On 16 November 2023, Sanne van Dijk, Marjolein Brusse-Keizer, Tanja Effing, Paul van der Valk, Eline Ploumen, Job van der Palen, Carine Doggen, and Anke Lenferink published a paper in the International Journal of Chronic Obstructive Pulmonary Disease. This paper was titled "Exploring Patterns of COPD Exacerbations and Comorbid Flare-Ups".
You can read the full paper here.
The abstract is presented below:
Background
Comorbidities are known to complicate disease management in patients with Chronic Obstructive Pulmonary Disease (COPD). This is partly due to lack of insight into the interplay of acute exacerbations of COPD (AECOPD) and comorbid flare-ups. This study aimed to explore patterns of AECOPDs and comorbid flare-ups.
Methods
Data of increased symptoms were extracted from a 12-month daily symptom follow-up database including patients with COPD and comorbidities (chronic heart failure (CHF), anxiety, depression) and transformed to visualisations of AECOPDs and comorbid flare-up patterns over time.
Patterns were subsequently categorised using an inductive approach, based on both predominance (i.e., which occurs most often) of AECOPDs or comorbid flare-ups, and their simultaneous (i.e., simultaneous start in ≥ 50%) occurrence.
Results
We included 48 COPD patients (68 ± 9 years; comorbid CHF: 52%, anxiety: 40%, depression: 38%). In 25 patients with AECOPDs and CHF flare-ups, the following patterns were identified: AECOPDs predominant (n = 14), CHF flare-ups predominant (n = 5), AECOPDs nor CHF flare-ups predominant (n = 6). Of the 24 patients with AECOPDs and anxiety and/or depression flare-ups, anxiety and depression flare-ups occurred simultaneously in 15 patients. In 9 of these 24 patients, anxiety or depression flare-ups were observed independently from each other. In 31 of the included 48 patients, AECOPDs and comorbid flare-ups occurred mostly simultaneously.
Conclusion
Patients with COPD and common comorbidities show a variety of patterns of AECOPDs and comorbid flare-ups. Some patients, however, show repetitive patterns that could potentially be used to improve personalised disease management, if recognised.
