Beil Michael, Moreno Rui, Fronczek Jakub, Kogan Yuri, Moreno Rui Paulo Jorge, Flaatten Hans, Guidet Bertrand, de Lange Dylan, Leaver Susannah, Nachshon Akiva, van Heerden Peter Vernon, Joskowicz Leo, Sviri Sigal, Jung Christian, Szczeklik Wojciech
Department of Medical Intensive Care, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
Unidade Local de Saúde São José, Hospital de São José, Lisbon, Portugal.
Ann Intensive Care. 2024 Jun 22;14(1):97. doi: 10.1186/s13613-024-01330-1.
Prognosis determines major decisions regarding treatment for critically ill patients. Statistical models have been developed to predict the probability of survival and other outcomes of intensive care. Although they were trained on the characteristics of large patient cohorts, they often do not represent very old patients (age ≥ 80 years) appropriately. Moreover, the heterogeneity within this particular group impairs the utility of statistical predictions for informing decision-making in very old individuals. In addition to these methodological problems, the diversity of cultural attitudes, available resources as well as variations of legal and professional norms limit the generalisability of prediction models, especially in patients with complex multi-morbidity and pre-existing functional impairments. Thus, current approaches to prognosticating outcomes in very old patients are imperfect and can generate substantial uncertainty about optimal trajectories of critical care in the individual. This article presents the state of the art and new approaches to predicting outcomes of intensive care for these patients. Special emphasis has been given to the integration of predictions into the decision-making for individual patients. This requires quantification of prognostic uncertainty and a careful alignment of decisions with the preferences of patients, who might prioritise functional outcomes over survival. Since the performance of outcome predictions for the individual patient may improve over time, time-limited trials in intensive care may be an appropriate way to increase the confidence in decisions about life-sustaining treatment.
预后决定了重症患者治疗的重大决策。已经开发出统计模型来预测重症监护的生存概率和其他结果。尽管这些模型是根据大量患者队列的特征进行训练的，但它们往往不能很好地代表高龄患者（年龄≥80岁）。此外，这一特定群体内部的异质性削弱了统计预测在为高龄个体提供决策信息方面的效用。除了这些方法学问题外，文化态度的多样性、可用资源以及法律和专业规范的差异限制了预测模型的通用性，尤其是在患有复杂多种疾病和已有功能障碍的患者中。因此，目前预测高龄患者预后的方法并不完善，可能会在个体重症监护的最佳治疗轨迹方面产生很大的不确定性。本文介绍了预测这些患者重症监护结果的最新技术水平和新方法。特别强调了将预测结果整合到个体患者的决策中。这需要对预后不确定性进行量化，并根据患者的偏好仔细调整决策，因为患者可能更看重功能结果而非生存。由于个体患者的预后预测性能可能会随着时间的推移而提高，重症监护中的限时试验可能是增加对维持生命治疗决策信心的合适方法。
