Department of Public Health and Primary Care, Katholieke Universiteit Leuven, Belgium; Institute of Health and Society, Université Catholique de Louvain, Belgium.
Department of Public Health and Primary Care, Katholieke Universiteit Leuven, Belgium.
J Am Med Dir Assoc. 2020 Mar;21(3):440.e1-440.e8. doi: 10.1016/j.jamda.2019.08.029. Epub 2019 Oct 31.
To compare the predictive performance of 3 frailty identification tools for mortality, hospitalization, and functional decline in adults aged ≥80 years using risk reclassification statistics and decision curve analysis.
Population-based, prospective cohort.
BELFRAIL study, Belgium.
560 community-dwelling adults aged ≥80 years.
Frailty by Cardiovascular Health Study (CHS) phenotype, Longitudinal Aging Study Amsterdam (LASA) markers, and Groeningen Frailty Indicator (GFI); mortality until 5.1 ± 0.25 years from baseline and hospitalization until 3.0 ± 0.25 years; and functional status assessed by activities of daily living at baseline and after 1.7 ± 0.21 years.
Frailty prevalence was 7.3% by CHS phenotype, 21.6% by LASA markers, and 22% by GFI. Participants determined to be frail by each tool had a significantly higher risk for all-cause mortality and first hospitalization. For functional decline, only frail by GFI had a higher adjusted odds ratio. Harrell 's C-statistic for mortality and hospitalization and area under receiver operating characteristic curve for functional decline were similar for all tools and <0.70. Reclassification statistics showed improvement only by LASA markers for hospitalization and mortality. In decision curve analysis, all tools had higher net benefit than the 2 default strategies of "treat all" and "treat none" for mortality risk ≥20%, hospitalization risk ≥35%, and functional decline probability ≥10%, but their curves overlapped across all relevant risk thresholds for these outcomes.
In a cohort of adults aged ≥80 years, 3 frailty tools based on different conceptualizations and assessment sources had comparable but unsatisfactory discrimination for predicting mortality, hospitalization, and functional decline. All showed clinical utility for predicting these outcomes over relevant risk thresholds, but none was significantly superior. Future research on frailty tools should include a focus on the specific group of adults aged ≥80 years, and the predictive accuracy for adverse outcomes of different tools needs a comprehensive assessment that includes decision curve analysis.
使用风险重新分类统计和决策曲线分析比较 3 种衰弱识别工具对 80 岁以上成年人死亡率、住院和功能下降的预测性能。
基于人群的前瞻性队列研究。
比利时 BELFRAIL 研究。
560 名 80 岁以上的社区居住成年人。
心血管健康研究（CHS）表型、纵向老龄化研究阿姆斯特丹（LASA）标志物和格罗宁根衰弱指标（GFI）确定的衰弱；从基线开始的 5.1±0.25 年的死亡率和 3.0±0.25 年的住院率；以及基线和 1.7±0.21 年后的日常生活活动评估的功能状态。
CHS 表型的衰弱患病率为 7.3%，LASA 标志物为 21.6%，GFI 为 22%。每个工具确定为虚弱的参与者所有原因死亡率和首次住院的风险显著更高。对于功能下降，只有 GFI 确定为虚弱的参与者具有更高的调整后优势比。所有工具的死亡率和住院率的 Harrell 'C 统计量和功能下降的接收者操作特征曲线下面积均相似，均<0.70。重新分类统计显示，仅 LASA 标志物对住院和死亡率有改善。在决策曲线分析中，对于死亡率风险≥20%、住院风险≥35%和功能下降概率≥10%，所有工具的净获益均高于“治疗所有”和“治疗无”这 2 种默认策略，但在这些结果的所有相关风险阈值上，它们的曲线都重叠。
在 80 岁以上成年人队列中，基于不同概念化和评估来源的 3 种虚弱工具在预测死亡率、住院和功能下降方面具有相似但不令人满意的区分能力。所有工具对于预测这些结果在相关风险阈值以上都具有临床实用性，但没有一种工具具有明显优势。未来对虚弱工具的研究应关注 80 岁以上成年人这一特定群体，并且不同工具的不良结局预测准确性需要包括决策曲线分析在内的全面评估。
