Age- and gender-based comorbidity categories in general practitioner and pulmonology patients with COPD.
Su-Jong Kim-DornerTorben SchmidtAlexander KuhlmannJohann-Matthias Graf von der SchulenburgTobias WelteHeidrun LingnerPublished in: NPJ primary care respiratory medicine (2022)
Chronic obstructive pulmonary disease (COPD) is a debilitating medical condition often accompanied by multiple chronic conditions. COPD is more frequent among older adults and affects both genders. The aim of the current cross-sectional survey was to characterize chronic comorbidities stratified by gender and age among patients with COPD under the care of general practitioners (GP) and pulmonologists, using real-world patient data. A total of 7966 COPD patients (women: 45%) with more than 5 years of the observation period in the practice were examined using 60 different Chronic comorbid conditions (CCC) and Elixhauser measures. More than 9 in 10 patients had at least one, and 51.7% had more than three comorbidities. No gender difference was found in the number of comorbidities. However, men had higher Elixhauser-van Walraven index scores than women, and the types of comorbidities differed by gender. An increasing number of comorbidities was seen with aging but the patients in their 30s and 40s also had a high number of comorbidities. Moreover, GP patients had a higher number and a wider array of documented comorbidities than pulmonology patients did. Psychological comorbidities were common in all patients, but particularly among younger patients. These findings around gender- and age-stratified comorbidities under the care of GPs and pulmonologists have implications for the choice of data provenience for decision-making analysis and treatment selection and success.
Keyphrases
- end stage renal disease
- chronic obstructive pulmonary disease
- ejection fraction
- chronic kidney disease
- newly diagnosed
- healthcare
- prognostic factors
- peritoneal dialysis
- adipose tissue
- cystic fibrosis
- physical activity
- high resolution
- machine learning
- electronic health record
- big data
- middle aged
- high throughput
- breast cancer risk