Davis John P, Wessells Dustin A, Moorman J Randall
Department of Surgery, University of Virginia, Charlottesville, VA.
Center for Advanced Medical Analytics, University of Virginia, Charlottesville, VA.
Crit Care Explor. 2020 Dec 18;2(12):e0294. doi: 10.1097/CCE.0000000000000294. eCollection 2020 Dec.
Coronavirus disease 2019 can lead to sudden and severe respiratory failure that mandates endotracheal intubation, a procedure much more safely performed under elective rather than emergency conditions. Early warning of rising risk of this event could benefit both patients and healthcare providers by reducing the high risk of emergency intubation. Current illness severity scoring systems, which usually update only when clinicians measure vital signs or laboratory values, are poorly suited for early detection of this kind of rapid clinical deterioration. We propose that continuous predictive analytics monitoring, a new approach to bedside management, is more useful. The principles of this new practice anchor in analysis of continuous bedside monitoring data, training models on diagnosis-specific paths of deterioration using clinician-identified events, and continuous display of trends in risks rather than alerts when arbitrary thresholds are exceeded.
2019冠状病毒病可导致突然且严重的呼吸衰竭,这就需要进行气管插管,而在择期而非紧急情况下进行该操作会更安全。对这一事件风险上升的早期预警,通过降低紧急插管的高风险,可使患者和医护人员都受益。当前的疾病严重程度评分系统通常仅在临床医生测量生命体征或实验室值时才更新,不太适合早期发现这种快速的临床恶化情况。我们认为,持续预测分析监测这种新的床边管理方法会更有用。这种新做法的原则基于对床边连续监测数据的分析、使用临床医生确定的事件在特定诊断的恶化路径上训练模型,以及持续显示风险趋势而非在超过任意阈值时发出警报。