Geographical distribution of the P-R interval reference value of Chinese healthy adults.

Abstract

To explore the relationship between the geographical factors and P-R interval reference value of healthy adults, and to elucidate the geographical distribution of the P-R interval reference value in Chinese adults, to provide the basis for the standard of P-R interval reference value in different regions. The P-R interval reference value of 64,753 healthy adults in 341 cities (counties) level hospitals, research institutes, and universities in China was collected, and 15 geographical data and P-R interval reference value of healthy people were studied, and then 10 geographical factors with correlation were extracted for further analysis. Using spatial autocorrelation analysis to determine the autocorrelation of data space, using backward regression and ridge regression to construct forecast model, and the optimal prediction model is selected by comparing and evaluating the prediction effect of each model, the spatial distribution map of P-R interval reference value of Chinese healthy adults was constructed by statistical analysis. There was a significant correlation between normal reference value of adult P-R interval reference value and geographical factors. The regression model of normal reference value and geographical factors of adult P-R interval reference value was established by ridge regression analysis method: [Formula: see text] =149.2 + 0.02590X2 + 0.0005000X3 + 0.02634X5-0.05890X6 + 0.0008400X7 + 0.01606X8 + 0.2592X9-0.03638X12 + 5.888X13-0.2126X15 ± 8.6, and ArcGIS10.2. In the software interpolation method, the distribution chart of normal reference value of Chinese adult P-R interval reference value was inserted. Knowing the geographical factors of some places in China, we can use this model to estimate the P-R interval reference value in this region, and to obtain the normal P-R interval reference value between adults anywhere in China.