Temporal Trends and Risk Factors for Delayed Hospital Admission in Suspected Stroke Patients

Prevalence and influencing factors of patient delay in stroke patients: a systematic review and meta-analysis

PURPOSE

Determine the prevalence and influencing factors of patient delay in stroke patients and explore variation in prevalence by country and delayed time.

METHODS

PubMed, The Cochrane Library, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), Chinese Biomedical Database (CBM), Weipu database, and Wanfang database were comprehensively searched for observational studies from inception to April, 2023. The pooled prevalence, odds ratio (OR), and 95% confidence intervals (CI) were calculated with Stata 16.0 software.

RESULTS

In total, 2721 articles were screened and data from 70 studies involving 85,468 subjects were used in meta-analysis. The pooled prevalence of patient delay in stroke patients was 59% (95% CI, 0.54-0.64). The estimates of pooled prevalence calculated for African, Asian, and European patient delay in stroke patients were 55% (0.29-0.81), 61% (0.56-0.66), and 49% (0.34-0.64).According to the patient delay time, the prevalence of 6 h, 5 h, 4.5 h, 3.5 h, 3 h and 2 h were 54% (0.47-0.61), 73% (0.61-0.86), 60% (0.49-0.71), 81% (0.68-0.93), 52% (0.42-0.62), 63% (0.19-1.07). Distance from the place of onset to the hospital > 10 km [OR=2.49, 95%CI (1.92, 3.24)], having medical insurance [OR = 0.45, 95%CI (0.26,0.80)], lack of stroke-related knowledge [OR = 1.56, 95%CI (1.08,2.26)], education level below junior high school [OR = 1.69, 95%CI (1.22,2.36)], non-emergency medical services (Non-EMS) [OR = 2.10, 95%CI (1.49,2.97)], living in rural areas [OR = 1.54, 95%CI (1.15,2.07)], disturbance of consciousness [OR = 0.60, 95%CI (0.39,0.93)], history of atrial fibrillation [OR = 0.53, 95%CI (0.47,0.59)], age ≥ 65 years [OR = 1.18, 95%CI (1.02,1.37)], National institutes of health stroke scale (NIHSS) ≤ 4 points [OR= 2.26, 95%CI (1.06,4.79)]were factors for patient delay in stroke patients.

CONCLUSIONS

The prevalence of patient delay in stroke patients is high, we should pay attention to the influencing factors of patient delay in stroke patients and provide a theoretical basis for shortening the treatment time of stroke patients.

The support dilemma of stroke inpatients and family caregivers under COVID-19 prevention and control: a qualitative study in China

China has implemented a strict isolation system in hospitals since the COVID-19 pandemic, that adversely affected the psychology of inpatients and their caregivers. Face-to-face, semi-structured interviews with 22 stroke inpatients from two municipal hospitals were conducted to explore the psychological, emotional and related support needs of stroke inpatients and their family caregivers under this environment. Results which showed that external support for stroke inpatients and their family caregivers was insufficient highlight the necessity for developing specific nursing interventions that meet the psychological and emotional needs of inpatients and the caregivers.

Factors Associated with Prehospital Delay in Patients with Acute Stroke in South India

Background

Early hospital presentation is critical in the management of acute ischemic stroke. The effectiveness of stroke treatment is highly dependent on the amount of time lapsed between onset of symptoms and treatment. This study was aimed to identify the factors associated with prehospital delay in patients with acute stroke.

Material and Methods

A cross-sectional descriptive study was conducted in Sri Ramachandra University Hospital, India. A total of 210 patients hospitalized in the stroke unit were included. Patients' data were obtained by interviewing the patient and/or accompanying family member and by reviewing their medical records using a standard questionnaire. Associations were determined between prehospital delay (≥4.5 h) and variables of interest by using univariate and multivariate logistic regression analyses.

