Diffusing Capacity as a Predictor of Hospitalizations in a Clinical Cohort of Chronic Obstructive Pulmonary Disease Article Swipe
Aparna Balasubramanian
,
Andrew S. Gearhart
,
Nirupama Putcha
,
Ashraf Fawzy
,
Anil Singh
,
Robert A. Wise
,
Nadia N. Hansel
,
Meredith C. McCormack
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1513/annalsats.202301-014oc
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1513/annalsats.202301-014oc
Rationale: Chronic obstructive pulmonary disease (COPD) hospitalizations are a major burden on patients. Diffusing capacity of the lung for carbon monoxide (DlCO) is a potential predictor that has not been studied in large cohorts. Objectives: This study used electronic health record data to evaluate whether clinically obtained DlCO predicts COPD hospitalizations. Methods: We performed time-to-event analyses of individuals with COPD and DlCO measurements from the Johns Hopkins COPD Precision Medicine Center of Excellence. Cox proportional hazard methods were used to model time from DlCO measurement to first COPD hospitalization and composite first hospitalization or death, adjusting for age, sex, race, body mass index, smoking status, forced expiratory volume in 1 second (FEV1), history of prior COPD hospitalization, and comorbidities. To identify the utility of including DlCO in risk models, area under the receiver operating curve (AUC) values were calculated for models with and without DlCO. Results were externally validated in a separate analogous cohort. Results: Of 2,793 participants, 368 (13%) had a COPD hospitalization within 3 years. In adjusted analyses, for every 10% decrease in DlCO% predicted, risk of COPD hospitalization increased by 10% (hazard ratio, 1.1; 95% confidence interval, 1.1-1.2; P < 0.001). Similar associations were observed for COPD hospitalizations or death. The model including demographics, comorbidities, FEV1, DlCO, and prior COPD hospitalizations performed well, with an AUC of 0.85 and an AUC of 0.84 in an external validation cohort. Conclusions: Diffusing capacity is a strong predictor of COPD hospitalizations in a clinical cohort of individuals with COPD, independent of airflow obstruction and prior hospitalizations. These findings support incorporation of DlCO in risk assessment of patients with COPD.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1513/annalsats.202301-014oc
- OA Status
- green
- Cited By
- 7
- References
- 61
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4387865564
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4387865564Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1513/annalsats.202301-014ocDigital Object Identifier
- Title
-
Diffusing Capacity as a Predictor of Hospitalizations in a Clinical Cohort of Chronic Obstructive Pulmonary DiseaseWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-10-23Full publication date if available
- Authors
-
Aparna Balasubramanian, Andrew S. Gearhart, Nirupama Putcha, Ashraf Fawzy, Anil Singh, Robert A. Wise, Nadia N. Hansel, Meredith C. McCormackList of authors in order
- Landing page
-
https://doi.org/10.1513/annalsats.202301-014ocPublisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://pmc.ncbi.nlm.nih.gov/articles/PMC10848911/pdf/AnnalsATS.202301-014OC.pdfDirect OA link when available
- Concepts
-
DLCO, Medicine, COPD, Internal medicine, Hazard ratio, Cohort, Diffusing capacity, Proportional hazards model, Spirometry, Physical therapy, Cardiology, Confidence interval, Lung, Asthma, Lung functionTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
7Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 4, 2024: 3Per-year citation counts (last 5 years)
- References (count)
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61Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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