Byrne Declan, Conway Richard, Cournane Seán, O'Riordan Deirdre, Silke Bernard
Department of Internal Medicine, St James's Hospital, Dublin 8, Ireland.
Medical Physics and Bioengineering Department, St Vincent's University Hospital, Dublin 4, Ireland.
Acute Med. 2018;17(1):18-25.
An Illness Severity and Co-morbidity composite score can predict 30-day mortality outcome.
We computed a summary risk score (RS) for emergency medical admissions and used cluster analysis to define four subsets Results: Four cluster groups were defined. Cluster 1 - RS 7 points (IQR 5, 8) Cluster 2 - 9 (IQR 8, 11), Cluster 3 - 12 (IQR 11, 13) and Cluster 4 - 14 (IQR 13, 15). Clusters predicted 30-day in hospital mortality OR 1.86 (95%CI: 1.82, 1.92); respective rates 1.4% (95% CI: 1.3%, 1.6%), 3.4% (95% CI: 3.1%, 3.6%), 7.8% (95% CI: 7.5%, 8.1%) and 16.5% (95% CI: 15.7%, 17.2%).
Cluster grouping of Risk Score was age related; strongest outcome determinant was Acute Illness Severity.
疾病严重程度和共病综合评分可预测30天死亡率结局。
我们计算了急诊入院的综合风险评分（RS），并使用聚类分析定义了四个亚组。结果：定义了四个聚类组。聚类1 - RS 7分（四分位距5，8），聚类2 - 9分（四分位距8，11），聚类3 - 12分（四分位距11，13），聚类4 - 14分（四分位距13，15）。聚类可预测30天住院死亡率，比值比为1.86（95%置信区间：1.82，1.92）；各自的死亡率分别为1.4%（95%置信区间：1.3%，1.6%）、3.4%（95%置信区间：3.1%，3.6%）、7.8%（95%置信区间：7.5%，8.1%）和16.5%（95%置信区间：15.7%，17.2%）。
风险评分的聚类分组与年龄相关；最强的结局决定因素是急性疾病严重程度。
