Centre for Healthcare Modelling and Informatics, University of Portsmouth, Portsmouth, UK.
Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.
Resuscitation. 2018 Dec;133:75-81. doi: 10.1016/j.resuscitation.2018.09.021. Epub 2018 Sep 22.
The National Early Warning System (NEWS) is based on vital signs; the Laboratory Decision Tree Early Warning Score (LDT-EWS) on laboratory test results. We aimed to develop and validate a new EWS (the LDTEWS:NEWS risk index) by combining the two and evaluating the discrimination of the primary outcome of unanticipated intensive care unit (ICU) admission or in-hospital mortality, within 24 h.
We studied emergency medical admissions, aged 16 years or over, admitted to Oxford University Hospitals (OUH) and Portsmouth Hospitals (PH). Each admission had vital signs and laboratory tests measured within their hospital stay. We combined LDT-EWS and NEWS values using a linear time-decay weighting function imposed on the most recent blood tests. The LDTEWS:NEWS risk index was developed using data from 5 years of admissions to PH, and validated on a year of data from both PH and OUH. We tested the risk index's ability to discriminate the primary outcome using the c-statistic.
The development cohort contained 97,933 admissions (median age = 73 years) of which 4723 (4.8%) resulted inhospital death and 1078 (1.1%) in unanticipated ICU admission. We validated the risk index using data from PH (n = 21,028) and OUH (n = 16,383). The risk index showed a higher discrimination in the validation sets (c-statistic value (95% CI)) (PH, 0.901 (0.898-0.905); OUH, 0.916 (0.911-0.921)), than NEWS alone (PH, 0.877 (0.873-0.882); OUH, 0.898 (0.893-0.904)).
The LDTEWS:NEWS risk index increases the ability to identify patients at risk of deterioration, compared to NEWS alone.
国家早期预警系统(NEWS)基于生命体征;实验室决策树早期预警评分(LDT-EWS)基于实验室检测结果。我们旨在通过结合这两种方法并评估其在 24 小时内对非预期重症监护病房(ICU)入住或院内死亡这一主要结局的区分能力,来开发和验证一种新的预警评分(LDTEWS:NEWS 风险指数)。
我们研究了牛津大学医院(OUH)和朴茨茅斯医院(PH)收治的年龄在 16 岁及以上的急诊医疗入院患者。每位患者的住院期间都测量了生命体征和实验室检查结果。我们使用线性时间衰减加权函数将 LDT-EWS 和 NEWS 值结合起来,该函数施加于最近的血液检测结果。LDTEWS:NEWS 风险指数是使用 PH 5 年的入院数据开发的,并在 PH 和 OUH 各 1 年的数据上进行了验证。我们使用 C 统计量测试了风险指数区分主要结局的能力。
发展队列包含 97933 例住院患者(中位年龄=73 岁),其中 4723 例(4.8%)院内死亡,1078 例(1.1%)非预期 ICU 入住。我们使用 PH(n=21028)和 OUH(n=16383)的数据验证了风险指数。该风险指数在验证组中的区分能力更高(C 统计值(95%CI))(PH,0.901(0.898-0.905);OUH,0.916(0.911-0.921)),高于单独使用 NEWS(PH,0.877(0.873-0.882);OUH,0.898(0.893-0.904))。
与单独使用 NEWS 相比,LDTEWS:NEWS 风险指数提高了识别病情恶化风险患者的能力。