One-Dimensional Statistical Parametric Mapping Identifies Impaired Orthostatic Cerebrovascular and Cardiovascular Response in Frailty Index

The journals of gerontology. Series A, Biological sciences and medical sciences

J Gerontol A Biol Sci Med Sci. 2021 Apr 30;76(5):885-892. doi: 10.1093/gerona/glaa315.

ABSTRACT

BACKGROUND: Orthostasis is a potent physiological stressor which adapts with age. The age-related accumulation of health deficits in multiple physiological systems may impair the physiological response to orthostasis and lead to negative health outcomes such as falls, depression, and cognitive decline. Research to date has focused on changes with orthostasis at prespecified intervals of time, without consideration for whole signal approaches.

METHODS: One-dimensional statistical parametric mapping identified regions in time of significant association between variables of interest using a general linear model. Frailty index operationalized accumulated health and social deficits using 32-items from a computer-assisted interview. This study examined the association of frailty index on blood pressure, heart rate, and cerebral oxygenation during an orthostatic test in a sample of 2742 adults aged 50 or older from The Irish Longitudinal Study on Ageing.

RESULTS: Frailty index was seen to be negatively associated with cerebral oxygenation changes from baseline over a period of 7 seconds (p = .036). Heart rate and systolic blood pressure were positively and negatively associated with frailty index over periods of 17 seconds (p = .001) and 10 seconds (p = .015), respectively.

CONCLUSIONS: Statistical parametric mapping demonstrated these significant regions of cerebral oxygenation during orthostasis provide indirect evidence of impaired autoregulation associated with frailty. Statistical parametric mapping also replicated prior relationships in heart rate and systolic blood pressure associated with a higher frailty index. These findings highlight the utility of 1-dimensional statistical parametric modeling in identifying significant regions of interest in physiological recordings.

PMID:33355652 | PMC:PMC8087271 | DOI:10.1093/gerona/glaa315