Rate of annual decline in FEV1 in community-dwelling older adults diagnosed with mild to moderate COPD


Study population

As shown in Figure 1, the data was taken from the ongoing population-based study Good Aging in Skåne (GÅS)14. Briefly, subjects between the ages of 60 and 93 living in Skåne, Sweden, are randomly invited using the population register. Participants are offered a thorough physical, medical and psychological examination and are asked for follow-up examinations at regular intervals until their death. To encourage the participation of frail adults, the study team conducts home visits according to the same study protocol. Three waves were fully recruited with an initial participation rate of approximately 60%. The participants recruited during the first wave in 2001-2004 were aged 60, 66, 72, 78, 81, 84, 87, 90 or 93 years old. The participants recruited during the second wave in 2006-2013 were aged 60, 66 or 81 years old. Participants recruited in the third wave in 2012-2016 were aged 60 or 81. A fourth wave has been recruiting since 2019, including participants aged 60 or 81. The GÅS study is conducted in accordance with the Declaration of Helsinki and Good Clinical Practice Guidelines and is approved by the Lund University Ethics Review Board (LU 744–00). All participants provide written informed consent. In this study, we aim to investigate early progression, and therefore to minimize bias, participants with a diagnosis of COPD at baseline were excluded from the analysis.

Fig. 1: Study population.

Participants diagnosed with COPD, with missing spirometry, or unable to perform three successful maneuvers at baseline were excluded from this study. During follow-up, 143 participants were diagnosed with COPD in clinical practice.

Spirometry assessments

Spirometry assessments were performed using a Vitalograph 2120 spirometer (Vitalograph Ltd, Buckingham, UK) following the guidelines of the American Thoracic Society15. Bronchodilators were not administered at the first wave baseline visit. Subjects received β2 agonist terbutaline 1.0 mg 10 min prior to spirometry at all other visits.

Identification of comorbidities and definition of COPD

Comorbidities were identified during medical examination and by retrieving medical records and diagnostic codes from Skåne’s healthcare registry16 (see Supplementary Table 1). Information on medications prescribed was obtained from medical records and self-reported. The diagnosis of COPD was extracted from medical records. Clinically, the diagnosis of COPD in the Skåne region is based on three criteria: obstruction verified by spirometry (FEV1/FVC

COPD has been classified according to the GOLD classification (Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Lung Disease)17 using spirometries collected during study visits. In some cases, participants diagnosed with COPD had normal spirometry at the study visit. Therefore, an additional category level (category 0) was included to accommodate diagnosed subjects whose FEV1/FVC ratio was ≥ 0.75. The spirometry performed during the study visit was used for the COPD GOLD classification. Reference equations for the lower limit of normal are only available for subjects less than 95 years of age and for this calculation age has been truncated to 95 years.

statistical analyzes

The purpose of the statistical analysis was to estimate the mean annual rate of decline in FEV1 in patients with COPD at onset of COPD and compare it to the rate of decline in participants without COPD. The annual change in FEV1 was defined as the difference in FEV1 between two consecutive study visits divided by the time elapsed between visits. This model assumes that the annual rate of decline is constant over time. A mixed model of repeated measures with random interception (participants) was set up. The variables FEV1, age, sex, smoking status, education, body mass index, heart disease, cerebrovascular disease, asthma and diabetes (at baseline) were included to reduce confusion.

Estimating the difference in annual rate of decline between participants with and without a diagnosis of COPD is difficult, as the two groups are expected to differ only in their COPD status. Patients in clinical practice do not perform spirometry examinations on a regular basis. Therefore, a participant with low FEV1 might be more likely to get a spirometry test and thus a diagnosis of COPD compared to a participant with higher FEV1 values, regardless of their true COPD status. The previous value of FEV1 may affect the likelihood of obtaining a diagnosis of COPD and therefore time-varying confusion may be present. To minimize bias, sensitivity analyzes using a marginal structural mixed model were performed (see Supplementary Table 5). The risk of misclassification in the diagnosis of COPD is recognized. We therefore presented an additional note on sensitivity analyzes where COPD status was assigned using spirometry results obtained during study visits. Stata IC 14.2 statistical software (StataCorp LLC, Texas, USA) was used.

Summary of reports

Further information on the research design can be found in the summary of nature research reports linked to this article.

Previous Bitcoin ATM Company to List on Nasdaq Cryptocurrency
Next County Redistricting Commission Recharges Before Map Deadline - Cortland Voice