Hermida R C, Ayala D E, Fernández J R, Fraga J M
Bioengineering and Chronobiology Laboratories, E.T.S.I. Telecomunicación, University of Vigo, Spain.
Biomed Instrum Technol. 1994 Jan-Feb;28(1):43-51.
Genetic risk is a primary contributing factor to the predisposition of a newborn child to elevated blood pressure later in life. To determine whether there is a correlation between potential genetic risk as established by family history and measured physiologic variables in the neonate, the systolic and diastolic blood pressures and heart rates of 150 newborn babies were automatically monitored at about 30-minute intervals for 48 hours with a Nippon Colin device, starting early after birth. Circadian parameters (obtained by the linear least-squares fit of a 24-hour cosine curve to each individual series) and descriptive statistics for the three circulatory variables were used in a multiple-regression analysis to compute a linear prediction function for a neonatal cardiovascular risk score. This score was obtained for each neonate on the basis of the presence or absence of overt cardiovascular disease, elevated blood pressure, or obesity across two generations, those of the newborn's parents and grandparents. Results from multiple regression indicate that the best model for prediction of the risk score includes the circadian amplitudes of systolic and diastolic blood pressure, the circadian range of heart rate, and the 90% range and standard deviation of diastolic blood pressure. The multiple correlation coefficient between the predicted and the computed risk scales is 0.666, a value that, although statistically significant (p < 0.001), is still low for a generalized practical use of the model in predicting risk.(ABSTRACT TRUNCATED AT 250 WORDS)
遗传风险是新生儿日后患高血压易感性的主要促成因素。为了确定家族病史所确定的潜在遗传风险与新生儿测量的生理变量之间是否存在相关性,使用日本 Colin 设备,从出生后早期开始,每隔约 30 分钟自动监测 150 名新生儿的收缩压、舒张压和心率,持续 48 小时。昼夜节律参数(通过对每个个体序列进行 24 小时余弦曲线的线性最小二乘拟合获得)和三个循环变量的描述性统计数据用于多元回归分析,以计算新生儿心血管风险评分的线性预测函数。该评分是根据新生儿的父母和祖父母两代人是否存在明显的心血管疾病、高血压或肥胖来为每个新生儿获得的。多元回归结果表明,预测风险评分的最佳模型包括收缩压和舒张压的昼夜节律幅度、心率的昼夜节律范围以及舒张压的 90%范围和标准差。预测风险量表与计算出的风险量表之间的多重相关系数为 0.666,该值虽然具有统计学意义(p < 0.001),但对于该模型在预测风险方面的广泛实际应用而言仍然较低。(摘要截短于 250 字)