Springer Mellanie V, Labovitz Daniel L
Department of Neurology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York.
Department of Neurology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York.
J Stroke Cerebrovasc Dis. 2018 May;27(5):1363-1367. doi: 10.1016/j.jstrokecerebrovasdis.2017.12.024. Epub 2018 Feb 8.
Studies examining predictors of delay in hospital arrival after stroke symptom onset have not accounted for patients who are found with their symptoms and cannot seek help independently. Our objective is to show that inclusion of patients who are "found down" in studies of prehospital delay biases the estimated association of sociodemographic and clinical variables with time of hospital arrival.
We performed a retrospective analysis of sociodemographic and clinical characteristics of patients with acute ischemic stroke presenting to a tertiary care hospital in the Bronx, New York.
Compared with all other patients with acute ischemic stroke (N = 1784), patients who were found down (N = 120) were more likely to be older (75 ± 13 years versus 68 ± 14 years, P < .0001), female (68% versus 53%, P = .003), Caucasian race (P < .001), have higher socioeconomic status (P = .001), more severe stroke deficits (P < .0001), use emergency medical services (P < .001), and arrive to the hospital more than 3 hours after symptom onset (P < .001). Inclusion of patients who were found down in a model predicting delay in hospital arrival decreased the strength of the association between the predictors and the outcome.
Being found with stroke symptoms confounds the association of sociodemographic and clinical variables with time of hospital arrival. Studies of predictors of prehospital delay should therefore exclude patients who are found down.
研究中风症状发作后延迟入院的预测因素时，未将那些被发现有症状且无法独立寻求帮助的患者纳入考虑。我们的目的是表明，在院前延迟研究中纳入“被发现倒地”的患者会使社会人口统计学和临床变量与入院时间之间的估计关联产生偏差。
我们对纽约布朗克斯一家三级护理医院的急性缺血性中风患者的社会人口统计学和临床特征进行了回顾性分析。
与所有其他急性缺血性中风患者（N = 1784）相比，被发现倒地的患者（N = 120）更可能年龄较大（75 ± 13岁对68 ± 14岁，P <.0001）、为女性（68%对53%，P =.003）、是白种人（P <.001）、社会经济地位较高（P =.001）、中风缺陷更严重（P <.0001）、使用紧急医疗服务（P <.001），且在症状发作后3小时以上到达医院（P <.001）。在预测入院延迟的模型中纳入被发现倒地的患者会降低预测因素与结果之间关联的强度。
被发现有中风症状会混淆社会人口统计学和临床变量与入院时间之间的关联。因此，院前延迟预测因素的研究应排除被发现倒地的患者。
