Medical Intensive Care Unit, Hadassah University Hospital, POB 12000, Jerusalem 9112001, Israel.
Intensive Care and Department of Clinical Medicine, Haukeland Universitetssjukehus, Bergen, Norway.
J Crit Care. 2021 Feb;61:34-38. doi: 10.1016/j.jcrc.2020.10.006. Epub 2020 Oct 13.
Predicting the future course of critical conditions involves personal experience, heuristics and statistical models. Although these methods may perform well for some cases and population averages, they suffer from substantial shortcomings when applied to individual patients. The reasons include methodological problems of statistical modeling as well as limitations of cross-sectional data sampling. Accurate predictions for individual patients become crucial when they have to guide irreversible decision-making. This notably applies to triage situations in response to a lack of healthcare resources. We will discuss these issues and argue that analysing longitudinal data obtained from time-limited trials in intensive care can provide a more robust approach to individual prognostication.
预测危急情况下的未来病程涉及个人经验、启发式方法和统计模型。虽然这些方法在某些情况下和人群平均值上可能表现良好，但在应用于个体患者时，它们存在着很大的缺陷。原因包括统计建模的方法学问题以及横断面数据采样的局限性。当需要指导不可逆转的决策时，对个体患者进行准确预测变得至关重要。这在医疗资源短缺时的分诊情况中尤为明显。我们将讨论这些问题，并认为分析从重症监护限时试验中获得的纵向数据可以为个体预后提供更稳健的方法。
