期刊
JOURNAL OF CARDIAC FAILURE
卷 29, 期 3, 页码 414-418出版社
CHURCHILL LIVINGSTONE INC MEDICAL PUBLISHERS
DOI: 10.1016/j.cardfail.2022.09.011
关键词
Heart failure; falls; frailty
The objective of this study was to quantify the frequency and predictors of falls over 1 year among adults with heart failure (HF). The results showed that nearly 40% of HF patients experienced a fall within 1 year. Screening for comorbidities, slowness, and exhaustion may help identify those at risk for a fall.
Objective: Adults with heart failure (HF) may be at high risk for falling due to age, comorbid-ities and frailty; however, few studies have examined falls in HF. The purpose of this study was to quantify the frequency and predictors of falls over 1 year among adults with HF. Methods: We conducted a prospective study of adults with New York Heart Association (NYHA) functional class I -IV HF. After baseline assessment of physical frailty and clinical char-acteristics, participants self-reported falls every 3 months during 1 year. Comparative statistics were used to identify baseline differences between those who fell vs those who did not. A stepwise negative binomial regression model was used to identify predictors of fall rate over 1 year. Results: The sample (n = 111) was 63.4 +/- 15.7 years old, 48% were women, 28% had HF with preserved ejection fraction, and 41% were frail. Over 1 year, 43 (39%) of participants reported at least 1 fall and 28 (25%) of participants reported 2+ falls. Among those who fell, 29 (67%) reported injurious falls. Those who fell had significantly higher body mass indexes and were more likely to have NYHA class III/IV, type 2 diabetes and HF with preserved ejection fraction and to meet slowness and physical exhaustion criteria than those who did not fall. The fall rate was elevated among those with type 2 diabetes and those meeting the slowness and physical exhaustion criteria for physical frailty. Conclusions: Nearly 40% of adults with HF experienced a fall within 1 year. Screening for comorbidities, slowness and exhaustion may help to identify those at risk for a fall.
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