【Abstract】Objective To analyze the risk factors for cardiovascular events related to potentially inappropriate medication (PIM) among community-dwelling elderly people and investigate the impact of PIM on mortality in order to provide a reference for promoting rational use of medicine. Methods Between September 2009 and June 2010, a survey was conducted on the elderly people aged≥65 years living in the Wanshou Road area of Beijing based on the Beers standard (2019 version). Parallel double entry was employed to input the data through EpiData. SPSS statistics 25.0 was used for data analysis. Student′s t test, Mann-Whitney U test, Chi-square test, or Fisher exact test was applied for intergroup comparison depending on data type. Multivariate logistic regression model was conducted to analyze the influencing factors for PIM. Cox proportional hazards regression model was utilized to determine the effect of PIM on mortality. Results For the 1 730 included elderly people, they suffered from 0-7 types of cardiovascular diseases and had polypharmacy of 0-11 types of conventional medicines. The patients with comorbidity of multiple cardiovascular diseases accounted for 50.4% (872/1 730), the incidence of polypharmacy was 8.0% (139/1 730), and the incidence of PIM was 18.6% (321/1 730). Comorbidity of multiple cardiovascular diseases (OR=2.610,95%CI 1.974-3.451), multiple use of drugs in the cardiovascular system (OR=1.805,95%CI 1.215-2.681), and endogenous creatinine clearance rate (Ccr) <30 ml/min (OR=2.446,95%CI 0.991-6.035) were risk factors for PIM in the elderly population in the community. Education level of college degree or above (OR=0.474,95% CI 0.351-0.640) and married (OR=0.681,95%CI 0.502-0.924) were protective factors for PIM. The occurrence of PIM increased the risk of cardiovascular death by 78.3% (HR=1.783,95%CI 1.155-2.752) in the general population and 114.8% (HR=2.148,95%CI 1.154-3.996) in the male. Conclusion PIM is quite common among community-dwelling old adults and can be regarded as a reference indicator for predicting mortality risk.
This work was supported by the National Natural Science Foundation of China (82173589, 82173590), the National Key Research and Development Program of China (2022YFC2503605) and the Special Fund for Capital Health Improvement and Research (2022-2G-5031).