医学
组内相关
可靠性(半导体)
急诊科
预测效度
急诊医学
结构效度
回顾性队列研究
内科学
心理测量学
精神科
临床心理学
量子力学
物理
功率(物理)
作者
H Ellis,Liam Dunnell,Julie Whitney,Cara Jennings,Dan Wilson,Jane Tippett,James Teo,Zina Ibrahim,Kenneth Rockwood
出处
期刊:Age and Ageing
[Oxford University Press]
日期:2025-06-27
卷期号:54 (7)
被引量:1
标识
DOI:10.1093/ageing/afaf192
摘要
Abstract Background Laboratory-based frailty indices (FI-Labs) offer potential adjuncts and alternatives to clinical assessments. Still, their optimal configuration and construct validity compared with nurse-assessed Clinical Frailty Scale (CFS) scores remain unclear. Methods In this retrospective cohort study, we evaluated five FI-Lab configurations against nurse-assessed CFS scores using data from 74 493 emergency department visits. We examined their association with clinical outcomes and assessed measurement reliability using mixed effects models. Results While nurse assessments demonstrated superior outcome discrimination (c-statistic 0.726 for 90-day mortality versus 0.718 for best FI-Lab), automated FI-Lab measures showed significantly greater between-visit reliability [intraclass correlation coefficient (ICC) = 0.51–0.76 versus 0.37 for nurse CFS]. The drug-adjusted FI-Lab demonstrated highest reliability (ICC = 0.76) but weaker age associations (β = 0.002, P = .08) compared to other configurations (β = 0.006–0.013, P < .001). In complex models adjusting for illness severity, nurse CFS scores showed stronger mortality associations (HR 1.55, 95% CI 1.45–1.66 per standard deviation) compared to FI-Lab configurations (HR range 1.19–1.29). Notably, all frailty measures showed effect sizes comparable to age (HR range 1.37–1.55 per SD). Conclusions Automated FI-Lab measures offer a reliability advantage over nurse-assessed CFS scores despite slightly lower predictive validity for mortality. Their comparable effect sizes to age suggest these automated measures capture clinically meaningful patient characteristics. This trade-off between reliability and predictive validity suggests that integrated approaches combining automated screening with targeted clinical assessment may provide optimal frailty identification in emergency settings.
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