Factors affecting prehospital delay in rural and urban patients with stroke: a prospective survey-based study in Southwest Germany

Abstract

Background Reducing prehospital delay plays an important role in increasing the thrombolysis rate in patients with stroke. Several studies have identified predictors for presentation ≤4.5 h, but few compared these predictors in urban and rural communities. We aimed to identify predictors of timely presentation to the hospital and identify possible differences between the urban and rural populations. Methods From January to June 2017, we conducted a prospective survey of patients with stroke admitted to an urban comprehensive stroke centre (CSC) and a rural primary care centre (PCC). Predictors were identified using binary logistical regression. Predictors and patient characteristics were then compared between the CSC and PCC. Results Overall, 459 patients were included in our study. We identified hesitation before seeking help, awareness of the existence of a time-window, type of admission and having talked about stroke symptoms with friends/relatives who had previously had a stroke as the strongest predictors for presentation to the emergency room ≤4.5 h. Patients admitted to the rural PCC were more hesitant to seek help and less likely to contact emergency services, even though patients had comparable knowledge pertaining to stroke care concepts. Conclusions Patients from rural areas were more likely to be hesitant to seek help and contacted the EMS less frequently, despite similar self-awareness of having a stroke. Educational campaigns should focus on addressing these disparities in rural populations. Affected patients should also be encouraged to talk about their symptoms and take part in educational campaigns.

Organizational Factors Determining Access to Reperfusion Therapies in Ischemic Stroke-Systematic Literature Review

“…We identified 67 studies addressing pre-hospital organizational factors associated with delay or access to ART ( Appendix A - Table A3 ). Activation of stroke code, pre-hospital notification and use of pre-hospital emergency services [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ], mobile stroke units [ 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 ], implementation of specific electronic apps to insert and share clinical data with the hospital stuff [ 33 ], use of ambulance [ 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ], telestroke [ 47 , 48 ], implementation of specific pre-hospital protocols [ 49 , 50 ], education campaigns […”

“…Under-recognition or delays in recognition of stroke symptoms are consistently identified as one of the main causes of pre-hospital delays [ 8 , 16 ]. Hence, with no surprise, population campaigns focused on stroke recognition, severity and existence of treatment emerged as a common factor to promote ART [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 20 , 23 , 34 , 36 , 38 , 39 , 40 , 41 , 46 , 48 , 103 , 104 , 105 , 106 , 107 , 108 ]. Sustainable levels of population awareness may only be achieved by continuous education campaigns, probably at least six months each [ 53 ].…”

Exploring the use of emergency health services for stroke: what is known about when to seek emergency help and how transport decisions impact in-hospital emergency care

“…Poor stroke knowledge was associated with greater presentation delay in some studies (Chen et al, 2007;Zerwic et al, 2007), while in contrast, other studies found that having a previous history of stroke or stroke knowledge was associated with less presentation delay (Kitko et al, 2008;Ungerer et al, 2020). Still, others found that having stroke knowledge did not decrease presentation delay (Faiz et al, 2013).…”

“…When examining the literature relating to EHS use following a stroke, presentation delay emerged as a central concept. A total of ten studies that examined the association of different determinants with presentation delay were captured in this review, of these three were qualitative (Kitko et al, 2008;Moloczij et al, 2008;Zerwic et al, 2007) and seven were quantitative (Chen et al, 2007;Ekundayo et al, 2013;Faiz et al, 2013;Geffner et al, 2012;Memis et al, 2008;Seremwe et al, 2017;Ungerer et al, 2020). These are summarized in Table 3 at the end of this section.…”

“…Most studies were single-centre and were undertaken in large, urban centres and there was a paucity of data examining rural location and EHS use, highlighting a gap in the knowledge base. However, one study that examined the role of location of residence as a factor in EHS use, found that neither rural nor urban residence was associated with use (Govindarajan et al, 2013) while another study examining the same found those living in rural areas were less likely to use EHS (Ungerer et al, 2020). While ethnicity and race were not frequently examined, in studies that did explore the impact of these factors, the findings were mixed.…”