pharm       Date:  2006 Jul-Aug

Review 5.  COPD Guidelines: A Review of the 2018 GOLD Report.

Authors:  Shireen Mirza; Ryan D Clay; Matthew A Koslow; Paul D Scanlon
Journal:  Mayo Clin Proc       Date:  2018-10       Impact factor: 7.616

Review 6.  Body weight and mortality in COPD: focus on the obesity paradox.

Authors:  Francesco Spelta; A M Fratta Pasini; L Cazzoletti; M Ferrari
Journal:  Eat Weight Disord       Date:  2017-11-06       Impact factor: 4.652

7.  A mixed methods study to compare models of spirometry delivery in primary care for patients at risk of COPD.

Authors:  J A Walters; E C Hansen; D P Johns; E L Blizzard; E H Walters; R Wood-Baker
Journal:  Thorax       Date:  2007-11-16       Impact factor: 9.139

8.  Development and validation of a model to predict the 10-year risk of general practitioner-recorded COPD.

Authors:  Daniel Kotz; Colin R Simpson; Wolfgang Viechtbauer; Onno C P van Schayck; Aziz Sheikh
Journal:  NPJ Prim Care Respir Med       Date:  2014-05-20       Impact factor: 2.871

9.  The unmet global burden of COPD.

Authors:  S A Quaderi; J R Hurst
Journal:  Glob Health Epidemiol Genom       Date:  2018-04-06

10.  A machine learning approach to triaging patients with chronic obstructive pulmonary disease.

Authors:  Sumanth Swaminathan; Klajdi Qirko; Ted Smith; Ethan Corcoran; Nicholas G Wysham; Gaurav Bazaz; George Kappel; Anthony N Gerber
Journal:  PLoS One       Date:  2017-11-22       Impact factor: 3.240

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