Results

The prehospital delay was observed in 154 patients (73.3%) and the median prehospital delay was 11.30 h. The following are the factors significantly (P < 0.05) attributed for the delay in presenting to the hospital: contextual factors like using public transport (bus), taxi, time of onset of symptoms, 7 pm-3 am; family history of stroke, perceived cognitive and behavioral factors like, wishing or praying for the symptoms to subside on its own, hesitation to travel due to long distance, delay in arranging transport, and arranging money for admission and wasting time by shopping for general practitioners, nursing homes, and hospitals. The presence of stroke symptom, headache, significantly decreased the prehospital delay.

Conclusions

Prehospital delay is high in South India and influenced by clinical, contextual, and cognitive/behavioral factors.

Organizational Factors Determining Access to Reperfusion Therapies in Ischemic Stroke-Systematic Literature Review

BACKGROUND

After onset of acute ischemic stroke (AIS), there is a limited time window for delivering acute reperfusion therapies (ART) aiming to restore normal brain circulation. Despite its unequivocal benefits, the proportion of AIS patients receiving both types of ART, thrombolysis and thrombectomy, remains very low. The organization of a stroke care pathway is one of the main factors that determine timely access to ART. The knowledge on organizational factors influencing access to ART is sparce. Hence, we sought to systematize the existing data on the type and frequency of pre-hospital and in-hospital organizational factors that determine timely access to ART in patients with AIS.

METHODOLOGY

Literature review on the frequency and type of organizational factors that determine access to ART after AIS. Pubmed and Scopus databases were the primary source of data. OpenGrey and Google Scholar were used for searching grey literature. Study quality analysis was based on the Newcastle-Ottawa Scale.

RESULTS

A total of 128 studies were included. The main pre-hospital factors associated with delay or access to ART were medical emergency activation practices, pre-notification routines, ambulance use and existence of local/regional-specific strategies to mitigate the impact of geographic distance between patient locations and Stroke Unit (SU). The most common intra-hospital factors studied were specific location of SU and brain imaging room within the hospital, and the existence and promotion of specific stroke treatment protocols. Most frequent factors associated with increased access ART were periodic public education, promotion of hospital pre-notification and specific pre- and intra-hospital stroke pathways. In specific urban areas, mobile stroke units were found to be valid options to increase timely access to ART.

CONCLUSIONS

Implementation of different organizational factors and strategies can reduce time delays and increase the number of AIS patients receiving ART, with most of them being replicable in any context, and some in only very specific contexts.

Access to acute stroke care: A retrospective descriptive analysis of stroke patients' journey to a district hospital

Introduction

The burden of stroke in Africa has increased in the last two decades, with the population undergoing a rapid epidemiological transition, with a rise in the incidence of stroke risk factors together with the gradual aging of the population. Evidence-based guidelines for acute stroke care are often not feasible in resource challenged settings but even when resources are available, considerable delays to definitive care exists. This study aims to describe the factors that influence time from symptom onset to hospital arrival in patients that present to a district level hospital Emergency Centre with confirmed ischaemic strokes.

Methods

A descriptive analysis was performed using a retrospective folder and database review. All adult patients with a confirmed ischaemic stroke, on Computed Tomography (CT) scan, presenting to Mitchells Plain Hospital Emergency Centre during the study period of 12 months (1^st of January 2019 to 31^st of December 2019), were eligible for inclusion. Data were collected from existing electronic patient databases and the time from onset of symptoms to hospital arrival was extracted from the clinical notes.

Results

A total of 730 (2%) patients presented with a diagnosis of stroke, of which 381 (52%) were included (CT confirmed ischaemic strokes). Only 48 (13%) presented within 4.5 h of symptom onset and the median time from onset of symptoms to presentation to the hospital was 24 h (IQR 12-72 h). The majority of patients (31%) arrived via a primary public emergency medical service (EMS) call, while 29% presented directly to the hospital as self-referrals with private transport. Primary public EMS calls had the shortest call-to-hospital-arrival time (1 hour and 31 minutes), even though the median time from symptom onset to hospital arrival was still 16 h.

Conclusion

The median time from symptom onset to hospital arrival for patients with stroke symptoms is much longer than what evidence-based guidelines suggest. The chain of survival for emergency stroke care is only as strong as its weakest link and the data from this study suggest that improvement campaigns should target stroke education and access to care.