背景:卒中是全球成年人死亡的第二大原因。在获得紧急医疗服务(EMS)方面存在显着的地理差异。此外,有记录表明,转运延迟会影响卒中结局.这项研究旨在检查EMS转移的中风症状患者的院内死亡率的空间变化。并利用自逻辑回归模型确定其相关因素。
方法:在这项历史队列研究中,我们纳入了转移到马什哈德Ghaem医院的有中风症状的患者,作为中风病人的转诊中心,从2018年4月到2019年3月。应用自逻辑回归模型来检查院内死亡率的可能地理变化及其相关因素。所有分析均使用社会科学统计软件包(SPSS,v.16)和R4.0.0软件在0.05的显著性水平。
结果:在这项研究中,共有1,170例有中风症状的患者被纳入。医院总死亡率为14.2%,地域分布不均。自logistic回归模型结果显示院内卒中死亡率与年龄相关(OR=1.03,95%CI:1.01-1.04),救护车可及性率(OR=0.97,95%CI:0.94-0.99),最终卒中诊断(OR=1.60,95%CI:1.07-2.39),分诊水平(OR=2.11,95%CI:1.31-3.54),和住院时间(LOS)(OR=1.02,95%CI:1.01-1.04)。
结论:我们的研究结果显示,在马什哈德社区,院内卒中死亡率的可能性存在很大的地域差异。此外,年龄和性别调整后的结果强调了诸如救护车的可及性等变量之间的直接关联,筛选时间,和住院LOS与院内卒中死亡率。因此,通过减少延迟时间和提高EMS接诊率,可以改善院内卒中死亡率的预后.
BACKGROUND: Stroke is the second leading cause of death in adults worldwide. There are remarkable geographical variations in the accessibility to emergency medical services (EMS). Moreover, transport delays have been documented to affect stroke outcomes. This study aimed to examine the spatial variations in in-hospital mortality among patients with symptoms of stroke transferred by EMS, and determine its related factors using the auto-logistic regression model.
METHODS: In this historical cohort study, we included patients with symptoms of stroke transferred to Ghaem Hospital of Mashhad, as the referral center for stroke patients, from April 2018 to March 2019. The auto-logistic regression model was applied to examine the possible geographical variations of in-hospital mortality and its related factors. All analysis was performed using the Statistical Package for the Social Sciences (SPSS, v. 16) and R 4.0.0 software at the significance level of 0.05.
RESULTS: In this study, a total of 1,170 patients with stroke symptoms were included. The overall mortality rate in the hospital was 14.2% and there was an uneven geographical distribution. The results of auto-logistic regression model showed that in-hospital stroke mortality was associated with age (OR = 1.03, 95% CI: 1.01-1.04), accessibility rate of ambulance vehicle (OR = 0.97, 95% CI: 0.94-0.99), final stroke diagnosis (OR = 1.60, 95% CI: 1.07-2.39), triage level (OR = 2.11, 95% CI: 1.31-3.54), and length of stay (LOS) in hospital (OR = 1.02, 95% CI: 1.01-1.04).
CONCLUSIONS: Our results showed considerable geographical variations in the odds of in-hospital stroke mortality in Mashhad neighborhoods. Also, the age- and sex-adjusted results highlighted the direct association between such variables as accessibility rate of an ambulance, screening time, and LOS in hospital with in-hospital stroke mortality. Thus, the prognosis of in-hospital stroke mortality could be improved by reducing delay time and increasing the EMS access rate.