استفاده از مدل آماری رگرسیون لجستیک در تعیین فاکتورهای تاثیرگذار در تاخیر رسیدن بیماران باسکته مغزی به بیمارستان

عنوان انگليسی

Using Multiple Logistic Regression to Determine Factors Affecting Delaying Hospital Arrival of Patients with Acute Ischemic Stroke

خلاصه انگلیسی

Background: Early treatment of ischemic stroke patients who arrive at the hospital ≤4.5 hours after the onset of symptoms with recombinant tissue plasminogen activator is more beneficial and very important. Objective: This study is aimed to investigate the factors delaying the hospital arrival of patients with acute ischemic stroke by using multiple logistic regression analysis. Methods and Materials: This descriptive cross-sectional study was done on patients diagnosed with acute ischemic stroke who were referred to Ardabil city Training and Research hospital at 2018. All patients and/or patient relatives were interviewed and data were collected through a checklist including demographic and clinical data of patients to explore the involved factors delaying hospital arrival of patients and then analyzed using multiple logistic regression analysis. Results: Of all included patients, only 25.3% arrived at the hospital in ≤ 4.5 hours. By using multivariate logistic regression analysis, living in cities (P = 0.007), cigarette consumption (P = 0.032), having valvular heart disease (P = 0.008), and gender (P = 0.049) were factors associated with an early arrival to the hospital. Conclusions: Results showed that most of the patients had a considerable delay in arriving at the hospital in ≤ 4.5 hours. Thus, providing health promotion strategies to improve society awareness of early symptoms of stroke, training of local physicians about the importance of early arrival of stroke patients, and more extended ambulance services in all cities and rural areas are necessary for better management of acute stroke patients in this area.

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