南方医科大学学报 ›› 2016, Vol. 36 ›› Issue (11): 1555-.

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健康成年人血肌酐参考值的地理环境分布

韦德智,葛淼,王聪霞,林倩怡,李孟姣,李鹏   

  • 出版日期:2016-11-20 发布日期:2016-11-20

Geographical distribution of the Serum creatinine reference values of healthy adults

  • Online:2016-11-20 Published:2016-11-20

摘要: 目的探讨健康成年人血肌酐(Scr)参考值与地理因素之间的关系,为制定不同地域的Scr 参考值标准提供科学依 据。方法搜集23 个省、4 个直辖市、5 个自治区的347 所医疗机构测定的29697 例健康成年人Scr 参考值,选取23 项地理数 据与Scr 参考值进行相关分析,确定与Scr 参考值显著相关的地理因素,通过主成分分析和岭回归分析分别建模,并对比实 测值与预测值的拟合度并选取最优预测模型,最后利用克里金插值法构建中国健康成年人Scr 参考值空间分布图。结果健 康成年人Scr 参考值与纬度、年日照时数、年平均气温、年平均相对湿度、年降水量、气温年较差、表土(粉土)阳离子交换量等 7 项地理因素指标存在显著关系,参考值的分布趋势为南部较高,北部较低,随纬度呈较有规律的变化。结论若得知某一 地区的地理因素数据便可以进行健康成年人Scr 参考值的预测,将地理因素纳入医学分析有助于因地制宜确定不同地区的 医学参考值、提高临床诊断的准确性。

Abstract: Objective To explore the relationship between serum creatinine (Scr) reference values in healthy adults and geographic factors and provide evidence for establishing Scr reference values in different regions. Methods We collected 29 697 Scr reference values from healthy adults measured by 347 medical facilities from 23 provinces, 4 municipalities and 5 autonomous regions. We chose 23 geographical factors and analyzed their correlation with Scr reference values to identify the factors correlated significantly with Scr reference values. According to the Principal component analysis and Ridge regression analysis, two predictive models were constructed and the optimal model was chosen after comparison of the two model’s fitting degree of predicted results and measured results. The distribution map of Scr reference values was drawn using the Kriging interpolation method. Results Seven geographic factors, including latitude, annual sunshine duration, annual average temperature, annual average relative humidity, annual precipitation, annual temperature range and topsoil (silt) cation exchange capacity were found to correlate significantly with Scr reference values. The overall distribution of Scr reference values featured a pattern that the values were high in the south and low in the north, varying consistently with the latitude change. Conclusion The data of the geographic factors in a given region allows the prediction of the Scr values in healthy adults. Analysis of these geographical factors can facilitate the determination of the reference values specific to a region to improve the accuracy for clinical diagnoses.