Department of Neurology, Nordsjællands Hospital, Hillerød, Denmark.
Department of Neurology, Nordsjællands Hospital, Hillerød, Denmark; Department of Clinical Medicine, University of Copenhagen, Denmark.
J Stroke Cerebrovasc Dis. 2020 Apr;29(4):104667. doi: 10.1016/j.jstrokecerebrovasdis.2020.104667. Epub 2020 Feb 8.
In Denmark 15%-20% of stroke victims die within the first year. Simple and valid tools are needed to assess patients' risk of dying. The aim of this study was to identify potential predictors of 1-year mortality in stroke victims and construct a simple and valid prediction model.
Data were collected retrospectively from a cohort of 1031 stroke victims admitted over a period of 18 months at Nordsjællands Hospital, Denmark. Follow-up was 1 year after symptom onset. Multiple logistic regression analysis with backwards selection was used to identify predictors and construction of a prediction model. The model was validated using cross validation with 10,000 repeated random splits of the dataset. Area under the receiver operating characteristic curve (AUC) and Brier score were used as measures of validity.
Within the first year 186 patients died (18.0%) and 4 (0.4%) were lost to follow-up. Age (OR 1.08), gender (OR 2.19), stroke severity (OR 1.03), Early Warning Score (OR 1.17), Performance Status (ECOG) (OR 1.94), Body Mass Index (OR 0.91), the Charlton's Comorbidity Index (OR 1.17), and urinary problems (OR 2.55) were found to be independent predictors of 1-year mortality. A model including age, stroke severity, Early Warning Score, and Performance Status was found to be valid (AUC 86.5 %, Brier Score 9.03).
A model including only 4 clinical variables available shortly after admission was able to predict the 1-year mortality risk of patients with acute ischemic and haemorrhagic stroke.
在丹麦,15%-20%的中风患者会在一年内死亡。因此,需要简单有效的工具来评估患者的死亡风险。本研究旨在确定中风患者一年内死亡的潜在预测因素,并构建一个简单有效的预测模型。
数据来自丹麦 Nordjællands 医院 18 个月内收治的 1031 名中风患者的队列研究。随访时间为症状发作后 1 年。采用向后选择的多变量逻辑回归分析来识别预测因素并构建预测模型。使用数据集重复随机分割 10000 次的交叉验证来验证模型。使用接收者操作特征曲线下面积(AUC)和 Brier 评分作为有效性的衡量标准。
在最初的 1 年内,有 186 名患者死亡(18.0%),4 名患者失访(0.4%)。年龄(OR 1.08)、性别(OR 2.19)、中风严重程度(OR 1.03)、早期预警评分(OR 1.17)、表现状态(ECOG)(OR 1.94)、体重指数(OR 0.91)、Charlton 合并症指数(OR 1.17)和尿失禁问题(OR 2.55)被认为是 1 年死亡率的独立预测因素。一个包括年龄、中风严重程度、早期预警评分和表现状态的模型被证明是有效的(AUC 86.5%,Brier 评分 9.03)。
一个仅包括入院后不久就可以获得的 4 个临床变量的模型能够预测急性缺血性和出血性中风患者的 1 年死亡风险。