Reasons for Prehospital Delay in Acute Ischemic Stroke

We analyzed the associations between area-level socioeconomic status (SES) and prehospital delay in acute ischemic stroke (AIS) patients by degree of urbanization with the use of an ecological framework. The participants were 13,637 patients over 18 years of age who experienced AIS from 2007 to 2012 and were admitted to any of the 29 hospitals in South Korea. Area-level SES was determined using 11 variables from the 2010 Korean census. The primary outcome was a prehospital delay (more than three hours from AIS onset time). Multilevel logistic regression was conducted to define the associations of individual- and area-level SES with prehospital delay after adjusting for confounders, which includes the use of emergency medical services (EMS) and individual SES. After adjusting for covariates, it was found that the area-level SES and urbanization were not associated with prehospital delay and EMS use was beneficial in both urban and rural areas. However, after stratification by urbanization, low area-level SES was significantly associated with a prehospital delay in urban areas (adjusted odds ratio (aOR) 1.24, 95% confidence interval (CI) 1.04–1.47) but not in rural areas (aOR 1.04, 95% CI 0.78–1.38). Therefore, we posit that area-level SES in urban areas might be a significant barrier to improving prehospital delay in AIS patients.

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“Hesitating and Puzzling”: The Experiences and Decision Process of Acute Ischemic Stroke Patients with Prehospital Delay after the Onset of Symptoms

Healthcare ◽

10.3390/healthcare9081061 ◽

2021 ◽

Vol 9 (8) ◽

pp. 1061

Author(s):

Pao-Yu Wang ◽

Lee-Ing Tsao ◽

Yu-Wei Chen ◽

Ying-Tao Lo ◽

Hui-Lin Sun

Keyword(s):

Ischemic Stroke ◽

Acute Ischemic Stroke ◽

Decision Process ◽

Public Awareness ◽

Sudden Change ◽

Recombinant Tissue Plasminogen Activator ◽

Disable Person ◽

Medical Attention ◽

Stroke Patients ◽

Prehospital Delay

Despite campaigns to increase public awareness of stroke symptoms by advocating FAST (Face-Arms-Speech-Time), some stroke patients still show delays in the recognition of and response to stroke symptoms and miss the golden first 4.5 h to receive rt-PA (recombinant tissue plasminogen activator) treatment. The aim of this study was to explore how acute ischemic stroke patients with prehospital delay seek help and undergo the decision process before arriving at the hospital. A qualitative approach using a grounded theory was applied. There were 24 ischemic stroke patients recruited by purposive sampling. Our main findings were: “Hesitating and puzzling” was the core category to describe and guide the process of acute ischemic stroke patients with prehospital delay. During the process, “Awareness the sudden change of physical sensation and/or function” was the antecedent category. In the prehospital delay experience, the following five interaction categories were identified: (1) “Self-judgment and interpretation according to previous experience,” (2) “Puzzling and doubting—it may only be a minor problem,” (3) “Self-treatment or seeking medical attention nearby,” (4) “Unexpected symptoms getting worse” needing immediate advanced medical help and (5) “Rushing to ER with different transportation—self-alerting that serious disease is coming.” Eventually, the patients “Regret to delay seeking treatment and become a disable person.” The process of prehospital delay provides some hidden cues for patients to increase their knowledge about strokes. The study emphasizes the importance of educating community residents about identifying stroke symptoms, breaking the myth of folk therapy, and seeking medical attention immediately. These results will assist healthcare providers by offering references for designing patient-centric educational strategies for preventing stroke prehospital delay to improve the quality of stroke medical care.

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Decision letter for "Machine learning is a valid method for predicting prehospital delay after acute ischemic stroke"

10.1002/brb3.1794/v2/decision1 ◽

2020 ◽

Keyword(s):

Machine Learning ◽

Ischemic Stroke ◽

Acute Ischemic Stroke ◽

Prehospital Delay ◽

Valid Method

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Review for "Machine learning is a valid method for predicting prehospital delay after acute ischemic stroke"

10.1002/brb3.1794/v1/review1 ◽

2020 ◽

Keyword(s):

Machine Learning ◽

Ischemic Stroke ◽

Acute Ischemic Stroke ◽

Prehospital Delay ◽

Valid Method

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Stroke awareness decreases prehospital delay after acute ischemic stroke in korea

BMC Neurology ◽

10.1186/1471-2377-11-2 ◽

2011 ◽

Vol 11 (1) ◽

Cited By ~ 66

Author(s):

Young Seo Kim ◽

Sang-Soon Park ◽

Hee-Joon Bae ◽

A-Hyun Cho ◽

Yong-Jin Cho ◽

...

Keyword(s):

Ischemic Stroke ◽

Acute Ischemic Stroke ◽

Prehospital Delay ◽

Stroke Awareness

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Early Hospital Arrival After Acute Ischemic Stroke Is Associated With Family Members' Knowledge About Stroke

Frontiers in Neurology ◽

10.3389/fneur.2021.652321 ◽

2021 ◽

Vol 12 ◽

Author(s):

Rongyu Wang ◽

Zhiqiang Wang ◽

Dongdong Yang ◽

Jian Wang ◽

Chongji Gou ◽

...

Keyword(s):

Ischemic Stroke ◽

Acute Ischemic Stroke ◽

Family Members ◽

Intravenous Thrombolysis ◽

Teaching Hospitals ◽

Prehospital Delay ◽

Early Arrival ◽

Consciousness Disturbance ◽

And Behavior ◽

The Impact

Background and Purpose: Prehospital delay is the major factor limiting intravenous thrombolysis and mechanical thrombectomy in acute ischemic stroke (AIS). This study aimed to: (1) identify factors related to prehospital delay and (2) determine the impact of recognition and behavior of family members on patient delay.Methods: A cross-sectional, multicenter study was conducted at six teaching hospitals in China between December 1, 2018 and November 30, 2019. Patients who experienced AIS within 7 days of onset were interviewed.Results: Of 1,782 consecutive patients (male, 57.97%; mean age, 66.3 ± 9.65 years) who had an AIS, 267 (14.98%) patients arrived within 4.5 h and 722 (40.52%) patients arrived within 6 h of stroke onset. Among patients who arrived within 4.5 h, 103 (38.6%) received thrombolysis. Age over 65 years (OR, 2.009; 95% CI, 1.014–3.982), prior stroke (OR, 3.478; 95% CI, 1.311–9.229), blurred vision (OR, 3.95; 95% CI, 1.71–9.123), and patients deciding to seek medical help (OR, 3.097; 95% CI, 1.417–6.769) were independently associated with late arrival. In contrast, sudden onset of symptoms (OR, 0.075; 95% CI, 0.028–0.196), the National Institutes of Health Stroke Scale 7–15 (OR, 0.093; 95% CI, 0.035–0.251), consciousness disturbance (OR, 0.258; 95% CI, 0.091–0.734), weakness (OR, 0.265; 95% CI, 0.09–0.784), arrival by ambulance (OR, 0.102; 95% CI, 0.049–0.211), decision time <30 min (OR, 0.008; 95% CI, 0.003–0.018), and family member understanding stroke requires early treatment (OR, 0.224; 95% CI, 0.109–0.462) were independently associated with early arrival.Conclusions: The prehospital delay in China lags behind Western countries. Recognition and behavior of stroke patients' family members may play a key role in early arrival.

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