Predicting non-elective hospital readmission or death using a composite assessment of cognitive impairment and frailty in elderly inpatients with cardiovascular diseases. (25th November 2020)

• Record Type: Journal Article
• Authors: Yao, S; Wang, H; Yang, J; Sun, N
• Is Part Of: European heart journal. Volume 41:(2020)Supplement 2
• Publication Date: 2020-11-25
• Subjects: Cardiovascular Disease in the Elderly; Cardiology -- Periodicals; Heart -- Diseases -- Periodicals; 616.12005
• DOI: 10.1093/ehjci/ehaa946.3227
• Languages: English
• ISSNs: 0195-668X

Abstract

Abstract: Background: Cardiovascular disease (CVD) and related complications are significant healthcare problems in the growing elderly population. Metabolic factors are the predominant risk factors for CVD, sedentary behaviour and physical inactivity are major modifiable risk factors for CVD. Age-associated cognitive decline and impairment are associated with an increased mortality. Cognitive and physical components of frailty have pathophysiologic rationale as risk factors for CVD. There is a clinical need to identify more practical screens that can assist us to definite cognitive impairment and physical frailty, then to determine which patients with CVD are at high risk of adverse outcomes, early management of these high-risk patients can reduce readmission rates, healthcare spending, and improve quality of care. Purpose: We aimed to assess the utility of a combination developed using the mini-mental state examination + clock drawing test and the Fried phenotype for predicting non-elective hospital readmission or death within 6-month in elderly inpatients with CVD. Methods: A single center prospective cohort was conducted between September 2018 and February 2019. Inpatients aged 65 years or older were recruited. All enrolled patients received a comprehensive geriatric assessment during hospitalization. The Kaplan-Meier curves were used to estimate the cumulative incidence of events. The multivariate Cox regression model was used to analyze the association between frailty and cognitive status and the non-elective hospital readmission or death. Results: A total of 542 patients were included; and a total of 113 patients (20.9%) died or were readmitted at 6-month. Overall 20% screened positive for cognitive impairment, including 8% were cognitive impairment combined with physical frailty, which were more older, more common in women and non-married group, had a lower education and a higher risk of malnutrition. Frail participants with normal (hazard ratio [HR]: 1.73, 95% confidence intervals [CI]: 1.06–2.82, P=0.028) and impaired cognition (HR: 2.50, 95% CI: 1.27–4.91, P=0.008) had a higher risk of non-elective hospital readmission or death than robust patients, after adjustment for age, sex, education level, marital status, the presence of diabetes mellitus, heart failure, and previous stroke. Conclusions: The presence of physical frailty and cognitive frailty were powerful predictors of non-elective hospital readmission or death in elderly inpatients with CVD, and taking cognitive impairment into account in the frailty model may allow better prediction of adverse outcomes of frailty in the short time. Funding Acknowledgement: Type of funding source: Public Institution(s). Main funding source(s): Beijing Municipal Science & Technology Commission, Chinese Academy of Medical Sciences