开发临床工具来估计高流氧治疗期间的呼吸力度:一个多中心队列研究
A Protti1,2, R Tonelli3,4, F Dalla Corte2
1Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy.
我们开发了两种模型来估计高流氧治疗患者的呼吸力度,使用COVID-19状态和血液气体分析等因素. 这些称为BREF的模型显示出有希望的临床评估结果.
科学领域:
- 关键护理医学 关键护理医学
- 呼吸系统生理学 呼吸系统生理学
- 医学建模 医学建模
背景情况:
- 在接受高流氧疗法 (HFOT) 的非输管患者中量化呼吸努力在临床上具有意义,但具有挑战性.
- 现有的评估HFOT患者呼吸困扰的方法缺乏精度.
- 开发准确的估计工具对于优化患者管理至关重要.
研究的目的:
- 开发和验证两个预测模型,以估计HFOT的非输管患者的呼吸力 (最大食道压力偏移,ΔPes).
- 确定预测高呼吸力度 (ΔPes>10 cmH2O) 的关键临床和生理参数.
主要方法:
- 分析了260名先前接受过HFOT治疗的患者的数据.
- 开发一个多变量线性回归模型来估计 ΔPes.
- 开发一个多变量后勤回归模型来预测 ΔPes > 10 cmH2O 的风险.
- 包括诸如COVID-19状态,基数过量 (BEa),呼吸速率和PaO2:FiO2比率等预测因素.
主要成果:
- 一个线性模型使用COVID-19状态,BEa,呼吸速率和PaO2:FiO2估计了ΔPes,达到0.39.2的调整后R2.
- 一个物流模型使用BEa,呼吸速率和PaO2:FiO2预测了ΔPes>10cmH2O的风险,ROC曲线下的面积为0.79.
- 这些模型被集体命名为BREF (呼吸努力).
结论:
- 成功开发了两种新型模型,即BREF,用于估计HFOT患者的呼吸力和预测高呼吸力风险.
- 这些模型结合了现有的临床和生理数据.
- 需要进一步的验证研究来证实BREF模型的临床实用性.
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