A Spatial Variation Analysis of In-Hospital Stroke Mortality Based on Integrated Pre-Hospital and Hospital Data in Mashhad, Iran

Eisa Nazar; Habibollah Esmaily; Razieh Yousefi; Jamshid Jamali; Kavian Ghandehari; Soheil Hashtarkhani; Zahra Jafari; Mohammad Taghi Shakeri

doi:10.34172/aim.2023.46

A Spatial Variation Analysis of In-Hospital Stroke Mortality Based on Integrated Pre-Hospital and Hospital Data in Mashhad, Iran

Arch Iran Med. 2023 Jun 1;26(6):300-309. doi: 10.34172/aim.2023.46.

Authors

Eisa Nazar^{1

2}, Habibollah Esmaily³, Razieh Yousefi^{4

5}, Jamshid Jamali³, Kavian Ghandehari⁶, Soheil Hashtarkhani⁷, Zahra Jafari⁸, Mohammad Taghi Shakeri³

Affiliations

¹ Psychiatry and Behavioral Sciences Research Center, Addiction Institute, Mazandaran University of Medical Sciences, Mazandaran, Iran.
² Orthopedic Research Center, Mazandaran University of Medical Sciences, Sari, Iran.
³ Department of Biostatistics, School of Public Health, Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
⁴ Student Research Committee, Mashhad University of Medical Sciences, Mashhad, Iran.
⁵ Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
⁶ Neurocognitive Research Center, Department of Neurology, Mashhad University of Medical Sciences, Mashhad, Iran.
⁷ Center for Biomedical Informatics, Department of Pediatrics, University of Tennessee Health Science Center, Memphis, USA.
⁸ Clinical Research Development Unit, Ghaem Hospital, Mashhad University of Medical Sciences, Mashhad, Iran.

Abstract

Background: Despite significant advances in the quality and delivery of specialized stroke care, there still persist remarkable spatial variations in emergency medical services (EMS) transport delays, stroke incidence, and its outcomes. Therefore, it is very important to investigate the possible geographical variations of in-hospital stroke mortality and to identify its associated factors.

Methods: This historical cohort study included suspected stroke cases transferred to Ghaem Hospital of Mashhad by the EMS from March 2018 to March 2019. Using emergency mission IDs, the pre-hospital emergency data were integrated with the patient medical records in the hospital. We used the Bayesian approach for estimating the model parameters.

Results: Out of 301 patients (142 (47.2%) females vs. 159 (52.8%) males) with a final diagnosis of stroke, 61 (20.3%) cases had in-hospital mortality. Results from Bayesian spatial log-logistic proportional odds (PO) model showed that age (PO=1.07), access rate to EMS (PO=0.78), arrival time (evening shift vs. day shift, PO=0.09), and sequelae variables (PO=9.20) had a significant association with the odds of in-hospital stroke mortality (P<0.05). Furthermore, the odds of in-hospital stroke mortality were higher in central urban areas compared to suburban areas.

Conclusion: Marked regional variations were found in the odds of in-hospital stroke mortality in Mashhad. There was a direct association between age and odds of in-hospital stroke mortality. Hence, the prognosis of in-hospital stroke mortality could be improved by better control of hypertension, prevention of the occurrence of sequelae, increasing the access rate to EMS, and optimizing shift work schedule.

Keywords: Bayesian; In-hospital Mortality; Iran; Sequelae; Spatial survival model; Stroke.

© 2023 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

MeSH terms

Bayes Theorem
Cohort Studies
Female
Hospital Mortality
Hospitals
Humans
Iran / epidemiology
Male
Stroke* / therapy