计算机化生理学方程的回顾性验证,以预测重症儿童的每分钟通风需求
Jonathan H Pelletier1, Jaskaran Rakkar2, Alicia K Au1,2,3,4,5,6,7
1Division of Critical Care, Department of Pediatrics, Akron Children's Hospital, Akron, OH.
概括
一个新的计算机化方程准确地预测了机械通风的危急病患儿童微小的通风需求. 这种工具在75%的病例中优于临床医生的调整,为儿科重症监护提供了有希望的进步.
科学领域:
- 儿科重症监护医学 儿科重症监护医学
- 呼吸系统生理学 呼吸系统生理学
- 医疗信息学 医疗信息学
背景情况:
- 机械通风 (MV) 是重症儿童的基石疗法.
- 精确的MV定位对于优化患者的治疗结果和最大限度地减少呼吸机引起的肺损伤至关重要.
- 调整MV设置的现有方法通常依赖于临床医生的判断,这可能是可变的.
研究的目的:
- 验证计算机化生理学方程,用于预测儿科患者每分钟通风需求.
- 为了将这个方程的性能与临床医生驱动的呼吸器调整在in silico试验中进行比较.
- 评估方程在预测动脉血液气体 (ABG) 值方面的准确性.
主要方法:
- 以四级儿科重症监护室 (PICU) 的电子病历为依据的回顾性队列研究.
- 纳入标准:儿童在侵袭性MV上进行连续ABG分析和药理神经肌肉阻塞 (NMB).
- 基于ABG和分钟通风数据,使用计算机方程预测PaCO2和pH值;其建议与临床医生的行动在一个in silico试验中进行比较.
主要成果:
- 该研究分析了484名患者的15,121个ABG. 中位数的PaCO2预测误差为0.00 mm Hg.
- 在涉及1,499个ABG的in silico试验中,75.0%的病例中,计算机方程的建议比临床医生的行动更有利.
- 敏感性分析证实了在各种临床情景中方程的良好表现.
结论:
- 预测每分钟通风需求的计算机方程式在临床医生调整的比较中表现优异,在重症儿童的75%分析的ABG中表现优异.
- 这种预测工具显示了改善儿童重症监护室机械通风管理的潜力.
- 需要进一步的前性验证研究来证实这些发现在现实世界的临床实践中.
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