Predicting factors for Delayed Hospital Arrival of Acute Stroke Patients
DOI:
https://doi.org/10.3329/bjm.v36i2.78535Keywords:
predictors of delayed arrivalAbstract
Background: Delayed hospital arrival following acute stroke is one of the important influencing factors for morbidity and mortality. The aim of the study was to identify the risk factors associated with hospital-delayed arrival among stroke patients.
Methods: This cross-sectional study was carried out in the Department of Medicine, DMCH, for a 12-month period following ethical approval. After giving informed written consent, 311 patients with acute stroke were included in the study. Data were collected using a semi-structured questionnaire and direct interview and analyzed using SPSS-20.
Results: Among 311 stroke patients, 134 were in the early arrival group, and 177 were in the late arrival group. In our cross-sectional study, age did not significantly impact arrival time (p = 0.491). A significant relationship was found between residence and arrival time (p = 0.010), with rural residents more likely to arrive late than semi-urban residents (OR = 0.720). Education level did not significantly affect arrival time (p = 0.576), but those with secondary education had higher odds of delayed arrival than those with higher education (OR = 32.242). Chronic conditions such as cardiac failure (p = 0.523), previous stroke (p = 0.577), diabetes (p = 0.273), hypertension (p = 0.620), and malignancy (p = 0.677) did not significantly influence arrival time. However, chronic obstructive pulmonary disease (COPD) was significantly associated with delayed hospital arrival (p = 0.020, OR = 4.533). Stroke symptoms played a critical role, with patients experiencing aphasia (p = 0.061, OR = 3.759) and dysarthria (p = 0.002, OR = 2.814) more likely to arrive late. At the same time, those with hemiparesis were less likely to arrive late (p = 0.000, OR = 0.113). Patients residing more than 15 km from the hospital were more likely to arrive late, and factors such as traffic jams, indecision about hospitalization, and mode of transportation contributed to delays. Notably, patients with knowledge about stroke were significantly less likely to arrive late (p = 0.000, OR = 0.351), and those living within 5 km from the hospital also had a reduced likelihood of late arrival (p = 0.000, OR = 0.036). Indecision about hospitalization significantly predicted late arrival (p = 0.000, OR = 10.653). Additionally, patients with hemianopia had lower odds of delayed arrival (p = 0.014, OR = 0.074), and those living within 5-15 km had reduced odds compared to those living more than 15 km away (p = 0.010, OR = 0.364).
Conclusion: Symptoms of stroke, as well as sociodemographic factors, significantly affected hospital arrival on time. Proper strategy and planning should be applied to enhance people's knowledge of stroke to decrease the unfavorable outcome.
Bangladesh J Medicine 2025; 36(2): 99-107
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