| Objective:Normal reference value of cardiac output and heart rate are two important indicators of the cardiac function check.They are important to indications of human’s life.And they are clinically the two most commonly used indicators to describe and evaluate the cardiac function.Cardiac output is the important factor of evaluation of circulating systemic efficiency. It largely adapt to the metabolic rate of body cells.There are close relationship between heart rate and cardiac cycle’s time and duration. However, the lack of a unified standard for cardiac output and heart rate reference value at home and abroad, a phenomenon seriously affect the accuracy of clinical diagnosis.Therefore, the quantitative and thematic study of the relationship between two cardiac function factors reference value and geographic factors is of great significance.Methods:From the perspective of natural geographical factors, we research on the relationship between geographical factors and cardiac output and heart rate of Cinese normal reference, using the linear and nonlinear quantitative study and contrast in different area,different age and different gender; Applying Kerrey (Kriging) method, with Arc Map module of Arc GIS softwares gets the normal reference of cardiac output and heart rate in healthy people in different area, different age and different gender of China. Although many literatures have also reported the relationship between the normal reference value of two heart functions and altitude, annual average temperature and so on, they have researched by only qualitative descriptions or simple linear regression analysis, and for the one to one relationship. By far, no paper does such systemic study on the relationship between them based on China entire geographical environment.Results:(1)In order to explore the perplexing relationship between senven geographical factors and normal reference value of cardiac and output and heart rate, collection of all China’s various regions has been obtained through a large number of literature retrieval and purchase method. They are as follows:cardiac output of3923adult males, cardiac output of2952adult females, heart rate of1844adolescent females, heart rate of13505adult males, heart rate of12062adult females, heart rate of3750olders. (2)According to share information provided by the State Bureau of Surveying and Mapping Center, the National Weather Service’s data center and related geographical works, dictionaries and literature, seven geographical factors are collected:altitude(X1), annual sunshine duration(X2), annual mean temperature(X3), annual mean relative humidity (X4), and annual precipitation (X5), annual temperature range (X6) and annual average wind speed (X7).(3)With the quantitative study of relationship between the medical indicators and geographical factors, we should build multiple linear regression models, curve evaluation models and factor analysis models between them. Eventually, through the comparation, we should find out the optimal forecasting models:①multiple linear regression model of normal reference value of cardiac output of adult females: Y=11.665-0.078882X3-0.0012091X5-0.046812X6+0.22990X7-0.06360X8±0.763。②factor analysis model of normal reference value of of cardiac output adult males: Y=5.6203-0.00014752X1-0.00012074X2+0.011332X3+0.0073441X4+0.00012832X5-0.0091319X6+0.043477X7±0.067。③multiple linear regression model of normal reference value of heart rate of adolescent females: Y=72.080-0.0086378X1+0.0054584X2±3.773④factor analysis model of normal reference value of heart rate of adult males: Y=92.063+0.0026932X1-0.00010906X2-0.061697X3-0.072034X4-0.00073385X5-0.20493X6-4.40019X7±0.437。⑤curve evaluation model of normal reference value of heart rate of adult females: Y=78.501-0.805X3+0.026X32⑥factor analysis model of normal reference value of heart rate of old people: Y=80.22+0.0009641X1-0.0006450X2+0.01799X3-0.003782X4+0.0002128X5-0.1352X6-1.3696X7±0.433(4)According to optimal prediction model and geostatistical analysis method, using the Arc Map module of Arc CIS softwares, loads normal reference value of cardiac function and attribute value of geographical factors of4383regions into the well-vectored map, and then applying the Kringing interpolation method to get spatial distribution map of normal reference value of cardiac function of two indicators respectively. Conclusion:The above models can estimate the Chinese regions different age and different gender’s normal reference cardiac function, they can provide scientific reference standard for clinical medicine and social psychology conveniently, and also can clearly find distribution trend about two indicators of cardiac function from the map, and roughly estimate the reference value of the two indicators of cardiac function in particular place. |
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