Stroke is the second leading cause of death in adults worldwide. There are remarkable geographical variations in the accessibility to emergency medical services (EMS), and transport delays have been documented worldwide to affect stroke outcomes significantly. Therefore, this study examines whether there are spatial variations in in-hospital mortality among suspected stroke patients transferred by EMS and attempts to determine its related factors using the auto logistic regression model.
In this historical cohort study, suspected stroke patients transferred to Ghaem Hospital of Mashhad by the EMS from April 2018 to March 2019 were included. Using emergency mission IDs, the baseline EMS data were integrated with the follow-up hospital records. The autologistic regression model was applied to examine the possible geographical variations in in-hospital mortality and its related factors. All analysis was carried out by SPSS version 16 and R 4.0.0 at the significant level of 0.05.
1,222 suspected stroke patients were included in this study, and the in-hospital mortality rate was 14.2%. Overall in-hospital stroke mortality was related to age, accessibility rate of an ambulance, screening time, and length of stay (p < 0.05). After stratifying by sex, we observed that mortality in men was related to age and length of stay, whereas, in women, variables of age, length of stay, accessibility rate of an ambulance, and screening time had a significant effect on in-hospital mortality among suspected stroke patients (p < 0.05).
Our results showed considerable geographical variations in in-hospital stroke mortality in Mashhad neighborhoods. Also, age- and sex-adjusted results from this study highlight the direct association between accessibility rate of an ambulance, screening time and length of stay, and in-hospital stroke mortality. The prognosis of in-hospital stroke mortality could be improved by reducing delay time and increasing the EMS access rate.