Abstract：
The brain\'s temperature measurements (TB) in patients with severe brain damage are important, in order to offer the optimal treatment. The purpose of this research is the creation of mathematical models for the TB\'s prediction, based on the temperatures in the bladder (TBL), femoral artery (TFA), ear canal (TΕC), and axilla (TA), without the need for placement of intracranial catheter, contributing significantly to the research of the human thermoregulatory system.The research involved 18 patients (13 men and 5 women), who were hospitalized in the adult intensive care units (ICU) of Larissa\'s two hospitals, with severe brain injury. An intracranial catheter with a thermistor was used to continuously measure TB and other parameters. The TB\'s measurements, and simultaneously one or more of TBL, TFA, TEC, and TA, were recorded every 1 h.To create TB predicting models, the data of each measurement was separated into (a) model sample (measurements\' 80%) and (b) validation sample (measurements\' 20%). Multivariate linear regression analysis demonstrated that it is possible to predict brain\'s temperature (PrTB), using independent variables (R2 was TBL = 0.73, TFA = 0.80, TEC = 0.27, and TA = 0.17, p < 0.05). Significant linear associations were found, statistically, and no difference in means between TB and PrTB of each prediction model. Also, the 95% limits of agreement and the percent coefficient of variation showed sufficient agreement between the TB and PrTB in each prediction model.In conclusion, brain\'s temperature prediction models based on TBL, TFA, TEC, and TA were successful. Its determination contributes to the improvement of clinical decision-making.
摘要：
大脑的温度测量（TB）在患有严重脑损伤的患者是重要的，以提供最佳治疗。本研究的目的是创建结核病预测的数学模型，根据膀胱中的温度（TBL），股动脉(TFA),耳道(TEC),和腋下（TA），不需要放置颅内导管,为人体体温调节系统的研究做出了重要贡献。该研究涉及18名患者（13名男性和5名女性），他们在Larissa的两家医院的成人重症监护病房（ICU）住院，严重的脑损伤.使用带有热敏电阻的颅内导管连续测量TB和其他参数。TB的测量，同时一个或多个TBL，TFA,TEC,还有TA,每1小时记录一次。要创建结核病预测模型，将每项测量的数据分为(a)模型样本(测量值\'80%)和(b)验证样本(测量值\'20%).多元线性回归分析表明，可以预测大脑温度(PrTB)，使用独立变量（R2为TBL=0.73，TFA=0.80，TEC=0.27，TA=0.17，p<0.05）。发现了显著的线性关联，统计，每个预测模型的TB和PrTB之间的均值没有差异。此外，95%的一致限度和百分比的变异系数表明，在每个预测模型中，TB和PrTB之间有足够的一致性。总之,基于TBL的大脑温度预测模型，TFA,TEC,TA成功了。它的确定有助于临床决策的改进。
