ArticleJournal of atherosclerosis and thrombosis2023
Detection of the Relationship between the Multi-Dimensional Data Sets of Serially Measured Blood Pressure and the Future Risk of Death in Healthy Elderly Japanese Population.
Article in Journal of atherosclerosis and thrombosis, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
aimsWhether the multi-dimensional data of serially measured blood pressure contains information for predicting the future risk of death in elderly individuals in nursing homes is unclear.
methodsOf the elderly individuals staying in a nursing home, 19,740 and 40,055 individuals with serially measured blood pressure from day 1 to 365 (for AI-long) and 1 to 90 (for AI-short) along with the death information at day 366 to 730 and 91-365 were included. The neural network-based artificial intelligence (AI) was applied to find the relationship between BP time-series and the future risks of death in both populations.
resultsAI-long found a significant relationship between the serially measured BP from day 1 to day 365 days and the risk of death occurring 366-730 days with c-statistics of 0.57 (95% CI: 0.51-0.63). AI-short also found a significant relationship between the serially measured BP from day 1 to day 90 and the rate of death occurring 91-365 days with c-statistics of 0.58 (95%CI: 0.52-0.63).
conclusionOur results suggest that neural network-based AI could find the hidden subtle relationship between multi-dimensional data of serially measured BP and the future risk of death in apparently healthy elderly Japanese individuals under nursing care.
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