We determined trends over time in cardiovascular and non-cardiovascular comorbidity in patients hospitalised for cardiovascular disease (CVD).
Methods
The Dutch nationwide hospital register was used to identify patients hospitalised for CVD during 2000–2010. Comorbidity was defined as a previous hospital admission for CVD other than the index CVD, cancer, diabetes, musculoskeletal and connective tissue disorders, respiratory disorders, thyroid gland disorders, kidney disorders and dementia in the five years previous to hospital admittance for the index CVD. Trends were calculated in strata of age and sex and for different types of CVD: coronary heart disease (CHD), cerebrovascular disease (CVA), heart failure (HF) and peripheral arterial disease (PAD).
Results
We identified 2,397,773 admissions for CVD between 2000 and 2010. Comorbidity was present in 38%. In HF, PAD, CHD and CVA this was 54%, 46%, 40%, and 32%, respectively. Between 2000 and 2010, the percentage of patients with comorbidity increased (+ 1.1%), this increase was most pronounced in patients ≥ 75 years (+ 3.0%). Cardiovascular disease was the most frequent comorbid condition, though became less prevalent over time (men − 5%; women: − 2%), whereas non-cardiovascular comorbidity increased in men (+ 4%), and remained similar in women (− 1%). Cancer was the most common non-cardiovascular comorbid condition and increased in men and women (men: + 5%; women: + 4%).
Conclusions
Comorbid conditions are highly prevalent in patients hospitalised for CVD, especially HF and PAD patients. In older patients, prevalences increased over time. Cardiovascular diseases were the most common comorbid condition, though the prevalence decreased over the study period whereas the prevalence of cancer increased.
This author takes responsibility for the design of the study, acquisition of the data, interpretation of the data and revising the article critically for important intellectual content.
This author takes responsibility for the design of the study, interpretation of the data and revising the article critically for important intellectual content.