数学模型在颅脑损伤患者入院指标与预后指标多因素模型分析中的应用

目的探讨颅脑损伤患者入院时的多项指标以及指标间交互作用对患者预后指标的影响。 方法收集2013年1月至2017年8月入住扬州大学附属医院重症医学科的130例颅脑外伤患者的临床资料进行分析，建立预后指标与入院指标的数学模型，进行数学模型相关分析。并收集2017年10月至2018年12月26例颅脑外伤患者临床资料进行建模数据外部验证。 结果镇静躁动评分（RASS）平方项、格拉斯哥昏迷评分（GCS）与RASS评分交互项、年龄与急性生理和慢性健康状况（APACHEⅡ）评分交互项、心率与乳酸（LAC）交互项等对预后指标有显著影响。 结论数学模型可以对颅脑损伤患者进行预后指标评估预测。

The application of mathematical model in the analysis of multi-factor models of admission indicators and prognostic indicators for patients with brain injury

ObjectiveTo explore the influence of prognosis indicators of multiple indicators and their interactionat hospital admission in patients with brain injury. MethodsWe analyzed the clinical data of 130 patients with craniocerebral trauma who were admitted to the Department of Critical Care Medicine of the Affiliated Hospital of Yangzhou University from January 2013 to August 2017. We performed a mathematical model to identify the correlation between data at hospital admission and outcome. The clinical data of 26 patients with craniocerebral trauma from October 2017 to December 2018 were collected for external validation. ResultsSedation score (RASS) squared item, Grasse coma (GCS) score and RASS score interaction item, age and acute physiology and chronic health status (APACHEⅡ) score interaction item, heart rate and lactic acid (LAC) interaction term were significantly associated with outcome. ConclusionMathematical models can be used to assess prognostic indicators in patients with brain injury.