Allergy Asthma Immunol Res.  2020 May;12(3):443-453. 10.4168/aair.2020.12.3.443.

Risk Factors for Acute Exacerbations in Elderly Asthma: What Makes Asthma in Older Adults Distinctive?

• Sohn KH
• Song WJ
• Park JS
• Park HW
• Kim TB
• Park CS
• Cho SH
• on behalf of the Elderly Asthma Cohort in Korea Group

• KMID: 2471228
• DOI: http://doi.org/10.4168/aair.2020.12.3.443

Abstract

PURPOSE
Asthma in the elderly (EA; ≥ 65 years of age) is increasing, adding a heavy socioeconomic burden to the healthcare system. However, little is known about risk factors associated with acute exacerbations in EA patients. The objective of this study was to investigate risk factors for acute exacerbation in EA compared to non-elderly asthma (NEA).
METHODS
We combined data from 3 adult asthma cohorts under a unified protocol and database. Asthmatic patients with regular follow-up during a 1-year period were selected from the cohorts to identify the risk factors predicting acute exacerbations in EA compared to NEA.
RESULTS
We selected a total of 1,086 patients from the merged cohort. During the observation period, 503 and 583 patients were assigned to the EA and NEA groups, respectively. The exacerbation rate was 31.0% in the EA and 33.2% in the NEA group. Multivariate logistic regression analysis revealed fixed airway obstruction, chronic rhinosinusitis (CRS), and male sex as independent risk factors for exacerbation in the EA group. In the NEA group, exacerbation increased along with an increase in eosinophil count. Bayesian analysis of the interactions among clinical factors revealed that forced expiratory volume in 1 second/forced vital capacity was directly related to exacerbation in the EA group, and eosinophil count was related to exacerbation in the NEA group.
CONCLUSIONS
We suggest that fixed airway obstruction and CRS as the important clinical factors predicting acute exacerbations in EA, whereas in NEA, eosinophil count was the strong predictor of exacerbation.

Keyword

Asthma; elderly; exacerbation; risk factors; airway obstruction

MeSH Terms

Adult*
Aged*
Airway Obstruction
Asthma*
Bayes Theorem
Cohort Studies
Delivery of Health Care
Eosinophils
Follow-Up Studies
Forced Expiratory Volume
Humans
Logistic Models
Male
Risk Factors*
Vital Capacity

Figure

• 

  Fig. 1 Study flow.COREA, Cohort for Reality and Evolution of Adult Asthma in Korea; EA, elderly asthma; NEA, non-elderly asthma.

• 

  Fig. 2 Comparison of the Bayesian network analysis between (A) EA and (B) NEA.EA, elderly asthma; NEA, non-elderly asthma; EXA, exacerbation; ATO, atopy; BMI, body mass index; SMOKE, 10 pack year smoking; Ratio, forced expiratory volume in 1 second per forced vital capacity; EOS, eosinophil; FEV1, forced expiratory volume in 1 second; FEV1P, percentage of forced expiratory volume in 1 second; FVC, forced vital capacity; FVCP, percentage of forced vital capacity.

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