Comorbidity Burden of Dementia: A Hospital-Based Retrospective Study from 2003 to 2012 in Seven Cities in China
1Department of Neurology and Center for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, China
2Department of Preventive Medicine, Daping Hospital, Third Military Medical University, Chongqing, China
3Department of Neurology, Chengdu General Hospital of the PLA, Chengdu, China
4Department of Neurology, Lanzhou General Hospital of the PLA, Lanzhou, China
5Department of Neurology, Guangzhou General Hospital of the PLA, Guangzhou, China
Abstract
Dementia is increasing dramatically and imposes a huge burden on society. To date, there is a lack of data on the health status of patients with dementia in China. In an attempt to investigate the comorbidity burden of dementia patients in China at the national level, we enrolled 2,938 patients with Alzheimer’s disease (AD), vascular dementia (VaD), or other types of dementia, who were admitted to tertiary hospitals in seven regions of China from January 2003 to December 2012. The Charlson Comorbidity Index (CCI) was used to evaluate the comorbidity burden of the patients with dementia. Among these patients, 53.4% had AD, 26.3% had VaD, and 20.3% had other types of dementia. The CCI was 3.0 ± 1.9 for all patients, 3.4 ± 1.8 for those with VaD, and 3.0 ± 2.1 for those with AD. The CCI increased with age in all patients, and the length of hospital stay and daily expenses rose with age and CCI. Males had a higher CCI and a longer stay than females. Moreover, patients admitted in the last 5 years of the study had a higher CCI than those admitted in the first 5 years. We found that the comorbidity burden of patients with dementia is heavy. These findings provide a better understanding of the overall health status of dementia patients, and help to increase the awareness of clinicians and policy-makers to improve medical care for patients.
Keywords
Alzheimer’s disease; Vascular dementia; Prevalence; Comorbidity; Charlson comorbidity index