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Predictors of Prehospital Delay in Patients With Acute Myocardial Infarction in Kashan City

BACKGROUND: The prehospital delay might result in death in patients with acute myocardial infarction (AMI). OBJECTIVES: This study aimed to investigate the prehospital delay and its related factors in patients with AMI admitted to Kashan’s Shahid Beheshti Hospital. PATIENTS AND METHODS: This cross-s...

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Detalles Bibliográficos
Autores principales: Saberi, Farzaneh, Adib-Hajbaghery, Mohsen, Zohrehea, Javad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Kashan University of Medical Sciences 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4348727/
https://www.ncbi.nlm.nih.gov/pubmed/25741517
Descripción
Sumario:BACKGROUND: The prehospital delay might result in death in patients with acute myocardial infarction (AMI). OBJECTIVES: This study aimed to investigate the prehospital delay and its related factors in patients with AMI admitted to Kashan’s Shahid Beheshti Hospital. PATIENTS AND METHODS: This cross-sectional study was conducted on 117 patients with AMI in the second half of 2013. The interval between the onset of symptoms and arrival at the hospital was noted and in cases of delay, the factors leading to the delay were investigated using a questionnaire. The content validity of the questionnaire was confirmed through content validity method and its internal consistency was confirmed using Cronbach's alpha coefficient. Chi-square test, odds ratio, and logistic regression analysis were used in data analysis. RESULTS: The median delay was 129 minutes (mean ± SD, 240.44 ± 295.30). Overall, 32.5% of patients were admitted within 90 minutes of symptom onset. The long distance between living locations to the hospital was the most common cause of delay to hospital admission (31.7%). Significant associations were observed between the delay time and location of residency (P = 0.00) and type of transportation vehicle (P = 0.003). Multivariate logistic regression analysis showed that the location of residency and type of transportation vehicle could significantly predict the delay time in patients with AMI (P = 0.039 and 0.036, respectively). CONCLUSIONS: The delay time from symptom onset to hospital admission was high in patients with AMI. It is necessary to create emergency medical system (EMS) stations in suburbs and train the public on the importance of quick contact with the EMS when the symptoms of an AMI are observed.