背景:在这项观察性研究中,我们比较了50岁及以上成年人在主动站立测试中的连续生理信号,由三个不同的标准表征为虚弱,使用爱尔兰老龄化纵向研究(TILDA)的数据。
方法:这项研究利用了TILA的数据,一项针对爱尔兰50岁或以上社区居住成年人的具有里程碑意义的前瞻性队列研究.TILDA中的初始采样策略基于随机地理目录采样。确定了四个独立的组:仅通过使用的脆弱工具之一(物理脆弱表型(FP),32项脆弱指数(FI),或临床虚弱量表(CFS)分类树),第四组,参与者没有被这些工具中的任何一个定性为虚弱。在主动站立测试期间收集连续的非侵入性生理信号,包括收缩压(sBP)和舒张压(dBP),以及心率(HR),使用数字动脉光电容积描记术。此外,额叶脑氧合(Oxy),脱氧(脱氧),和组织饱和指数(TSI)也使用近红外光谱(NIRS)进行非侵入性测量。在虚弱组之间对信号进行可视化,并使用一维统计参数映射(SPM)进行统计学比较。
结果:共纳入1124名参与者(平均年龄为63.5岁;50.2%为女性):23名仅由FP表征为虚弱,97由FI,38由CFS,和966没有这些标准。SPM分析显示,与非虚弱组相比,只有通过FI表征为虚弱的组具有显著不同的信号(p<0.001)。具体来说,他们在站立后10至15s之间的HR增益减弱,在站立后15至20s之间的sBP和dBP赤字更大。
结论:FI被证明更擅长捕捉对站立的不同生理反应,可能是由于其定义中直接包含了心血管疾病。在通过不同的虚弱标准识别的虚弱人群中,观察到心血管信号的动态存在显着差异。建议在生理信号上使用虚弱识别工具时应谨慎,特别是主动站立测试中的神经心血管信号。
BACKGROUND: In this observational study, we compared continuous physiological signals during an active standing test in adults aged 50 years and over, characterised as frail by three different criteria, using data from The Irish Longitudinal Study on Ageing (TILDA).
METHODS: This study utilised data from TILDA, an ongoing landmark prospective cohort study of community-dwelling adults aged 50 years or older in Ireland. The initial sampling strategy in TILDA was based on random geodirectory sampling. Four independent groups were identified: those characterised as frail only by one of the frailty tools used (the physical Frailty Phenotype (FP), the 32-item Frailty Index (FI), or the Clinical Frailty Scale (CFS) classification tree), and a fourth group where participants were not characterised as frail by any of these tools. Continuous non-invasive physiological signals were collected during an active standing test, including systolic (sBP) and diastolic (dBP) blood pressure, as well as heart rate (HR), using digital artery photoplethysmography. Additionally, the frontal lobe cerebral oxygenation (Oxy), deoxygenation (Deoxy), and tissue saturation index (TSI) were also non-invasively measured using near-infrared spectroscopy (NIRS). The signals were visualised across frailty groups and statistically compared using one-dimensional statistical parametric mapping (SPM).
RESULTS: A total of 1124 participants (mean age of 63.5 years; 50.2% women) were included: 23 were characterised as frail only by the FP, 97 by the FI, 38 by the CFS, and 966 by none of these criteria. The SPM analyses revealed that only the group characterised as frail by the FI had significantly different signals (p < 0.001) compared to the non-frail group. Specifically, they exhibited an attenuated gain in HR between 10 and 15 s post-stand and larger deficits in sBP and dBP between 15 and 20 s post-stand.
CONCLUSIONS: The FI proved to be more adept at capturing distinct physiological responses to standing, likely due to its direct inclusion of cardiovascular morbidities in its definition. Significant differences were observed in the dynamics of cardiovascular signals among the frail populations identified by different frailty criteria, suggesting that caution should be taken when employing frailty identification tools on physiological signals, particularly the neurocardiovascular signals in an active standing test.