National Health and Medical Research Council (NHMRC) Centre of Research Excellence: Frailty and Healthy Ageing, University of Adelaide, Adelaide, South Australia.
Adelaide Geriatrics Training & Research with Aged Care (G-TRAC) Centre, Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia.
J Am Geriatr Soc. 2019 Nov;67(11):2311-2317. doi: 10.1111/jgs.16066. Epub 2019 Jul 18.
Frailty places individuals at greater risk of adverse health outcomes. However, it is a dynamic condition and may not always lead to decline. Our objective was to determine the relationship between frailty status (at baseline and follow-up) and mortality using both the frailty phenotype (FP) and frailty index (FI).
Population-based cohort.
Community-dwelling older adults.
A total of 909 individuals aged 65 years or older (55% female), mean age 74.4 (SD 6.2) years, had frailty measurement at baseline. Overall, 549 participants had frailty measurement at two time points.
Frailty was measured using the FP and FI, with a mean 4.5 years between baseline and follow-up. Mortality was matched to official death records with a minimum of 10 years of follow-up.
For both measures, baseline frailty was a significant predictor of mortality up to 10 years, with initially good predictive ability (area under the curve [AUC] = .8-.9) decreasing over time. Repeated measurement at follow-up resulted in good prediction compared with lower (AUC = .6-.7) discrimination of equivalent baseline frailty status. In a multivariable model, frailty measurement at follow-up was a stronger predictor of mortality compared with baseline. Frailty change for the Continuous FI was a significant predictor of decreased or increased mortality risk based on corresponding improvement or worsening of score (hazard ratio = 1.04; 95% confidence interval = 1.02-1.07; P = .001).
Frailty measurement is a good predictor of mortality up to 10 years; however, recency of frailty measurement is important for improved prediction. A regular review of frailty status is required in older adults. J Am Geriatr Soc 67:2311-2317, 2019.
衰弱使个体面临更大的健康不良后果风险。然而，它是一种动态的状态，并不总是导致衰退。我们的目的是使用衰弱表型（FP）和衰弱指数（FI）来确定衰弱状态（基线和随访时）与死亡率之间的关系。
基于人群的队列研究。
居住在社区的老年人。
共有 909 名年龄在 65 岁或以上（55%为女性）、平均年龄 74.4（SD 6.2）岁的个体在基线时进行了衰弱测量。总体而言，有 549 名参与者在两个时间点进行了衰弱测量。
使用 FP 和 FI 测量衰弱，基线和随访之间的平均时间为 4.5 年。通过与官方死亡记录相匹配来确定死亡率，随访时间至少为 10 年。
对于这两种测量方法，基线衰弱是 10 年内死亡率的重要预测指标，最初具有良好的预测能力（曲线下面积[AUC]为.8-.9），随着时间的推移逐渐降低。在随访时进行重复测量可与基线时衰弱状态的较低（AUC =.6-.7）区分能力相比，进行更好的预测。在多变量模型中，与基线相比，随访时的衰弱测量是死亡率的更强预测指标。连续 FI 的衰弱变化是死亡率风险降低或增加的显著预测指标，这取决于相应的评分改善或恶化（风险比=1.04；95%置信区间=1.02-1.07；P=.001）。
衰弱测量是 10 年内死亡率的良好预测指标；然而，衰弱测量的及时性对于改善预测很重要。需要定期审查老年人的衰弱状况。美国老年医学会 67:2311-2317,2019。
