Clinical Informatics Department, Saint-Denis University Hospital, Saint-Denis, Reunion Island, France.
Methodological Support Unit, Saint-Denis University Hospital, Saint-Denis, Reunion Island, France.
J Med Syst. 2024 Sep 16;48(1):88. doi: 10.1007/s10916-024-02107-6.
In Intensive Care Unit (ICU), the settings of the critical alarms should be sensitive and patient-specific to detect signs of deteriorating health without ringing continuously, but alarm thresholds are not always calibrated to operate this way. An assessment of the connection between critical alarm threshold settings and the patient-specific variables in ICU would deepen our understanding of the issue. The aim of this retrospective descriptive and exploratory study was to assess this relationship using a large cohort of ICU patient stays. A retrospective study was conducted on some 70,000 ICU stays taken from the MIMIC-IV database. Critical alarm threshold values and threshold modification frequencies were examined. The link between these alarm threshold settings and 30 patient variables was then explored by computing the Shapley values of a Random Tree Forest model, fitted with patient variables and alarm settings. The study included 57,667 ICU patient stays. Alarm threshold values and alarm threshold modification frequencies exhibited the same trend: they were influenced by the vital sign monitored, but almost never by the patient's overall health status. This exploratory study also placed patients' vital signs as the most important variables, far ahead of medication. In conclusion, alarm settings were rigid and mechanical and were rarely adapted to the evolution of the patient. The management of alarms in ICU appears to be imperfect, and a different approach could result in better patient care and improved quality of life at work for staff.
在重症监护病房(ICU)中,关键警报的设置应该敏感且针对患者个体,以便在不连续响铃的情况下检测健康状况恶化的迹象,但警报阈值并不总是校准为以这种方式运行。评估关键警报阈值设置与 ICU 中患者特定变量之间的关系将加深我们对该问题的理解。本回顾性描述性和探索性研究的目的是使用大量 ICU 患者入住数据来评估这种关系。对来自 MIMIC-IV 数据库的约 70,000 例 ICU 入住进行了回顾性研究。检查了关键警报阈值值和阈值修改频率。然后,通过计算随机树森林模型的 Shapley 值来探索这些警报阈值设置与 30 个患者变量之间的关系,该模型拟合了患者变量和警报设置。该研究包括 57,667 例 ICU 患者入住。警报阈值值和警报阈值修改频率表现出相同的趋势:它们受到监测的生命体征的影响,但几乎从不受患者整体健康状况的影响。这项探索性研究还将患者的生命体征作为最重要的变量,远远领先于药物。总之,警报设置是僵化和机械的,很少根据患者的变化进行调整。ICU 中的警报管理似乎并不完善,采用不同的方法可能会为患者提供更好的护理,并提高工作人员的工作生活质量。