Chaochao Ma1, Liangyu Xia1, Xinqi Chen1, Jie Wu1, Yicong Yin1, Lian Hou1, Xiaoqi Li1, Xiuzhi Guo1, Songbai Lin2, Ling Qiu1. 1. Department of Laboratory Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing 100730, China. 2. Department of Health Care, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China.
Abstract
BACKGROUND: the ageing population has increased in many countries, including China. However, reference intervals (RIs) for older people are rarely established because of difficulties in selecting reference individuals. Here, we aimed to analyse the factors affecting biochemical analytes and establish RI and age-related RI models for biochemical analytes through mining real-world big data. METHODS: data for 97,220 individuals downloaded from electronic health records were included. Three derived databases were established. The first database included 97,220 individuals and was used to build age-related RI models after identifying outliers by the Tukey method. The second database consisted of older people and was used to establish variation source models and RIs for biochemical analytes. Differences between older and younger people were compared using the third database. RESULTS: sex was the main source of variation of biochemical analytes for older people in the variation source models. The distributions of creatinine and uric acid were significantly different in the RIs of biochemical analytes for older people established according to sex. Age-related RI models for biochemical analytes that were most affected by age were built and visualized, revealing various patterns of changes from the younger to older people. CONCLUSION: the study analysed the factors affecting biochemical analytes in older people. Moreover, RI and age-related RI models of biochemical analytes for older people were established to provide important insight into biological processes and to assist clinical use of various biochemical analytes to monitor the status of various diseases for older people.
BACKGROUND: the ageing population has increased in many countries, including China. However, reference intervals (RIs) for older people are rarely established because of difficulties in selecting reference individuals. Here, we aimed to analyse the factors affecting biochemical analytes and establish RI and age-related RI models for biochemical analytes through mining real-world big data. METHODS: data for 97,220 individuals downloaded from electronic health records were included. Three derived databases were established. The first database included 97,220 individuals and was used to build age-related RI models after identifying outliers by the Tukey method. The second database consisted of older people and was used to establish variation source models and RIs for biochemical analytes. Differences between older and younger people were compared using the third database. RESULTS: sex was the main source of variation of biochemical analytes for older people in the variation source models. The distributions of creatinine and uric acid were significantly different in the RIs of biochemical analytes for older people established according to sex. Age-related RI models for biochemical analytes that were most affected by age were built and visualized, revealing various patterns of changes from the younger to older people. CONCLUSION: the study analysed the factors affecting biochemical analytes in older people. Moreover, RI and age-related RI models of biochemical analytes for older people were established to provide important insight into biological processes and to assist clinical use of various biochemical analytes to monitor the status of various diseases for older people.
Authors: Guerino Recinella; Giovanni Marasco; Giovanni Serafini; Lorenzo Maestri; Giampaolo Bianchi; Paola Forti; Marco Zoli Journal: Aging Clin Exp Res Date: 2020-10-08 Impact factor: 3.636